The authors wish to acknowledge the financial support of NIH/NCI R01 CA160771, P30 CA006973, Philips Research North America, Briarcliff Manor, NY, USA and the French Society of Radiology (SFR).

1. Patient Selection
<ol>
	<li>Select patient eligible for drug eluding beads loaded with Adriamycin (DEB-TACE) with primary hepatic tumors such as HCC at a multidisciplinary gastro-intestinal oncology team conference and with primary teams (i.e. surgical oncology, radiology, interventional radiology, medical oncology).</li>
	<li>Place the patient into the supine position on the angiography table and sedate him.</li>
	<li>Premedicate the patient to reduce systemic effects of inflammatory response and nausea (Diphenhydramine intravenous (IV), Dexamethasone IV and Ondansetron IV).</li>
	<li>Prepare patient&#39;s right groin and drape in the usual sterile fashion.</li>
</ol>
2. &#34;See&#34; the Tumor
<ol>
	<li>Catheterization of the common hepatic artery
	<ol>
		<li>Access the right common femoral artery with a micro-puncture needle using Seldinger&#39;s technique, insert a sheath and attach to saline flush.</li>
		<li>Catheterize sequentially the superior mesenteric artery (SMA) and the celiac axis with an angiographic catheter.</li>
		<li>Perform an angiogram of the SMA to ensure standard anatomy, lack of replaced hepatic arterial supply and to confirm portal vein patency.</li>
		<li>Perform a celiac artery angiogram to determine anatomy and hepatic arterial blood supply.</li>
		<li>Advance coaxially a microcatheter through the catheter into the right or left hepatic artery depending on tumor location.</li>
		<li>Perform a repeat right or left superselective hepatic arteriogram to confirm the location of the tumor(s).</li>
		<li>Correlate tumor(s) seen on the intraprocedural imaging to preprocedural cross sectional imaging findings (MRI or MDCT).</li>
	</ol>
	</li>
	<li>Intraprocedural pretreatment Dual Phase cone-beam computed tomography
	<ol>
		<li>Instruct the sedated patient to be at end-expiration apnea during each of the CBCT scans with free breathing between the early arterial and delayed venous phase scans. If necessary, administer oxygen to the patients during the CBCT acquisition to minimize the discomfort of breath holding.</li>
		<li>Coordinate with anesthesiologist for timing and to minimize overlying artifact-inducing equipment.</li>
		<li>Place for each CBCT scan the area of interest (liver) roughly in the system isocenter. Trigger the first scan three seconds after power contrast injection (amount, 18 ml; rate 2 ml/sec; 300 mg/ml) through the catheter in the common hepatic.</li>
		<li>Perform a DP-CBCT: two 5 sec CBCT scans (early arterial and late venous phases) were acquired during a single contrast media injection with a 3 sec delay before the first scan. At the conclusion of the 1st scan, the patient is instructed to breathe 1-2x and then continue to hold breath at end-expiration apnea during the second scan starts.</li>
	</ol>
	</li>
</ol>
3. Intervention Planning: Tumor Detection, Tumor Segmentation, 3D Roadmap
<ol>
	<li>Analyze the two scans (early arterial and late venous phases) automatically codisplayed in the workstation.</li>
	<li>Control the automatic registration and overlay of the two scans and if necessary adjust manually, and validate the two CBCT acquisitions to make them match to each other in all three planes (axial, coronal, and sagittal planes)</li>
	<li>Correlate the targeted tumor(s) defined by CBCT with other preprocedural imaging. Select the prototype software to plan access to the targeted lesions and generate a 3D roadmap to guide device navigation.</li>
	<li>Segment the targeted tumor(s) from where best visualized; often the delayed venous phase scan unless better visualization is achieved on arterial phase. Atypical HCC (hypo-vascular) can also be easily segmented. A few seconds after the DP CBCT is completed, the reconstruction is ready (this rapid reconstruction is enabled by a fiber optic link between the image acquisition and the reconstruction computers).</li>
	<li>Verify the vessel path on CBCT images automatically detected from the early arterial phase CBCT and extracted by the software in sagittal, coronal and axial planes to ensure that the vessel chosen and path mapped do supply the desired tumor(s).</li>
	<li>Overlay and confirm&#160;segmented tumor(s) and tumor(s) feeding arteries, and the 3D roadmap on fluoroscopy.</li>
</ol>
4. Reach the Tumor
<ol>
	<li>Plan the intervention to target the tumor(s), like internet-based highway maps.</li>
	<li>Use the 3D overlayed roadmap synchronized on live fluoroscopy to C-arm and table movement to catheterize targeted tumor(s) feeding arteries.</li>
	<li>Choose the best C-arm/table position, angle, and magnification that best facilitates catheterization to minimize vessel overlap and foreshortening to easily target tumor(s).</li>
	<li>If needed, adjust the 3D roadmap to better match on the fluoroscopy in case of patient movement to mitigate the need for creating a new roadmap and minimize the need for additional contrast injection and X-ray exposure.</li>
	<li>Reach each tumor(s) feeding artery using the 3D navigation guidance, to minimizing delivery of chemo-embolizing material to healthy tissue and maximizing the selective drug dose to the tumor(s).</li>
</ol>
5. Treat the Tumor - Measurement of Treatment Success
<ol>
	<li>Embolize the targeted tumor(s) with drug eluding beads thought the microcatheter to the contrast stasis into the tumor before detection of any backflow.</li>
	<li>Perform a post-TACE DP-CBCT (as described above) to assess the treatment success.</li>
	<li>Assess a defect of contrast enhancement in the target tumor(s) (due to blood vessel embolization) after a DEB-TACE</li>
	<li>In case of minimal decrease of tumor enhancement and/or there is not enhancement defect, look for aberrant vessels feeding the tumor, complete embolization with additional drug eluding beads agent volume or treat extra-hepatic vessels in the same or future TACE session. Perform additional selective CBCT during selective hepatic arteriography within collateralized or parasitized vasculature to define alternate tumor supplies if necessary.</li>
	<li>At the end of the procedure, remove the microcatheter, the catheter, and the sheath and make homeostasis.</li>
</ol>

<ol>
	<li>Feldkamp, L. A., Davis, L. C., Kress, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Practical+cone-beam+algorithm.">Practical cone-beam algorithm.</a> J. Opt. Soc. Am. 1, (1984).</li><li>Abi-Jaoudeh, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multimodality+image+fusion-guided+procedures:+technique,+accuracy,+and+applications.">Multimodality image fusion-guided procedures: technique, accuracy, and applications.</a> Cardiovasc. Intervent. Radiol. 35, 986-998 (2012).</li><li>Mistretta, C. A., Grist, T. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=X-ray+digital+subtraction+angiography+to+magnetic+resonance-digital+subtraction+angiography+using+three-dimensional+TRICKS.+Historical+perspective+and+computer+simulations:+a+review.">X-ray digital subtraction angiography to magnetic resonance-digital subtraction angiography using three-dimensional TRICKS. Historical perspective and computer simulations: a review.</a> Invest Radiol. 33, 496-505 (1998).</li><li>Hirota, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cone-beam+CT+with+flat-panel-detector+digital+angiography+system:+early+experience+in+abdominal+interventional+procedures.">Cone-beam CT with flat-panel-detector digital angiography system: early experience in abdominal interventional procedures.</a> Cardiovasc. Intervent. Radiol. 29, 1034-1038 (2006).</li><li>Wallace, M. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+C-arm+cone-beam+CT:+applications+in+the+interventional+suite.">Three-dimensional C-arm cone-beam CT: applications in the interventional suite.</a> J. Vasc. Interv. Radiol. 20, 523-537 (2009).</li><li>Richter, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flat+panel+detector+angiographic+CT+for+stent-assisted+coil+embolization+of+broad-based+cerebral+aneurysms.">Flat panel detector angiographic CT for stent-assisted coil embolization of broad-based cerebral aneurysms.</a> AJNR Am. J. Neuroradiol. 28, 1902-1908 (2007).</li><li>Racadio, J. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Live+3D+guidance+in+the+interventional+radiology+suite.">Live 3D guidance in the interventional radiology suite.</a> Am. J. Roentgenol. 189, 357-364 (2007).</li><li>Loffroy, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparing+the+detectability+of+hepatocellular+carcinoma+by+C-arm+dual-phase+cone-beam+computed+tomography+during+hepatic+arteriography+with+conventional+contrast-enhanced+magnetic+resonance+imaging.">Comparing the detectability of hepatocellular carcinoma by C-arm dual-phase cone-beam computed tomography during hepatic arteriography with conventional contrast-enhanced magnetic resonance imaging.</a> Cardiovasc. Intervent. Radiol. 35, 97-104 (2012).</li><li>Higashihara, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diagnostic+accuracy+of+C-arm+CT+during+selective+transcatheter+angiography+for+hepatocellular+carcinoma:+comparison+with+intravenous+contrast-enhanced,+biphasic,+dynamic+MDCT.">Diagnostic accuracy of C-arm CT during selective transcatheter angiography for hepatocellular carcinoma: comparison with intravenous contrast-enhanced, biphasic, dynamic MDCT.</a> Eur. Radiol. 22, 872-879 (2012).</li><li>Sunshine, J. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Utilization+of+interventional+oncology+treatments+in+the+United+States.">Utilization of interventional oncology treatments in the United States.</a> J. Vasc. Interv. Radiol. 21, 1054-1060 (2010).</li><li>Lin, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluating+tumors+in+transcatheter+arterial+chemoembolization+(TACE)+using+dual-phase+cone-beam+CT.">Evaluating tumors in transcatheter arterial chemoembolization (TACE) using dual-phase cone-beam CT.</a> Minim. Invasive Ther. Allied Technol. 20, 276-281 (2011).</li><li>Miyayama, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detection+of+corona+enhancement+of+hypervascular+hepatocellular+carcinoma+by+C-arm+dual-phase+cone-beam+CT+during+hepatic+arteriography.">Detection of corona enhancement of hypervascular hepatocellular carcinoma by C-arm dual-phase cone-beam CT during hepatic arteriography.</a> Cardiovasc. Intervent. Radiol. 34, 81-86 (2011).</li><li>Tacher, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Semi-automatic+volumetric+tumor+segmentation+for+hepatocellular+carcinoma:+Comparison+between+C-arm+Cone+Beam+Computed+Tomography+and+MRI.">Semi-automatic volumetric tumor segmentation for hepatocellular carcinoma: Comparison between C-arm Cone Beam Computed Tomography and MRI.</a> Acad. Radiol. 20, 446-452 (2013).</li><li>Pellerin, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+Semi-automatic+Volumetric+VX2+Hepatic+Tumor+Segmentation+from+Cone+Beam+CT+and+Multi-detector+CT+with+Histology+in+Rabbit+Models.">Comparison of Semi-automatic Volumetric VX2 Hepatic Tumor Segmentation from Cone Beam CT and Multi-detector CT with Histology in Rabbit Models.</a> Acad Radiol. 20, 115-121 (2013).</li><li>Deschamps, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computed+Analysis+of+Three-Dimensional+Cone-Beam+Computed+Tomography+Angiography+for+Determination+of+Tumor-Feeding+Vessels+During+Chemoembolization+of+Liver+Tumor:+A+Pilot+Study.">Computed Analysis of Three-Dimensional Cone-Beam Computed Tomography Angiography for Determination of Tumor-Feeding Vessels During Chemoembolization of Liver Tumor: A Pilot Study.</a> Cardiovasc. Intervent. Radiol. , (2010).</li><li>Miyayama, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Usefulness+of+cone-beam+computed+tomography+during+ultraselective+transcatheter+arterial+chemoembolization+for+small+hepatocellular+carcinomas+that+cannot+be+demonstrated+on+angiography.">Usefulness of cone-beam computed tomography during ultraselective transcatheter arterial chemoembolization for small hepatocellular carcinomas that cannot be demonstrated on angiography.</a> Cardiovasc. Intervent. Radiol. 32, 255-264 (2009).</li><li>Takayasu, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Superselective+transarterial+chemoembolization+for+hepatocellular+carcinoma.+Validation+of+treatment+algorithm+proposed+by+Japanese+guidelines.">Superselective transarterial chemoembolization for hepatocellular carcinoma. Validation of treatment algorithm proposed by Japanese guidelines.</a> J. Hepatol. 56, 886-892 (2012).</li><li>Loffroy, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intra-Procedural+C-Arm+Dual-Phase+Cone+Beam+CT+Imaging+to+predict+Response+to+Drug-Eluting+Beads+Transcatheter+Arterial+Chemoembolization+in+Patients+with+Hepatocellular+Carcinoma?.">Intra-Procedural C-Arm Dual-Phase Cone Beam CT Imaging to predict Response to Drug-Eluting Beads Transcatheter Arterial Chemoembolization in Patients with Hepatocellular Carcinoma?.</a> Radiol. , 266-636 (2013).</li><li>Iwazawa, J., Ohue, S., Hashimoto, N., Muramoto, O., Mitani, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Survival+after+C-arm+CT-assisted+chemoembolization+of+unresectable+hepatocellular+carcinoma.">Survival after C-arm CT-assisted chemoembolization of unresectable hepatocellular carcinoma.</a> Eur. J. rad. , (2012).</li><li>Grass, M., Guillemaud, R., Rasche, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Tomogr. , 287-306 (2010).</li><li>Lin, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> RSNA. , (2011).</li><li>Sch&#228;fer, D., Ahrens, M., Eshuis, P., Grass, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> , 83132V (2011).</li><li>Sch&#228;fer, D., Borgert, J., Rasche, V., Grass, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Motion-compensated+and+gated+cone+beam+filtered+back-projection+for+3-D+rotational+X-ray+angiography.">Motion-compensated and gated cone beam filtered back-projection for 3-D rotational X-ray angiography.</a> IEEE Trans. Med. Imaging. 25, 898-906 (2006).</li><li>Sch&#228;fer, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Breathing+motion+compensated+reconstruction+for+C-arm+cone+beam+CT+imaging:+initial+experience+based+on+animal+data.">Breathing motion compensated reconstruction for C-arm cone beam CT imaging: initial experience based on animal data.</a> Phys. Med. Imaging. , 83131D (2012).</li><li>Rao, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> RSNA 2011. , E353B (2011).</li><li>Tacher, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Image+quality+improvements+in+C-Arm+CT+(CACT)+for+liver+oncology+applications:+Preliminary+study+in+rabbits.">Image quality improvements in C-Arm CT (CACT) for liver oncology applications: Preliminary study in rabbits.</a> Minim. Invasive Ther. Allied Technol. , (2013).</li></ol>

M. Lin, A. Radaelli, B. Carelsen, and N. Noordhoek: Philips employee. J.F. Geschwind: Financial activities related to the present article: Philips Healthcare. Financial activities not related to the present article: J.F. Geschwind is a paid consultant for Biocompatibles, Bayer Healthcare, Guerbet, Nordion, Merit, Abbott, and Jennerex; institution has grants or grants pending from Biocompatibles, Genentech, Bayer Healthcare, Nordion, Context Vision, and CeloNova. BJW has a cooperative research and development agreement with Philips Healthcare and Biocompatibles, and is supported by NIH Intramural Research Program and NIH Grant Z1A BC-011242-04. The other authors have disclosed no relevant financial relationships.
Open access fees supported by Philips Healthcare

DP-CBCT is a useful tool to facilitate the three main steps in intra-arterial liver therapy: tumor localization (see), navigation planning and intraprocedural guidance for catheterization (reach), and intraprocedural evaluation of treatment goals and success (treat).
Firstly, DP-CBCT is as equally sensitive and specific for detecting HCC as current gold standard imaging techniques including, contrast-enhanced MRI and MDCT8. In addition, tumor segmentation and volume calculations on DP-CBCT are precise and reproducible13. Furthermore, the volume and the spatial localization of target lesions on CBCT and on MRI are strongly correlated13. Most importantly, this information is available during the procedure, when it is most needed.
Secondly, DP-CBCT can be used to generate a navigation &#34;map&#34; in order to reach difficult lesions and improving tumor targeting results in decreased nontarget embolization, increased tumor coverage and preservation of normal hepatic tissue.
Thirdly, the use of DP-CBCT immediately following therapy is predictive of treatment success, and may be used instead of a six weeks MRI or MDCT to assess treatment completeness18.
While respiratory motion can induce misalignment in image registration, the 3D roadmap can be adjusted visually by the operator using the catheter&#39;s position on fluoroscopy as a reference. Moreover more significant patient motion can be corrected manually by shifting the 3D roadmap on real-time fluoroscopy using bony landmarks or the catheter as a reference. Visual gating can be performed in this way, waiting for matched respiratory cycles to make catheter manipulations. Patient comfort is essential and an 8 sec breath-hold is needed to avoid significant motion artifact and significant image quality degradation. If necessary, oxygen can be administered to the patient during the acquisition to minimize the discomfort of breath holding.
The limitations of the CBCT include imaging artifacts and X-ray exposure. CBCT images present artifacts due to multiple sources such as noise, scatter, partial volume effects, beam hardening, ringing, and motion. Several algorithms have been developed to reduce noise during reconstruction, modify the X-ray spectrum or to reduce motion artifacts20-26. The direct impact of these artifacts during the DEB-TACE has not been, described to the author&#39;s knowledge. CBCT X-ray exposure is generally less than MDCT of similar protocol. In cases of diffuse liver disease, embolization can be performed from a proximal location. A 3D roadmap may not be necessary in those instances. Then, MDCT or MRI preprocedural images can be used to generate a 3D roadmap for proper hepatic artery catheterization. An intraprocedural DP-CBCT post therapy can still be used to predict treatment success when drug eluding beads are used
DP-CBCT is a useful tool in interventional oncology which can be used to standardize DEB-TACE procedures. DP-CBCT provides information that improves the three major steps of TACE procedures: see, reach and treat liver tumor.

Image guidance is the backbone of interventional radiology. Two relatively recent capabilities of the X-ray angiography equipment are three-dimensional (3D) rotational angiography, and C-arm cone-beam computed tomography (CBCT). CBCT has enabled the acquisition of 3D volumetric imaging in the angiography suite with the advent of the C-arm, the flat panel detector and the Feldkamp back projection algorithm1,2. These newer image acquisition capabilities have enabled clinicians to perform procedures not feasible with traditional fluoroscopy or digital subtraction angiography alone3-7. Recent improvements in image quality allow the comparison of CBCT images being with diagnostic imaging8,9. Moreover these recent tools can improve accuracy of a growing variety of interventions5,7.
Transarterial chemoembolization (TACE) is a therapeutic option for hepatocellular carcinoma (HCC) per Barcelona Clinic Liver Cancer staging and treatment algorithm10. Intraprocedural imaging directly guides this interventional oncology procedure. The intervention planning is a key step to optimize devices needed for procedure, determination of the best view to reach the tumor(s), potentially improving drug delivery to targeted tumor(s), and theoretically reducing potential complications. Tools for image acquisition, intraprocedural guidance, and therapeutic response assessment have been developed for use during TACE, to optimize TACE. The use of dual-phase CBCT (DP-CBCT) especially during TACE with drug-eluting beads (DEB-TACE) provides more information than traditional fluoroscopy, CBCT without contrast injection, or single phase enhanced CBCT11. Indeed, DP-CBCT is two five-seconds CBCT scans (early arterial and delayed venous phases) done intraprocedurally during one single intra-arterial injection17,21-23. DP-CBCT could be described as an essential tool in the armamentarium of the interventional oncologist to standardize TACE approach on a daily basis.
Firstly, DP-CBCT imaging is highly sensitive and specific for detecting HCC. It compares favorably to the existing gold standard, contrast-enhanced magnetic resonance imaging (CE-MRI) and multiphasic-multidetector computed tomography (M-MDCT)8,9,12. Accurate detection and tumor volume segmentation can be obtained from CBCT images often the delayed venous phase scan unless better visualization is achieved on arterial phase8,13,14. Secondly. DP-CBCT can generate a roadmap for the hyperselective catheterization and identification and embolization of feeding vessels. Recent data demonstrates that hyperselective chemotherapy delivery is associated with lower complications and improved results&#160;15-17. Finally, DP-CBCT provides an intraprocedural predictive assessment of liver tumor (HCC) response after intra-arterial therapy and may augment or predict six-weeks follow-up CE-MRI18. The use of CBCT imaging during TACE has been shown to increase survival19.
The purpose of this manuscript is to describe the use of CBCT to execute the steps of DEB-TACE: seeing, reaching, and treating liver tumors. Modification of the DEB-TACE based upon DP-CBCT information is a common clinical scenario.

<table border="1">
	<tbody>
		<tr>
			<td>Name of Material/ Equipment</td>
			<td>Company</td>
			<td>Catalog Number</td>
			<td>Comments/Description</td>
		</tr>
		<tr>
			<td>Angiographic system (Allura Xper FD20)</td>
			<td>Philips Healthcare, Best, The Netherlands</td>
			<td></td>
			<td>Angiographic system made of a C-arm computed tomography (CBCT) and a flat panel detector</td>
		</tr>
		<tr>
			<td>Workstation (XtraVision 8)</td>
			<td>Philips Healthcare, Best, The Netherlands</td>
			<td></td>
			<td>Workstation for CBCT images reconstruction and postprocessing</td>
		</tr>
		<tr>
			<td>Contrast agent: Oxilan 300 (Ioxilan)</td>
			<td>Guerbet LLC, Bloomington, IN, USA</td>
			<td></td>
			<td>Contrast agent used for acquiring DP-CBCT images</td>
		</tr>
		<tr>
			<td>Sheath</td>
			<td></td>
			<td></td>
			<td>(5Fr)</td>
		</tr>
		<tr>
			<td>Catheter</td>
			<td>Terumo Medical, Somerset, NJ, USA</td>
			<td></td>
			<td>Glide Simmons 1 (5Fr)</td>
		</tr>
		<tr>
			<td>Microcatheter</td>
			<td>Boston Scientific, Natick, MA, USA</td>
			<td></td>
			<td>Renegade Hi-Flow (3Fr)</td>
		</tr>
		<tr>
			<td>Steerable guidewire</td>
			<td>Boston Scientific, Natick, MA, USA</td>
			<td></td>
			<td>Fathom wire (0.018 in)</td>
		</tr>
	</tbody>
</table>

dual-phase cone-beam computed tomography to see, reach, and treat hepatocellular carcinoma during drug-eluting beads transarterial chemo-embolization

The advent of cone-beam computed tomography (CBCT) in the angiography suite has been revolutionary in interventional radiology. CBCT offers 3 dimensional&#160;(3D) diagnostic imaging in the interventional suite and can enhance minimally-invasive therapy beyond the limitations of 2D angiography alone. The role of CBCT has been recognized in transarterial chemo-embolization (TACE) treatment of hepatocellular carcinoma (HCC). The recent introduction of a CBCT technique: dual-phase CBCT (DP-CBCT) improves intra-arterial HCC treatment with drug-eluting beads (DEB-TACE). DP-CBCT can be used to localize liver tumors with the diagnostic accuracy of multi-phasic multidetector computed tomography (M-MDCT) and contrast enhanced magnetic resonance imaging (CE-MRI) (See the tumor), to guide intra-arterially guidewire and microcatheter to the desired location for selective therapy (Reach the tumor), and to evaluate treatment success during the procedure (Treat the tumor). The purpose of this manuscript is to illustrate how DP-CBCT is used in DEB-TACE to see, reach, and treat HCC.

The use of intraprocedural C-arm CBCT images allowed acquisition of 3D volume image sets for the 3 major steps of HCC DEB-TACE treatment: see, reach, and treat HCC. CBCT images were obtained with a plat panel detector fixed on a C-arm CT (Figure 1).
We illustrated representative results by a case of a 64 year&#160;old man with a unresectable HCC of 8.9 cm located in the segment 7 of liver. First, to see the targeted tumor(s), an intraprocedural pretreatment DPCBCT was performed while the catheter was placed in the selective right hepatic artery, two CBCT scans (early arterial and delayed venous phases), were acquired after a single intra-arterial contrast injection through the microcatheter. The two scans were reconstructed on a workstation less than one minute after the CBCT scans (Figure 2). The registration and the overlay of the two CBCT scans were automatically performed unless a physician decided to manually register, overlay, and validate the two CBCT acquisitions to make them match to each other in three planes (axial, coronal, and sagittal planes) (Figure 3).
The physician defined the target tumor(s) to be treated using preprocedural diagnostic imaging (CE-MRI or M-MDCT) and correlated images to intraprocedural pre-TACE DPCBCT scans. The physician segmented in 3D the target tumor (blue colored spheres) on the venous phase CBCT phase, which best demonstrated the lesions (Figure 4). The feeding arteries (colored lines) were automatically detected and colored by the software (Figure 5).The physician controlled the automatic tumor feeding arteries detection before validating and starting the catheter navigation. Tumor segmentation and tumor feeding arteries were overlayed on real-time fluoroscopy (Figure 6). The physician controlled the automatic detection. The 3D roadmap could specifically display any opacified vessel, which isolated the tumoral vascular supply of all segmented tumor.
As soon as the 3D roadmap was overlayed on the live fluoroscopy (Figure 6), the catheterization of the targeted tumor(s) could have started. If necessary, the 3D roadmap was intraprocedurally adjusted manually in case of patient motion during the procedure. The catheterization was done using a 3D roadmap overlayed on the 2D live fluoroscopy. The operator was able to move the table and the C-arm positions for a better visualization of potential tortuous vessels with 3D roadmap synchronization.
When the microcatheter was located in an appropriate place to treat, the drug-eluding beads agents were injected until stasis was seen on 2D fluoroscopy and before any back flow detection.
After DEB-TACE embolization into the targeted tumor, another DP-CBCT was performed to assess treatment completeness. In this HCC DEB-TACE case, a contrast enhancement defect was detected in the delayed venous phase of the post-TACE DP-CBCT compared to the delayed venous phase of the pre-TACE DP-CBCT (Figure 7).
<img alt="Figure 1" fo:content-width="4in" fo:src="/files/ftp_upload/50795/50795fig1highres.jpg" src="/files/ftp_upload/50795/50795fig1.jpg" /> 
Figure 1. Angiography suite with physicians performing a TACE. The 3D roadmap on the right monitor is being used to guide catheter placement.
<img alt="Figure 2" fo:content-width="6in" fo:src="/files/ftp_upload/50795/50795fig2highres.jpg" src="/files/ftp_upload/50795/50795fig2.jpg" /> 
Figure 2. Representative axial images of two phases of one DP-CBCT obtained intraprocedurally, before the embolization. (A) represents the arterial phase and image (B) depicts the venous phase. The first phase shows opacification of the arterial tree of the liver and feeding arteries of the single hepatocellular carcinoma (white arrow) and the second phase shows liver tumor margins (white arrow).
<img alt="Figure 3" fo:content-width="5in" fo:src="/files/ftp_upload/50795/50795fig3highres.jpg" src="/files/ftp_upload/50795/50795fig3.jpg" /> 
Figure 3. The registration of the two scans can be done in the coronal, sagittal, and axial planes. The red shade represents the primary volume (early phase) and the grey scale image represents the secondary volume (delayed phase) shown in the axial plane. The portal venous phase is not yet well blended or windowed for ideal tumor visualization.
<img alt="Figure 4" fo:content-width="5in" fo:src="/files/ftp_upload/50795/50795fig4highres.jpg" src="/files/ftp_upload/50795/50795fig4.jpg" /> 
Figure 4. The delayed venous phase CBCT scans is shown on the workstation in three planes and allows for more precise 3D tumor segmentation (A). The tumor volume is represented in blue colored circle in three planes. The segmentation can be done in any of the three axes: coronal (B), sagittal (C), and axial (D).
<img alt="Figure 5" fo:content-width="5in" fo:src="/files/ftp_upload/50795/50795fig5highres.jpg" src="/files/ftp_upload/50795/50795fig5.jpg" /> 
Figure 5. The early arterial phase scan is shown in three planes: coronal (B), sagittal (C), and axial (D). The arterial tree and tumor feeding arteries are visualized on all planes. Feeding arteries may be represented by different color and be shown on all views as above. The segmented tumor is automatically overlayed on all these images. The tumor segmentation and the extracted colored vessels are represented on the first image (A).
<img alt="Figure 6" fo:content-width="5in" fo:src="/files/ftp_upload/50795/50795fig6highres.jpg" src="/files/ftp_upload/50795/50795fig6.jpg" /> 
Figure 6. After the overlay is completed on the two data sets, the 3D roadmap is superimposed on the live fluoroscopy. The gray scale background is the fluoroscopy, the red colored overlay is the arterial tree and the blue colored overlay represents the targeted liver tumor. This 3D roadmap is used to reach tumor before the drug delivery. This case shows a target tumor in segment 7 colored in blue. The catheter is in the common hepatic artery and the microcatheter in the segment 7 hepatic artery.
<img alt="Figure 7" fo:content-width="5in" fo:src="/files/ftp_upload/50795/50795fig7highres.jpg" src="/files/ftp_upload/50795/50795fig7.jpg" /> 
Figure 7. This is an illustration of a case showing the variation of tumor enhancement on DP-CBCT images before and after embolization on the first (A) and second (B) scan phase. No Lipiodol was used.

Watch this Scientific Journal Video about Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization at JoVE.

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

Dual-phase cone-beam computed tomography (DP-CBCT) is a useful intraprocedural imaging technique for transarterial chemo-embolization treatment with drug-eluting beads of hepatocellular carcinoma. DP-CBCT has been used to perform three major steps in oncologic interventional radiology: tumor localization (see), navigation and intraprocedural catheter guidance (reach), and intraprocedural evaluation of treatment success (treat).

The advent of cone-beam computed tomography (CBCT) in the angiography suite has been revolutionary in interventional radiology. CBCT offers 3 ...

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10.2K 次观看.  The Johns Hopkins Hospital. Dual-phase cone-beam computed tomography (DP-CBCT) is a useful intraprocedural imaging technique for transarterial chemo-embolization treatment with drug-eluting beads of hepatocellular carcinoma. DP-CBCT has been used to perform three major steps in oncologic interventional radiology: tumor localization (see), navigation and intraprocedural catheter guidance (reach), and intraprocedural evaluation of treatment success (treat).

视频: Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies1. However, light absorption by tissue chromophores (e.g., hemoglobin, water, lipids, melanin) typically limits optical signal propagation through thicknesses larger than a few millimeters2. Compared to other visible wavelengths, tissue absorption for red and near-infrared (near-IR) light absorption dramatically decreases and non-elastic scattering becomes the dominant light-tissue interaction mechanism. The relatively recent development of fluorescent agents that absorb and emit light in the near-IR range (600-1000 nm), has driven the development of imaging systems and light propagation models that can achieve whole body three-dimensional imaging in small animals3.
Despite great strides in this area, the ill-posed nature of diffuse fluorescence tomography remains a significant problem for the stability, contrast recovery and spatial resolution of image reconstruction techniques and the optimal approach to FMI in small animals has yet to be agreed on. The majority of research groups have invested in charge-coupled device (CCD)-based systems that provide abundant tissue-sampling but suboptimal sensitivity4-9, while our group and a few others10-13 have pursued systems based on very high sensitivity detectors, that at this time allow dense tissue sampling to be achieved only at the cost of low imaging throughput. Here we demonstrate the methodology for applying single-photon detection technology in a fluorescence tomography system to localize a cancerous brain lesion in a mouse model.
The fluorescence tomography (FT) system employed single photon counting using photomultiplier tubes (PMT) and information-rich time-domain light detection in a non-contact conformation11. This provides a simultaneous collection of transmitted excitation and emission light, and includes automatic fluorescence excitation exposure control14, laser referencing, and co-registration with a small animal computed tomography (microCT) system15. A nude mouse model was used for imaging. The animal was inoculated orthotopically with a human glioma cell line (U251) in the left cerebral hemisphere and imaged 2 weeks later. The tumor was made to fluoresce by injecting a fluorescent tracer, IRDye 800CW-EGF (LI-COR Biosciences, Lincoln, NE) targeted to epidermal growth factor receptor, a cell membrane protein known to be overexpressed in the U251 tumor line and many other cancers18. A second, untargeted fluorescent tracer, Alexa Fluor 647 (Life Technologies, Grand Island, NY) was also injected to account for non-receptor mediated effects on the uptake of the targeted tracers to provide a means of quantifying tracer binding and receptor availability/density27. A CT-guided, time-domain algorithm was used to reconstruct the location of both fluorescent tracers (i.e., the location of the tumor) in the mouse brain and their ability to localize the tumor was verified by contrast-enhanced magnetic resonance imaging.
Though demonstrated for fluorescence imaging in a glioma mouse model, the methodology presented in this video can be extended to different tumor models in various small animal models potentially up to the size of a rat17.

Diffuse fluorescence tomography offers a relatively low-cost and potentially high-throughout approach to preclinical in vivo tumor imaging. The methodology of optical data collection, calibration, and image reconstruction is presented for a computed tomography-guided non-contact time-domain system using fluorescent targeting of the tumor biomarker epidermal growth factor receptor in a mouse glioma model.

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies1. However, light ...

Osmotic Drug Delivery to Ischemic Hindlimbs and Perfusion of Vasculature with Microfil for Micro-Computed Tomography Imaging

Preclinical research in animal models of peripheral arterial disease plays a vital role in testing the efficacy of therapeutic agents designed to stimulate microcirculation. The choice of delivery method for these agents is important because the route of administration profoundly affects the bioactivity and efficacy of these agents1,2. In this article, we demonstrate how to locally administer a substance in ischemic hindlimbs by using a catheterized osmotic pump. This pump can deliver a fixed volume of aqueous solution continuously for an allotted period of time. We also present our mouse model of unilateral hindlimb ischemia induced by ligation of the common femoral artery proximal to the origin of profunda femoris and epigastrica arteries in the left hindlimb. Lastly, we describe the in vivo cannulation and ligation of the infrarenal abdominal aorta and perfusion of the hindlimb vasculature with Microfil, a silicone radiopaque casting agent. Microfil can perfuse and fill the entire vascular bed (arterial and venous), and because we have ligated the major vascular conduit for exit, the agent can be retained in the vasculature for future ex vivo imaging with the use of small specimen micro-CT3.

We show here the in vivo insertion of an osmotic pump for constant local drug delivery and the creation of hindlimb ischemia in a mouse model. Moreover, the hindlimb vasculature is perfused with Microfil, a silicone radiopaque agent, to prepare for micro-computed tomography (micro-CT) imaging.

Preclinical research in animal models of peripheral arterial disease plays a vital role in testing the efficacy of therapeutic agents designed to ...

Generation of Subcutaneous and Intrahepatic Human Hepatocellular Carcinoma Xenografts in Immunodeficient Mice

In vivo experimental models of hepatocellular carcinoma (HCC) that recapitulate the human disease provide a valuable platform for research into disease pathophysiology and for the preclinical evaluation of novel therapies. We present a variety of methods to generate subcutaneous or orthotopic human HCC xenografts in immunodeficient mice that could be utilized in a variety of research applications. With a focus on the use of primary tumor tissue from patients undergoing surgical resection as a starting point, we describe the preparation of cell suspensions or tumor fragments for xenografting. We describe specific techniques to xenograft these tissues i) subcutaneously; or ii) intrahepatically, either by direct implantation of tumor cells or fragments into the liver, or indirectly by injection of cells into the mouse spleen. We also describe the use of partial resection of the native mouse liver at the time of xenografting as a strategy to induce a state of active liver regeneration in the recipient mouse that may facilitate the intrahepatic engraftment of primary human tumor cells. The expected results of these techniques are illustrated. The protocols described have been validated using primary human HCC samples and xenografts, which typically perform less robustly than the well-established human HCC cell lines that are widely used and frequently cited in the literature. In comparison with cell lines, we discuss factors which may contribute to the relatively low chance of primary HCC engraftment in xenotransplantation models and comment on technical issues that may influence the kinetics of xenograft growth. We also suggest methods that should be applied to ensure that xenografts obtained accurately resemble parent HCC tissues.

Human tumor xenografts in immunodeficient mice are valuable tools to study cancer biology. Specific protocols to generate subcutaneous and intrahepatic xenografts from human hepatocellular carcinoma cells or tumor fragments are described. Liver regeneration induced by partial hepatectomy in recipient mice is presented as a strategy to facilitate intrahepatic engraftment.

In  vivo experimental models of hepatocellular carcinoma (HCC) that recapitulate  the human disease provide a valuable platform for research into disease  ...

The In Ovo Chick Chorioallantoic Membrane (CAM) Assay as an Efficient Xenograft Model of Hepatocellular Carcinoma

The chick chorioallantoic membrane (CAM) begins to develop by day 7 after fertilization and matures by day 12. The CAM is naturally immunodeficient and highly vascularized, making it an ideal system for tumor implantation. Furthermore, the CAM contains extracellular matrix proteins such as fibronectin, laminin, collagen, integrin alpha(v)beta3, and MMP-2, making it an attractive model to study tumor invasion and metastasis. Scientists have long taken advantage of the physiology of the CAM by using it as a model of angiogenesis. More recently, the CAM assay has been modified to work as an in vivo xenograft model system for various cancers that bridges the gap between basic in vitro work and more complex animal cancer models. The CAM assay allows for the study of tumor growth, anti-tumor therapies, and pro-tumor molecular pathways in a biologically relevant system that is both cost- and time-effective. Here, we describe the development of CAM xenograft model of hepatocellular carcinoma (HCC) with embryonic survival rates of up to 93% and reliable tumor take leading to growth of three-dimensional, vascularized tumors.

The In Ovo Chick Chorioallantoic Membrane CAM Assay as an Efficient Xenograft Model of Hepatocellular Carcinoma

The chick chorioallantoic membrane (CAM) is immunodeficient and highly vascularized, making it a natural in vivo model of tumor growth and angiogenesis. In this protocol, we describe a reliable method of growing three-dimensional, vascularized hepatocellular carcinoma (HCC) tumors using the CAM assay.

The chick chorioallantoic membrane (CAM) begins to develop by day 7 after fertilization and matures by day 12. The CAM is naturally immunodeficient and ...

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Reliably differentiating brown adipose tissue (BAT) from other tissues using a non-invasive imaging method is an important step toward studying BAT in humans. Detecting BAT is typically confirmed by the uptake of the injected radioactive tracer 18F-Fluorodeoxyglucose (18F-FDG) into adipose tissue depots, as measured by positron emission tomography/computed tomography (PET-CT) scans after exposing the subject to cold stimulus. Fat-water separated magnetic resonance imaging (MRI) has the ability to distinguish BAT without the use of a radioactive tracer. To date, MRI of BAT in adult humans has not been co-registered with cold-activated PET-CT. Therefore, this protocol uses 18F-FDG PET-CT scans to automatically generate a BAT mask, which is then applied to co-registered MRI scans of the same subject. This approach enables measurement of quantitative MRI properties of BAT without manual segmentation. BAT masks are created from two PET-CT scans: after exposure for 2 hr to either thermoneutral (TN) (24 &#176;C) or cold-activated (CA) (17 &#176;C) conditions. The TN and CA PET-CT scans are registered, and the PET standardized uptake and CT Hounsfield values are used to create a mask containing only BAT. CA and TN MRI scans are also acquired on the same subject and registered to the PET-CT scans in order to establish quantitative MRI properties within the automatically defined BAT mask. An advantage of this approach is that the segmentation is completely automated and is based on widely accepted methods for identification of activated BAT (PET-CT). The quantitative MRI properties of BAT established using this protocol can serve as the basis for an MRI-only BAT examination that avoids the radiation associated with PET-CT.

The method presented here uses 18F-Fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET-CT) and fat-water separated magnetic resonance imaging (MRI), each scanned following 2 hr exposure to thermoneutral (24 &#176;C) and cold conditions (17 &#176;C) in order to map brown adipose tissue (BAT) in adult human subjects.

Reliably differentiating brown adipose tissue (BAT) from other tissues using a non-invasive imaging method is an important step toward studying BAT in ...

A "Patient-Like" Orthotopic Syngeneic Mouse Model of Hepatocellular Carcinoma Metastasis

The majority of cancer-related deaths are caused by the metastasis of the cancer rather than the primary tumor itself. Yet, the underlying mechanisms of cancer metastasis are still unclear. Animal models are essential for elucidating the mechanisms and for evaluating novel strategies for the treatment of metastatic cancers. Here, an in-depth description of a &#8220;patient-like&#8221; orthotopic syngeneic mouse model for exploring the mechanisms of metastasis of solid organ tumors is provided. The survival surgical implantation of BNL 1ME A.7R.1 mouse hepatocellular carcinoma cells directly into the liver (the organ of origin) of the inbred wild-type immune competent laboratory mouse strain, BALB/c is described. The success and reproducibility of this methodology recommends it for widespread use in elucidating the biological mechanisms of solid organ cancer metastasis.

A &quot;Patient-Like&quot; Orthotopic Syngeneic Mouse Model of Hepatocellular Carcinoma Metastasis

The metastatic spread of cancer is the major cause of cancer-related deaths. We provide an in-depth description of our survival surgery methodology for establishing a &#8220;patient-like&#8221; orthotopic syngeneic mouse model system for studying the mechanisms of metastasis in solid organ tumors.

The majority of cancer-related deaths are caused by the metastasis of the cancer rather than the primary tumor itself. Yet, the underlying mechanisms of ...

Cone Beam Intraoperative Computed Tomography-based Image Guidance for Minimally Invasive Transforaminal Interbody Fusion

Transforaminal lumbar interbody fusion (TLIF) is commonly used for the treatment of spinal stenosis, degenerative disc disease, and spondylolisthesis. Minimally invasive surgery (MIS) approaches have been applied to this technique with an associated decrease in estimated blood loss (EBL), length of hospital stay, and infection rates, while preserving outcomes with traditional open surgery. Previous MIS TLIF techniques involve significant fluoroscopy that subjects the patient, surgeon, and operating room staff to non-trivial levels of radiation exposure, particularly for complex multi-level procedures. We present a technique that utilizes an intraoperative computed tomography (CT) scan to aid in placement of pedicle screws, followed by traditional fluoroscopy for confirmation of cage placement. Patients are positioned in the standard fashion and a reference arc is placed in the posterior superior iliac spine (PSIS) followed by intraoperative CT scan. This allows for image-guidance-based placement of pedicle screws through a one-inch skin incision on each side. Unlike traditional MIS-TLIF that requires significant fluoroscopic imaging during this stage, the operation can now be performed without any additional radiation exposure to the patient or operating room staff. After completion of the facetectomy and discectomy, final TLIF cage placement is confirmed with fluoroscopy. This technique has the potential to decrease operative time and minimize total radiation exposure.

The purpose of this article is to provide image-guidance for minimally invasive transforaminal interbody fusion.

Transforaminal lumbar interbody fusion (TLIF) is commonly used for the treatment of spinal stenosis, degenerative disc disease, and spondylolisthesis. ...

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans

Coronary artery calcification (CAC) provides an objective measure of coronary artery disease and can readily be identified on non-gated computed tomography (CT) scans with a high correlation with gated cardiac CT scans. This standardized protocol takes a step-wise approach to not only optimizing an image for the identification of calcification but also to distinguishing CAC from other common causes of calcification in the cardiac silhouette. Recognition of CAC on non-gated CT scans helps to identify a very powerful prognostic factor that can influence therapeutic interventions or downstream diagnostic testing without requiring a gated cardiac scan. These non-gated CT scans are often acquired as part of the routine care of the patient, and this data is readily available without another dose of&#160;ionizing radiation. This protocol allows for the precise and accurate extraction of this data for the purposes of retrospective data analysis in clinical research studies, but also in the clinical evaluation and management of patients.

Here, we present a protocol to reliably and systematically identify coronary artery calcification (CAC) on non-gated computed tomography (CT) scans of the chest or abdomen. CAC provides an objective measure of coronary artery disease for both research and clinical purposes.

Coronary artery calcification (CAC) provides an objective measure of coronary artery disease and can readily be identified on non-gated computed ...

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Intra-arterial therapies are the standard of care for patients with hepatocellular carcinoma who cannot undergo surgical resection. The objective of this study was to develop a method to predict response to intra-arterial treatment prior to intervention.
The method provides a general framework for predicting outcomes prior to intra-arterial therapy. It involves pooling clinical, demographic and imaging data across a cohort of patients and using these data to train a machine learning model. The trained model is applied to new patients in order to predict their likelihood of response to intra-arterial therapy.
The method entails the acquisition and parsing of clinical, demographic and imaging data from N patients who have already undergone trans-arterial therapies. These data are parsed into discrete features (age, sex, cirrhosis, degree of tumor enhancement, etc.) and binarized into true/false values (e.g., age over 60, male gender, tumor enhancement beyond a set threshold, etc.). Low-variance features and features with low univariate associations with the outcome are removed. Each treated patient is labeled according to whether they responded or did not respond to treatment. Each training patient is thus represented by a set of binary features and an outcome label. Machine learning models are trained using N - 1 patients with testing on the left-out patient. This process is repeated for each of the N patients. The N models are averaged to arrive at a final model.
The technique is extensible and enables inclusion of additional features in the future. It is also a generalizable process that may be applied to clinical research questions outside of interventional radiology. The main limitation is the need to derive features manually from each patient. A popular modern form of machine learning called deep learning does not suffer from this limitation, but requires larger datasets.

Intra-arterial therapies are the standard of care for patients with hepatocellular carcinoma who cannot undergo surgical resection. A method for predicting response to these therapies is proposed. The technique uses pre-procedural clinical, demographic, and imaging information to train machine learning models capable of predicting response prior to treatment.

Intra-arterial therapies are the standard of care for patients with hepatocellular carcinoma who cannot undergo surgical resection. The objective of this ...

Four-Dimensional Computed Tomography-Guided Valve Sizing for Transcatheter Pulmonary Valve Replacement

The measurements of the right ventricle (RV) and pulmonary artery (PA), for selecting the optimal prosthesis size for transcatheter pulmonary valve replacement (TPVR), vary considerably. Three-dimensional (3D) computed tomography (CT) imaging for device size prediction is insufficient to assess the displacement of the right ventricular outflow tract (RVOT) and PA, which could increase the risk of stent misplacement and paravalvular leak. The aim of this study is to provide a dynamic model to visualize and quantify the anatomy of the RVOT to PA over the entire cardiac cycle by four-dimensional (4D) cardiac CT reconstruction to obtain an accurate quantitative evaluation of the required valve size. In this pilot study, cardiac CT from sheep J was chosen to illustrate the procedures. 3D cardiac CT was imported into 3D reconstruction software to build a 4D sequence which was divided into eleven frames over the cardiac cycle to visualize the deformation of the heart. Diameter, cross-sectional area, and circumference of five imaging planes at the main PA, sinotubular junction, sinus, basal plane of the pulmonary valve (BPV), and RVOT were measured at each frame in 4D straightened models prior to valve implantation to predict the valve size. Meanwhile, dynamic changes in the RV volume were also measured to evaluate right ventricular ejection fraction (RVEF). 3D measurements at the end of the diastole were obtained for comparison with the 4D measurements. In sheep J, 4D CT measurements from the straightened model resulted in the same choice of valve size for TPVR (30 mm) as 3D measurements. The RVEF of sheep J from pre-CT was 62.1 %. In contrast with 3D CT, the straightened 4D reconstruction model not only enabled accurate prediction for valve size selection for TPVR but also provided an ideal virtual reality, thus presenting a promising method for TPVR and the innovation of TPVR devices.

This study assessed a new methodology with a straightened model generated from the four-dimensional cardiac computed tomography sequence to obtain the desired measurements for valve sizing in the application of transcatheter pulmonary valve replacement.

The measurements of the right ventricle (RV) and pulmonary artery (PA), for selecting the optimal prosthesis size for transcatheter pulmonary valve ...