Feasibility of Automated Volumetric Assessment of Large Hepatocellular Carcinomas' Responses to Transarterial Chemoembolization.

Background: Hepatocellular carcinoma (HCC) is the most common liver malignancy and the leading cause of death in patients with cirrhosis. Various treatments for HCC are available, including transarterial chemoembolization (TACE), which is the commonest intervention performed in HCC. Radiologic tumor response following TACE is an important prognostic factor for patients with HCC. We hypothesized that, for large HCC tumors, assessment of treatment response made with automated volumetric response evaluation criteria in solid tumors (RECIST) might correlate with the assessment made with the more time- and labor-intensive unidimensional modified RECIST (mRECIST) and manual volumetric RECIST (M-vRECIST) criteria. Accordingly, we undertook this retrospective study to compare automated volumetric RECIST (A-vRECIST) with M-vRECIST and mRESIST for the assessment of large HCC tumors' responses to TACE. Methods:We selected 42 pairs of contrast-enhanced computed tomography (CT) images of large HCCs. Images were taken before and after TACE, and in each of the images, the HCC was segmented using both a manual contouring tool and a convolutional neural network. Three experienced radiologists assessed tumor response to TACE using mRECIST criteria. The intra-class correlation coefficient was used to assess inter-reader reliability in the mRECIST measurements, while the Pearson correlation coefficient was used to assess correlation between the volumetric and mRECIST measurements. Results:Volumetric tumor assessment using automated and manual segmentation tools showed good correlation with mRECIST measurements. For A-vRECIST and M-vRECIST, respectively, r = 0.597 vs. 0.622 in the baseline studies; 0.648 vs. 0.748 in the follow-up studies; and 0.774 vs. 0.766 in the response assessment (P < 0.001 for all). The A-vRECIST evaluation showed high correlation with the M-vRECIST evaluation (r = 0.967, 0.937, and 0.826 in baseline studies, follow-up studies, and response assessment, respectively, P < 0.001 for all). Conclusion:Volumetric RECIST measurements are likely to provide an early marker for TACE monitoring, and automated measurements made with a convolutional neural network may be good substitutes for manual volumetric measurements.

Automated Volumetric Assessment of Hepatocellular Carcinoma Response to Sorafenib: A Pilot Study.

PURPOSE: This pilot study evaluates the feasibility of automated volumetric quantification of hepatocellular carcinoma (HCC) as an imaging biomarker to assess treatment response for sorafenib. METHODS: In this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study, a training database of manually labeled background liver, enhancing and nonenhancing tumor tissue was established using pretherapy and first posttherapy multiphasic computed tomography images from a registry of 13 HCC patients. For each patient, Hounsfield density and geometry-based feature images were generated from registered multiphasic computed tomography data sets and used as the input for a random forest-based classifier of enhancing and nonenhancing tumor tissue. Leave-one-out cross-validation of the dice similarity measure was applied to quantify the classifier accuracy. A Cox regression model was used to confirm volume changes as predictors of time to progression (TTP) of target lesions for both manual and automatic methods. RESULTS: When compared with manual labels, an overall classification accuracy of dice similarity coefficient of 0.71 for pretherapy and 0.66 posttherapy enhancing tumor labels and 0.45 for pretherapy and 0.59 for posttherapy nonenhancing tumor labels was observed. Automated methods for quantifying volumetric changes in the enhancing lesion agreed with manual methods and were observed as a significant predictor of TTP. CONCLUSIONS: Automated volumetric analysis was determined to be feasible for monitoring HCC response to treatment. The information extracted using automated volumetrics is likely to reproduce labor-intensive manual data and provide a good predictor for TTP. Further work will extend these studies to additional treatment modalities and larger patient populations.

Evaluation of Magnetic Resonance (MR) Biomarkers for Assessment of Response With Response Evaluation Criteria in Solid Tumors: Comparison of the Measurements of Neuroendocrine Tumor Liver Metastases (NETLM) With Various MR Sequences and at Multiple Phases of Contrast Administration.

PURPOSE: Our aim was to compare the interobserver and intraobserver variability for the measurement of the size of liver metastases in patients with carcinoid tumors with various magnetic resonance (MR) series. MATERIALS AND METHODS: In this retrospective institutional review board-approved study, 30 patients with liver metastases from a carcinoid primary had a complete MR examination of the abdomen at 1.5 T with gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA). The complete MR examination included T1 (in-phase [IP]/out-of-phase [OOP], T2, diffusion-weighted imaging, pre-Gd-EOB-DTPA and post-Gd-EOB-DTPA 3D gradient echo (4 phases plus 20-minute hepatobiliary phase [HBP] Gd]). Four readers reviewed each series independently. The measurement for each lesion was compared to HBP-Gd images. The sensitivity for detection of each lesion was compared to HBP-Gd. Variance component analysis was used to estimate variance due to patient, lesion within patient, and reader by sequence. Linear mixed model was used to compare lesion size between sequences. RESULTS: The HBP-Gd had the smallest interreader variability. There was no significant difference between series with respect to interreader variability. Lesion sizes measured in diffusion-weighted imaging was significantly higher. T2-weighted imaging was the closest to HBP-Gd. Lesion sizes measured with the other sequences were significantly smaller. There was significant difference in sensitivity of lesion detection of some series when compared to HBP-Gd. CONCLUSION: The HBP-Gd series had the smallest interreader variability and is the recommended series to measure lesion size for evaluation of response to treatment.

Update on 3D and multiplanar MDCT in the assessment of biliary and pancreatic pathology.

The development of multidetector row computed tomography (MDCT) has led to the acquisition of true isotropic voxels that can be postprocessed to yield images in any plane of the same resolution as the original axially acquired images. This, coupled with rapid MDCT imaging during peak target organ enhancement has led to a variety of means to review imaging information beyond that of the axial perspective. Postprocessing can be utilized to identify variant biliary anatomy to guide preoperative planning of biliary-related surgery, determine the level and cause of biliary obstruction and assist in staging of biliary cancer. Postprocessing can also be used to identify pancreatic ductal variants, visualize diagnostic features of pancreatic cystic lesions, diagnose and stage pancreatic cancer, and differentiate pancreatic from peripancreatic disease.