Clinicogenomic predictors of outcomes in patients with hepatocellular carcinoma treated with immunotherapy.

INTRODUCTION: Immune checkpoint inhibitor (ICI) combinations extend overall survival (OS) while anti-PD-1/L1 monotherapy is non-inferior to sorafenib in treatment-naïve, patients with advanced hepatocellular carcinoma (HCC). Clinicogenomic features are posited to influence patient outcomes. METHODS: The primary objective of this retrospective study was to define the clinical, pathologic, and genomic factors associated with outcomes to ICI therapy in patients with HCC. Patients with histologically confirmed advanced HCC treated with ICI at Memorial Sloan Kettering Cancer Center from 2012 to 2022 were included. Association between clinical, pathological, and genomic characteristics were assessed with univariable and multivariable Cox regression model for progression-free survival (PFS) and OS. RESULTS: Two-hundred and forty-two patients were treated with ICI-based therapy. Patients were predominantly male (82%) with virally mediated HCC (53%) and Child Pugh A score (70%). Median follow-up was 28 months (0.5-78.4). Median PFS for those treated in 1st line, 2nd line and ≥ 3rd line was 4.9 (range: 2.9-6.2), 3.1 (2.3-4.0), and 2.5 (2.1-4.0) months, respectively. Median OS for those treated in 1st line, 2nd line, and ≥ 3rd line was 16 (11-22), 7.5 (6.4-11), and 6.4 (4.6-26) months, respectively. Poor liver function and performance status associated with worse PFS and OS, while viral hepatitis C was associated with favorable outcome. Genetic alterations were not associated with outcomes. CONCLUSION: Clinicopathologic factors were the major determinates of outcomes for patients with advanced HCC treated with ICI. Molecular profiling did not aid in stratification of ICI outcomes. Future studies should explore alternative biomarkers such as the level of immune activation or the pretreatment composition of the immune tumor microenvironment.

MRI imaging features for predicting macrotrabecular-massive subtype hepatocellular carcinoma: a systematic review and meta-analysis.

PURPOSE: To identify significant MRI features associated with macrotrabecular-massive hepatocellular carcinoma (MTM-HCC), and to assess the distribution of Liver Imaging Radiology and Data System (LI-RADS, LR) category assignments. METHODS: PubMed and EMBASE were searched up to March 28, 2023. Random-effects model was constructed to calculate pooled diagnostic odds ratios (DORs) and 95% confidence intervals (CIs) for each MRI feature for differentiating MTM-HCC from NMTM-HCC. The pooled proportions of LI-RADS category assignments in MTM-HCC and NMTM-HCC were compared using z-test. RESULTS: Ten studies included 1978 patients with 2031 HCCs (426 (20.9%) MTM-HCC and 1605 (79.1%) NMTM-HCC). Six MRI features showed significant association with MTM-HCC: tumor in vein (TIV) (DOR = 2.4 [95% CI, 1.6-3.5]), rim arterial phase hyperenhancement (DOR =2.6 [95% CI, 1.4-5.0]), corona enhancement (DOR = 2.6 [95% CI, 1.4-4.5]), intratumoral arteries (DOR = 2.6 [95% CI, 1.1-6.3]), peritumoral hypointensity on hepatobiliary phase (DOR = 2.2 [95% CI, 1.5-3.3]), and necrosis (DOR = 4.2 [95% CI, 2.0-8.5]). The pooled proportions of LI-RADS categories in MTM-HCC were LR-3, 0% [95% CI, 0-2%]; LR-4, 11% [95% CI, 6-16%]; LR-5, 63% [95% CI, 55-71%]; LR-M, 12% [95% CI, 6-19%]; and LR-TIV, 13% [95% CI, 6-22%]. In NMTM-HCC, the pooled proportions of LI-RADS categories were LR-3, 1% [95% CI, 0-2%]; LR-4, 8% [95% CI, 3-15%]; LR-5, 77% [95% CI, 71-82%]; LR-M, 5% [95% CI, 3-7%]; and LR-TIV, 6% [95% CI, 2-11%]. MTM-HCC had significantly lower proportion of LR-5 and higher proportion of LR-M and LR-TIV categories. CONCLUSIONS: Six MRI features showed significant association with MTM-HCC. Additionally, compared to NMTM-HCC, MTM-HCC are more likely to be categorized LR-M and LR-TIV and less likely to be categorized LR-5. CLINICAL RELEVANCE STATEMENT: Several MR imaging features can suggest macrotrabecular-massive hepatocellular carcinoma subtype, which can assist in guiding treatment plans and identifying potential candidates for clinical trials of new treatment strategies. KEY POINTS: • Macrotrabecular-massive hepatocellular carcinoma is a subtype of HCC characterized by its aggressive nature and unfavorable prognosis. • Tumor in vein, rim arterial phase hyperenhancement, corona enhancement, intratumoral arteries, peritumoral hypointensity on hepatobiliary phase, and necrosis on MRI are indicative of macrotrabecular-massive hepatocellular carcinoma. • Various MRI characteristics can be utilized for the diagnosis of the macrotrabecular-massive hepatocellular carcinoma subtype. This can prove beneficial in guiding treatment decisions and identifying potential candidates for clinical trials involving novel treatment approaches.

LI-RADS: Looking Back, Looking Forward.

Since its initial release in 2011, the Liver Imaging Reporting and Data System (LI-RADS) has evolved and expanded in scope. It started as a single algorithm for hepatocellular carcinoma (HCC) diagnosis with CT or MRI with extracellular contrast agents and has grown into a multialgorithm network covering all major liver imaging modalities and contexts of use. Furthermore, it has developed its own lexicon, report templates, and supplementary materials. This article highlights the major achievements of LI-RADS in the past 11 years, including adoption in clinical care and research across the globe, and complete unification of HCC diagnostic systems in the United States. Additionally, the authors discuss current gaps in knowledge, which include challenges in surveillance, diagnostic population definition, perceived complexity, limited sensitivity of LR-5 (definite HCC) category, management implications of indeterminate observations, challenges in reporting, and treatment response assessment following radiation-based therapies and systemic treatments. Finally, the authors discuss future directions, which will focus on mitigating the current challenges and incorporating advanced technologies. Tha authors envision that LI-RADS will ultimately transform into a probability-based system for diagnosis and prognostication of liver cancers that will integrate patient characteristics and quantitative imaging features, while accounting for imaging modality and contrast agent.

Hepatic Adenoma Subtypes on Hepatobiliary Phase of Gadoxetic Acid-Enhanced MRI: Systematic Review and Meta-Analysis.

BACKGROUND. Accumulating evidence indicates that hepatocellular adenoma (HCA) may have a higher frequency of hepatobiliary phase (HBP) iso- or hyperintensity than previously reported. OBJECTIVE. The purpose of this study was to evaluate the proportion of HCA that shows iso- or hyperintensity in the HBP of gadoxetic acid-enhanced MRI, stratified by HCA subtype (HNF1a-inactivated [H-HCA], inflammatory [I-HCA], ß-catenin-activated [B-HCA], and unclassified [U-HCA] HCA), and to assess the diagnostic performance of HBP iso- or hyperintensity for differentiating focal nodular hyperplasia (FNH) from HCA. EVIDENCE ACQUISITION. PubMed, Embase, and Cochrane Central Register of Controlled Trials were searched through February 14, 2022, for articles reporting HBP signal intensity on gadoxetic acid-enhanced MRI among pathologically proven HCAs, stratified by subtype. The pooled proportion of HBP iso- or hyperintensity was determined for each subtype and compared using metaregression. Diagnostic performance of HBP iso- or hyperintensity for differentiating FNH from all HCA subtypes combined and from B-HCA and U-HCA combined was assessed using bivariate modeling. EVIDENCE SYNTHESIS. Twenty-eight studies (12 original investigations, 16 case reports or case series) were included, yielding 364 patients with 410 HCAs (112 H-HCAs, 203 I-HCAs, 33 B-HCAs, 62 U-HCAs). Pooled proportion of HBP iso- or hyperintensity was 14% (95% CI, 4-26%) among all HCAs, 0% (95% CI, 0-2%) among H-HCAs, 11% (95% CI, 0-29%) among U-HCAs, 14% (95% CI, 2-31%) among I-HCAs, and 59% (95% CI, 26-88%) among B-HCAs; metaregression showed significant difference among subtypes (p < .001). In four studies reporting diagnostic performance information, HBP iso- or hyperintensity had sensitivity of 99% (95% CI, 57-100%) and specificity of 89% (95% CI, 82-94%) for differentiating FNH from all HCA subtypes and sensitivity of 99% (95% CI, 53-100%) and specificity of 65% (95% CI, 44-80%) for differentiating FNH from B-HCA or U-HCA. CONCLUSION. HCA subtypes other than H-HCA show proportions of HBP iso- or hyperintensity ranging from 11% (U-HCA) to 59% (B-HCA). Low prevalence of B-HCA has contributed to prior reports of high diagnostic performance of HBP iso- or hyperintensity for differentiating FNH from HCA. CLINICAL IMPACT. Radiologists should recognize the low specificity of HBP iso- or hyperintensity on gadoxetic acid-enhanced MRI for differentiating FNH from certain HCA subtypes.

Recurrence After Resection of Pancreatic Cancer: Can Radiomics Predict Patients at Greatest Risk of Liver Metastasis?

BACKGROUND: Liver metastasis (LM) after pancreatic ductal adenocarcinoma (PDAC) resection is common but difficult to predict and has grave prognosis. We combined preoperative clinicopathological variables and quantitative analysis of computed tomography (CT) imaging to predict early LM. METHODS: We retrospectively evaluated patients with PDAC submitted to resection between 2005 and 2014 and identified clinicopathological variables associated with early LM. We performed liver radiomic analysis on preoperative contrast-enhanced CT scans and developed a logistic regression classifier to predict early LM (< 6 months). RESULTS: In 688 resected PDAC patients, there were 516 recurrences (75%). The cumulative incidence of LM at 5 years was 41%, and patients who developed LM first (n = 194) had the lowest 1-year overall survival (OS) (34%), compared with 322 patients who developed extrahepatic recurrence first (61%). Independent predictors of time to LM included poor tumor differentiation (hazard ratio (HR) = 2.30; P < 0.001), large tumor size (HR = 1.17 per 2-cm increase; P = 0.048), lymphovascular invasion (HR = 1.50; P = 0.015), and liver Fibrosis-4 score (HR = 0.89 per 1-unit increase; P = 0.029) on multivariate analysis. A model using radiomic variables that reflect hepatic parenchymal heterogeneity identified patients at risk for early LM with an area under the receiver operating characteristic curve (AUC) of 0.71; the performance of the model was improved by incorporating preoperative clinicopathological variables (tumor size and differentiation status; AUC = 0.74, negative predictive value (NPV) = 0.86). CONCLUSIONS: We confirm the adverse survival impact of early LM after resection of PDAC. We further show that a model using radiomic data from preoperative imaging combined with tumor-related variables has great potential for identifying patients at high risk for LM and may help guide treatment selection.

Liver imaging: it is time to adopt standardized terminology.

Liver imaging plays a vital role in the management of patients at risk for hepatocellular carcinoma (HCC); however, progress in the field is challenged by nonuniform and inconsistent terminology in the published literature. The Steering Committee of the American College of Radiology (ACR)'s Liver Imaging Reporting And Data System (LI-RADS), in conjunction with the LI-RADS Lexicon Writing Group and the LI-RADS International Working Group, present this consensus document to establish a single universal liver imaging lexicon. The lexicon is intended for use in research, education, and clinical care of patients at risk for HCC (i.e., the LI-RADS population) and in the general population (i.e., even when LI-RADS algorithms are not applicable). We anticipate that the universal adoption of this lexicon will provide research, educational, and clinical benefits. KEY POINTS: •To standardize terminology, we encourage authors of research and educational materials on liver imaging to use the standardized LI-RADS Lexicon. •We encourage reviewers to promote the use of the standardized LI-RADS Lexicon for publications on liver imaging. •We encourage radiologists to use the standardized LI-RADS Lexicon for liver imaging in clinical care.

Immunofluorescence Assay of Ablated Colorectal Liver Metastases: The Frozen Section of Image-Guided Tumor Ablation?

PURPOSE: To validate an immunofluorescence assay (IFA) detecting residual viable tumor (VT) as intraprocedural thermal ablation (TA) zone assessment and demonstrate its prognostic value for local tumor progression (LTP) after colorectal liver metastasis (CLM) TA. MATERIALS AND METHODS: This prospective study, approved by the institutional review board, included 99 patients with 155 CLMs ablated between November 2009 and January 2019. Tissue samples from the ablation zone (AZ) center and minimal margin underwent immunofluorescent microscopic examination interrogating cellular morphology and mitochondrial viability (IFA) within 30 minutes after ablation. The same tissue samples were subsequently evaluated with standard morphologic and immunohistochemical methods. The sensitivity, specificity, and overall accuracy of IFA versus standard morphologic and immunohistochemical examination were calculated. The LTP-free survival rates were evaluated for the 12-month follow-up period. RESULTS: Of the 311 tissue samples stained, 304 (98%) were deemed evaluable. Of these specimens, 27% (81/304) were considered positive for the presence of VT. The accuracy of IFA was 94% (286/304). The sensitivity and specificity were 100% (63/63) and 93% (223/241), respectively. The 18 false-positive IFA assessments corresponded to samples that included viable cholangiocytes. The 12-month LTP-free survival was 59% versus 78% for IFA positive versus negative for VT AZs, respectively (P < .001). There was no difference in LTP between margin positive only and central AZ-positive tumors (25% vs 31%, P = 1). CONCLUSIONS: The IFA assessment of the AZ can be completed intraprocedurally and serve as a valid real-time biomarker of complete tumor eradication or detect residual VT after TA. This method could improve tumor control by TA.

Machine learning radiomics can predict early liver recurrence after resection of intrahepatic cholangiocarcinoma.

BACKGROUND: Most patients recur after resection of intrahepatic cholangiocarcinoma (IHC). We studied whether machine-learning incorporating radiomics and tumor size could predict intrahepatic recurrence within 1-year. METHODS: This was a retrospective analysis of patients with IHC resected between 2000 and 2017 who had evaluable computed tomography imaging. Texture features (TFs) were extracted from the liver, tumor, and future liver remnant (FLR). Random forest classification using training (70.3%) and validation cohorts (29.7%) was used to design a predictive model. RESULTS: 138 patients were included for analysis. Patients with early recurrence had a larger tumor size (7.25 cm [IQR 5.2-8.9] vs. 5.3 cm [IQR 4.0-7.2], P = 0.011) and a higher rate of lymph node metastasis (28.6% vs. 11.6%, P = 0.041), but were not more likely to have multifocal disease (21.4% vs. 17.4%, P = 0.643). Three TFs from the tumor, FD1, FD30, and IH4 and one from the FLR, ACM15, were identified by feature selection. Incorporation of TFs and tumor size achieved the highest AUC of 0.84 (95% CI 0.73-0.95) in predicting recurrence in the validation cohort. CONCLUSION: This study demonstrates that radiomics and machine-learning can reliably predict patients at risk for early intrahepatic recurrence with good discrimination accuracy.

Patterns of Metastatic Disease in Patients with Cancer Derived from Natural Language Processing of Structured CT Radiology Reports over a 10-year Period.

Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatment planning but have historically been documented by means of autopsy series. Purpose To show the feasibility of using natural language processing (NLP) to gather accurate data from radiology reports for assessing spatial and temporal patterns of metastatic spread in a large patient cohort. Materials and Methods In this retrospective longitudinal study, consecutive patients who underwent CT from July 2009 to April 2019 and whose CT reports followed a departmental structured template were included. Three radiologists manually curated a sample of 2219 reports for the presence or absence of metastases across 13 organs; these manually curated reports were used to develop three NLP models with an 80%-20% split for training and test sets. A separate random sample of 448 manually curated reports was used for validation. Model performance was measured by accuracy, precision, and recall for each organ. The best-performing NLP model was used to generate a final database of metastatic disease across all patients. For each cancer type, statistical descriptive reports were provided by analyzing the frequencies of metastatic disease at the report and patient levels. Results In 91 665 patients (mean age ± standard deviation, 61 years ± 15; 46 939 women), 387 359 reports were labeled. The best-performing NLP model achieved accuracies from 90% to 99% across all organs. Metastases were most frequently reported in abdominopelvic (23.6% of all reports) and thoracic (17.6%) nodes, followed by lungs (14.7%), liver (13.7%), and bones (9.9%). Metastatic disease tropism is distinct among common cancers, with the most common first site being bones in prostate and breast cancers and liver among pancreatic and colorectal cancers. Conclusion Natural language processing may be applied to cancer patients' CT reports to generate a large database of metastatic phenotypes. Such a database could be combined with genomic studies and used to explore prognostic imaging phenotypes with relevance to treatment planning. © RSNA, 2021 Online supplemental material is available for this article.

Differences in Liver Parenchyma are Measurable with CT Radiomics at Initial Colon Resection in Patients that Develop Hepatic Metastases from Stage II/III Colon Cancer.

BACKGROUND: Currently, there are no methods to identify patients with an increased risk of liver metastases to guide patient selection for liver-directed therapies. We tried to determine whether quantitative image features (radiomics) of the liver obtained from preoperative staging CT scans at the time of initial colon resection differ in patients that subsequently develop liver metastases, extrahepatic metastases, or demonstrate prolonged disease-free survival. METHODS: Patients who underwent resection of stage II/III colon cancer from 2004 to 2012 with available preoperative CT scans were included in this single-institution, retrospective case-control study. Patients were grouped by initial recurrence patterns: liver recurrence, extrahepatic recurrence, or no evidence of disease at 5 years. Radiomic features of the liver parenchyma extracted from CT images were compared across groups. RESULTS: The cohort consisted of 120 patients divided evenly between three recurrence groups, with an equal number of stage II and III patients in each group. After adjusting for multiple comparisons, 44 of 254 (17%) imaging features displayed different distributions across the three patient groups (p < 0.05), with the clearest distinction between those with liver recurrence and no evidence of disease. Increased heterogeneity in the liver parenchyma by radiomic analysis was protective of liver metastases. CONCLUSIONS: CT radiomics is a promising tool to identify patients at high risk of developing liver metastases and is worthy of further investigation and validation.

MRI of the Pancreas.

MRI has played a critical role in the evaluation of patients with pancreatic pathologies, from screening of patients at high risk for pancreatic cancer to the evaluation of pancreatic cysts and indeterminate pancreatic lesions. The high mortality associated with pancreatic adenocarcinomas has spurred much interest in developing effective screening tools, with MRI using magnetic resonance cholangiopancreatography (MRCP) playing a central role in the hopes of identifying cancers at earlier stages amenable to curative resection. Ongoing efforts to improve the resolution and robustness of imaging of the pancreas using MRI may thus one day reduce the mortality of this deadly disease. However, the increasing use of cross-sectional imaging has also generated a concomitant clinical conundrum: How to manage incidental pancreatic cystic lesions that are found in over a quarter of patients who undergo MRCP. Efforts to improve the specificity of MRCP for patients with pancreatic cysts and with indeterminate pancreatic masses may be achieved with continued technical advances in MRI, including diffusion-weighted and T1 -weighted dynamic contrast-enhanced MRI. However, developments in quantitative MRI of the pancreas remain challenging, due to the small size of the pancreas and its upper abdominal location, adjacent to bowel and below the diaphragm. Further research is needed to improve MRI of the pancreas as a clinical tool, to positively affect the lives of patients with pancreatic abnormalities. This review focuses on various MR techniques such as MRCP, quantitative imaging, and dynamic contrast-enhanced imaging and their clinical applicability in the imaging of the pancreas, with an emphasis on pancreatic malignant and premalignant lesions. Level of Evidence 5 Technical Efficacy Stage 3 J. MAGN. RESON. IMAGING 2021;53:347-359.

Imaging Features at the Periphery: Hemodynamics, Pathophysiology, and Effect on LI-RADS Categorization.

Liver lesions have different enhancement patterns at dynamic contrast-enhanced imaging. The Liver Imaging Reporting and Data System (LI-RADS) applies the enhancement kinetic of liver observations in its algorithms for imaging-based diagnosis of hepatocellular carcinoma (HCC) in at-risk populations. Therefore, careful analysis of the spatial and temporal features of these enhancement patterns is necessary to increase the accuracy of liver mass characterization. The authors focus on enhancement patterns that are found at or around the margins of liver observations-many of which are recognized and defined by LI-RADS, such as targetoid appearance, rim arterial phase hyperenhancement, peripheral washout, peripheral discontinuous nodular enhancement, enhancing capsule appearance, nonenhancing capsule appearance, corona enhancement, and periobservational arterioportal shunts-as well as peripheral and periobservational enhancement in the setting of posttreatment changes. Many of these are considered major or ancillary features of HCC, ancillary features of malignancy in general, features of non-HCC malignancy, features associated with benign entities, or features related to treatment response. Distinction between these different patterns of enhancement can help with achieving a more specific diagnosis of HCC and better assessment of response to local-regional therapy. ©RSNA, 2021.

Evaluation of treatment response in hepatocellular carcinoma in the explanted liver with Liver Imaging Reporting and Data System version 2017.

OBJECTIVE: To investigate the performance of Liver Imaging Reporting and Data System (LI-RADS) v2017 treatment response algorithm for predicting hepatocellular carcinoma (HCC) viability after locoregional therapy (LRT) using the liver explant as reference. METHODS: One hundred fourteen patients with 206 HCCs who underwent liver transplantation (LT) after LRT for HCCs were included in this retrospective study. Two radiologists independently evaluated tumor viability using the LI-RADS and modified RECIST (mRECIST) with CT and MRI, respectively. The sensitivity and specificity of arterial phase hyperenhancement (APHE) and LR-TR viable criteria (any of three findings: APHE, washout, and enhancement pattern similar to pretreatment imaging) were compared using logistic regression. Receiver operating characteristics (ROC) analysis was used to compare the diagnostic performance between LI-RADS and mRECIST and between CT and MRI. RESULTS: The sensitivity and specificity for diagnosing viable tumor were not significantly different between APHE alone and LR-TR viable criteria on CT (p = 0.054 and p = 0.317) and MRI (p = 0.093 and p = 0.603). On CT, the area under the ROC curve (AUC) of LI-RADS was significantly higher than that of mRECIST (0.733 vs. 0.657, p < 0.001). On MRI, there was no significant difference in AUCs between LI-RADS and mRECIST (0.802 vs. 0.791, p = 0.500). Intra-individual comparison of CT and MRI showed comparable AUCs using LI-RADS (0.783 vs. 0.795, p = 0.776). CONCLUSIONS: LI-RADS v2017 treatment response algorithm showed better diagnostic performance than mRECIST on CT. With LI-RADS, CT and MRI were comparable to diagnose tumor viability of HCC after LRT. KEY POINTS: • Using Liver Imaging Reporting and Data System (LI-RADS) v2017 treatment response algorithm, the viability of hepatocellular carcinoma (HCC) after locoregional therapy (LRT) can be accurately diagnosed. • LI-RADS v2017 treatment response algorithm is superior to modified Response Evaluation Criteria in Solid Tumors for evaluating HCC viability using CT. • Either CT or MRI can be performed to assess tumor viability after LRT using LI-RADS v2017 treatment response algorithm.

Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation.

OBJECTIVES: This study aims to measure the reproducibility of radiomic features in pancreatic parenchyma and ductal adenocarcinomas (PDAC) in patients who underwent consecutive contrast-enhanced computed tomography (CECT) scans. METHODS: In this IRB-approved and HIPAA-compliant retrospective study, 37 pairs of scans from 37 unique patients who underwent CECTs within a 2-week interval were included in the analysis of the reproducibility of features derived from pancreatic parenchyma, and a subset of 18 pairs of scans were further analyzed for the reproducibility of features derived from PDAC. In each patient, pancreatic parenchyma and pancreatic tumor (when present) were manually segmented by two radiologists independently. A total of 266 radiomic features were extracted from the pancreatic parenchyma and tumor region and also the volume and diameter of the tumor. The concordance correlation coefficient (CCC) was calculated to assess feature reproducibility for each patient in three scenarios: (1) different radiologists, same CECT; (2) same radiologist, different CECTs; and (3) different radiologists, different CECTs. RESULTS: Among pancreatic parenchyma-derived features, using a threshold of CCC > 0.90, 58/266 (21.8%) and 48/266 (18.1%) features met the threshold for scenario 1, 14/266 (5.3%) and 15/266 (5.6%) for scenario 2, and 14/266 (5.3%) and 10/266 (3.8%) for scenario 3. Among pancreatic tumor-derived features, 11/268 (4.1%) and 17/268 (6.3%) features met the threshold for scenario 1, 1/268 (0.4%) and 5/268 (1.9%) features met the threshold for scenario 2, and no features for scenario 3 met the threshold, respectively. CONCLUSIONS: Variations between CECT scans affected radiomic feature reproducibility to a greater extent than variation in segmentation. A smaller number of pancreatic tumor-derived radiomic features were reproducible compared with pancreatic parenchyma-derived radiomic features under the same conditions. KEY POINTS: • For pancreatic-derived radiomic features from contrast-enhanced CT (CECT), fewer than 25% are reproducible (with a threshold of CCC < 0.9) in a clinical heterogeneous dataset. • Variations between CECT scans affected the number of reproducible radiomic features to a greater extent than variations in radiologist segmentation. • A smaller number of pancreatic tumor-derived radiomic features were reproducible compared with pancreatic parenchyma-derived radiomic features under the same conditions.

LI-RADS Treatment Response Algorithm: Performance and Diagnostic Accuracy.

Background In 2017, the Liver Imaging Reporting and Data System (LI-RADS) included an algorithm for the assessment of hepatocellular carcinoma (HCC) treated with local-regional therapy. The aim of the algorithm was to enable standardized evaluation of treatment response to guide subsequent therapy. However, the performance of the algorithm has not yet been validated in the literature. Purpose To evaluate the performance of the LI-RADS 2017 Treatment Response algorithm for assessing the histopathologic viability of HCC treated with bland arterial embolization. Materials and Methods This retrospective study included patients who underwent bland arterial embolization for HCC between 2006 and 2016 and subsequent liver transplantation. Three radiologists independently assessed all treated lesions by using the CT/MRI LI-RADS 2017 Treatment Response algorithm. Radiology and posttransplant histopathology reports were then compared. Lesions were categorized on the basis of explant pathologic findings as either completely (100%) or incompletely (<100%) necrotic, and performance characteristics and predictive values for the LI-RADS Treatment Response (LR-TR) Viable and Nonviable categories were calculated for each reader. Interreader association was calculated by using the Fleiss κ. Results A total of 45 adults (mean age, 57.1 years ± 8.2; 13 women) with 63 total lesions were included. For predicting incomplete histopathologic tumor necrosis, the accuracy of the LR-TR Viable category for the three readers was 60%-65%, and the positive predictive value was 86%-96%. For predicting complete histopathologic tumor necrosis, the accuracy of the LR-TR Nonviable category was 67%-71%, and the negative predictive value was 81%-87%. By consensus, 17 (27%) of 63 lesions were categorized as LR-TR Equivocal, and 12 of these lesions were incompletely necrotic. Interreader association for the LR-TR category was moderate (κ = 0.55; 95% confidence interval: 0.47, 0.67). Conclusion The Liver Imaging Reporting and Data System 2017 Treatment Response algorithm had high predictive value and moderate interreader association for the histopathologic viability of hepatocellular carcinoma treated with bland arterial embolization when lesions were assessed as Viable or Nonviable. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Gervais in this issue.

Quantitative imaging features of pretreatment CT predict volumetric response to chemotherapy in patients with colorectal liver metastases.

OBJECTIVES: This study investigates whether quantitative image analysis of pretreatment CT scans can predict volumetric response to chemotherapy for patients with colorectal liver metastases (CRLM). METHODS: Patients treated with chemotherapy for CRLM (hepatic artery infusion (HAI) combined with systemic or systemic alone) were included in the study. Patients were imaged at baseline and approximately 8 weeks after treatment. Response was measured as the percentage change in tumour volume from baseline. Quantitative imaging features were derived from the index hepatic tumour on pretreatment CT, and features statistically significant on univariate analysis were included in a linear regression model to predict volumetric response. The regression model was constructed from 70% of data, while 30% were reserved for testing. Test data were input into the trained model. Model performance was evaluated with mean absolute prediction error (MAPE) and R2. Clinicopatholologic factors were assessed for correlation with response. RESULTS: 157 patients were included, split into training (n = 110) and validation (n = 47) sets. MAPE from the multivariate linear regression model was 16.5% (R2 = 0.774) and 21.5% in the training and validation sets, respectively. Stratified by HAI utilisation, MAPE in the validation set was 19.6% for HAI and 25.1% for systemic chemotherapy alone. Clinical factors associated with differences in median tumour response were treatment strategy, systemic chemotherapy regimen, age and KRAS mutation status (p < 0.05). CONCLUSION: Quantitative imaging features extracted from pretreatment CT are promising predictors of volumetric response to chemotherapy in patients with CRLM. Pretreatment predictors of response have the potential to better select patients for specific therapies. KEY POINTS: • Colorectal liver metastases (CRLM) are downsized with chemotherapy but predicting the patients that will respond to chemotherapy is currently not possible. • Heterogeneity and enhancement patterns of CRLM can be measured with quantitative imaging. • Prediction model constructed that predicts volumetric response with 20% error suggesting that quantitative imaging holds promise to better select patients for specific treatments.

Pilot study of rapid MR pancreas screening for patients with BRCA mutation.

PURPOSE: To develop and optimize a rapid magnetic resonance imaging (MRI) screening protocol for pancreatic cancer to be performed in conjunction with breast MRI screening in breast cancer susceptibility gene (BRCA)-positive individuals. METHODS: An IRB-approved prospective study was conducted. The rapid screening pancreatic MR protocol was designed to be less than 10 min to be performed after a standard breast MRI protocol. Protocol consisted of coronal NT T2 SSFSE, axial NT T2 SSFSE and axial NT rFOV FOCUS DWI, and axial T1. Images were acquired with the patient in the same prone position of breast MRI using the built-in body coil. Image quality was qualitatively assessed by two radiologists with 12 and 13 years of MRI experience, respectively. The imaging protocol was modified until an endpoint of five consecutive patients with high-quality diagnostic images were achieved. Signal-to-noise ratio and contrast-to-noise ratio were assessed. RESULTS: The rapid pancreas MR protocol was successfully completed in all patients. Diagnostic image quality was achieved for all patients. Excellent image quality was achieved for low b values; however, image quality at higher b values was more variable. In one patient, a pancreatic neuroendocrine tumor was found and the patient was treated surgically. In four patients, small pancreatic cystic lesions were detected. In one subject, a hepatic mass was identified and confirmed as adenoma by liver MRI. CONCLUSION: Rapid MR protocol for pancreatic cancer screening is feasible and has the potential to play a role in screening BRCA patients undergoing breast MRI. KEY POINT: • Develop and optimize a rapid magnetic resonance imaging (MRI) screening protocol for pancreatic cancer to be performed in conjunction with breast MRI screening in BRCA mutation positive individuals.

Comparison of Navigator Triggering Reduced Field of View and Large Field of View Diffusion-Weighted Imaging of the Pancreas.

RATIONALE AND OBJECTIVES: The purpose of this study is to compare image quality, presence and grade of artifacts, signal-to-noise ratio, and apparent diffusion coefficient (ADC) values in pancreatic tissue between high-resolution navigator-triggered (NT) restricted field of view (rFOV) FOCUS single-shot (SS) echo-planar imaging (EPI) diffusion-weighted imaging (DWI) and NT large FOV SS-EPI DWI. MATERIALS AND METHODS: Magnetic resonance imaging examinations were performed with GE 3-T systems using a 32-channel body array coil. Seventeen consecutive patients were imaged. A 5-point scale semiquantitative grading system was used to evaluate image quality and general artifacts. Signal-to-noise ratio and ADC were measured in the head, body, and tail of the pancreas. Statistical analysis was performed using Student t test and Wilcoxon signed rank test, with differences considered significant for P value less than 0.05. RESULTS: More artifacts were present on large FOV compared with rFOV FOCUS SS-EPI DW images (P < 0.01). Restricted field of view image quality was subjectively better (P < 0.01). No difference in the signal-to-noise ratio was demonstrated between the 2 image datasets. Apparent diffusion coefficient values were significantly lower (P < 0.01) when calculated from rFOV images than large FOV images. CONCLUSIONS: Our results demonstrate better image quality and reduced artifacts in rFOV images compared with large FOV DWI. Measurements from ADC maps derived from rFOV DWI show significantly lower ADC values when compared with ADC maps derived from large FOV DWI.

Preoperative risk prediction for intraductal papillary mucinous neoplasms by quantitative CT image analysis.

BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs) are radiographically identifiable potential precursor lesions of pancreatic adenocarcinoma. While resection is recommended when main duct dilation is present, management of branch duct IPMN (BD-IPMN) remains controversial. This study sought to evaluate whether preoperative quantitative imaging features of BD-IPMNs could distinguish low-risk disease (low- and intermediate-grade dysplasia) from high-risk disease (high-grade dysplasia and invasive carcinoma). METHODS: Patients who underwent resection between 2005 and 2015 with pathologically proven BD-IPMN and a preoperative CT scan were included in the study. Quantitative image features were extracted using texture analysis and a novel quantitative mural nodularity feature developed for the study. Significant features on univariate analysis were combined with clinical variables to build a multivariate prediction model. RESULTS: Within the study group of 103 patients, 76 (74%) had low-risk disease and 27 (26%) had high-risk disease. Quantitative imaging features were prognostic of low-vs. high-risk disease. The model based only on clinical variables achieved an AUC of 0.67 and 0.79 with the addition of quantitative imaging features. CONCLUSION: Quantitative image analysis of BD-IPMNs is a novel method that may enable risk stratification. External validation may provide a reliable non-invasive prognostic tool for clinicians.

Phase 1 trial evaluating cisplatin, gemcitabine, and veliparib in 2 patient cohorts: Germline BRCA mutation carriers and wild-type BRCA pancreatic ductal adenocarcinoma.

BACKGROUND: A phase 1 trial was used to evaluate a combination of cisplatin, gemcitabine, and escalating doses of veliparib in patients with untreated advanced pancreatic ductal adenocarcinoma (PDAC) in 2 cohorts: a germline BRCA1/2-mutated (BRCA+) cohort and a wild-type BRCA (BRCA-) cohort. The aims were to determine the safety, dose-limiting toxicities (DLTs), maximum tolerated dose, and recommended phase 2 dose (RP2D) of veliparib combined with cisplatin and gemcitabine and to assess the antitumor efficacy (Response Evaluation Criteria in Solid Tumors, version 1.1) and overall survival. METHODS: Gemcitabine and cisplatin were dosed at 600 and 25 mg/m2 , respectively, over 30 minutes on days 3 and 10 of a 21-day cycle. Four dose levels of veliparib were evaluated: 20 (dose level 0), 40 (dose level 1), and 80 mg (dose level 2) given orally twice daily on days 1 to 12 and 80 mg given twice daily on days 1 to 21 (dose level 2A [DL2A]). RESULTS: Seventeen patients were enrolled: 9 BRCA+ patients, 7 BRCA- patients, and 1 patient with an unknown status. DLTs were reached at DL2A (80 mg twice daily on days 1 to 21). Two of the 5 patients in this cohort (40%) experienced grade 4 neutropenia and thrombocytopenia. Two grade 5 events occurred on protocol. The objective response rate in the BRCA+ cohort was 7 of 9 (77.8%). The median overall survival for BRCA+ patients was 23.3 months (95% confidence interval [CI], 3.8-30.2 months). The median overall survival for BRCA- patients was 11 months (95% CI, 1.5-12.1 months). CONCLUSIONS: The RP2D of veliparib was 80 mg by mouth twice daily on days 1 to 12 in combination with cisplatin and gemcitabine; the DLT was myelosuppression. Substantial antitumor activity was seen in BRCA+ PDAC. A randomized phase 2 trial is currently evaluating cisplatin and gemcitabine with and without veliparib for BRCA+ PDAC (NCT01585805). Cancer 2018;124:1374-82. © 2018 American Cancer Society.