Tumor response assessment in hepatocellular carcinoma treated with immunotherapy: imaging biomarkers for clinical decision-making.

OBJECTIVE: To compare the performance of 1D and 3D tumor response assessment for predicting median overall survival (mOS) in patients who underwent immunotherapy for hepatocellular carcinoma (HCC). METHODS: Patients with HCC who underwent immunotherapy between 2017 and 2023 and received multi-phasic contrast-enhanced MRIs pre- and post-treatment were included in this retrospective study. Tumor response was measured using 1D, RECIST 1.1, and mRECIST, and 3D, volumetric, and percentage quantitative EASL (vqEASL and %qEASL). Patients were grouped into disease control vs progression and responders vs non-responders. Kaplan-Meier curves analyzed with log-rank tests assessed the predictive value for mOS. Cox regression modeling evaluated the association of clinical baseline parameters with mOS. RESULTS: This study included 37 patients (mean age, 69.1 years [SD, 8.0]; 33 men). The mOS was 16.9 months. 3D vqEASL and %qEASL successfully stratified patients into disease control and progression (vqEASL: HR 0.21, CI: 0.55-0.08, p < 0.001; %qEASL: HR 0.18, CI: 0.83-0.04, p = 0.013), as well as responder and nonresponder (vqEASL: HR 0.25, CI: 0.08-0.74, p = 0.007; %qEASL: HR 0.17, CI: 0.04-0.72, p = 0.007) for predicting mOS. The 1D criteria, mRECIST stratified into disease control and progression only (HR 0.24, CI: 0.65-0.09, p = 0.002), and RECIST 1.1 showed no predictive value in either stratification. Multivariate Cox regression identified alpha-fetoprotein > 500 ng/mL as a predictor for poor mOS (p = 0.04). CONCLUSION: The 3D quantitative enhancement-based response assessment tool qEASL can predict overall survival in patients undergoing immunotherapy for HCC and could identify non-responders. CLINICAL RELEVANCE STATEMENT: Using 3D quantitative enhancement-based tumor response criteria (qEASL), radiologists' predictions of tumor response in patients undergoing immunotherapy for HCC can be further improved. KEY POINTS: MRI-based tumor response criteria predict immunotherapy survival benefits in HCC patients. 3D tumor response assessment methods surpass current evaluation criteria in predicting overall survival during HCC immunotherapy. Enhancement-based 3D tumor response criteria are robust prognosticators of survival for HCC patients on immunotherapy.

Outcomes of repeat conventional transarterial chemoembolization in patients with liver metastases.

INTRODUCTION AND OBJECTIVES: Although unlimited sessions of conventional transarterial chemoembolization (cTACE) may be performed for liver metastases, there is no data indicating when treatment becomes ineffective. This study aimed to determine the optimal number of repeat cTACE sessions for nonresponding patients before abandoning cTACE in patients with liver metastases. MATERIALS AND METHODS: In this retrospective, single-institutional analysis, patients with liver metastases from neuroendocrine tumors (NET), colorectal carcinoma (CRC), and lung cancer who underwent consecutive cTACE sessions from 2001 to 2015 were studied. Quantitative European Association for Study of the Liver (qEASL) criteria were utilized for response assessment. The association between the number of cTACE and 2-year, 5-year, and overall survival was evaluated to estimate the optimal number of cTACE for each survival outcome. RESULTS: Eighty-five patients underwent a total of 186 cTACE sessions for 117 liver metastases, of which 30.7 % responded to the first cTACE. For the target lesions that did not respond to the first, second, and third cTACE sessions, response rates after the second, third, and fourth cTACE sessions were 33.3 %, 23 %, and 25 %, respectively. The fourth cTACE session was the optimal number for 2-year survival (HR 0.40; 95 %CI: 0.16-0.97; p = 0.04), 5-year survival (HR 0.31; 95 %CI: 0.11-0.87; p = 0.02), and overall survival (HR 0.35; 95 %CI: 0.13-0.89; p = 0.02). CONCLUSIONS: Repeat cTACE in the management of liver metastases from NET, CRC, and lung cancer was associated with improved patient survival. We recommend at least four cTACE sessions before switching to another treatment for nonresponding metastatic liver lesions.

Comparison of Volumetric and 2D Measurements and Longitudinal Trajectories in the Response Assessment of BRAF V600E-Mutant Pediatric Gliomas in the Pacific Pediatric Neuro-Oncology Consortium Clinical Trial.

BACKGROUND AND PURPOSE: Response on imaging is widely used to evaluate treatment efficacy in clinical trials of pediatric gliomas. While conventional criteria rely on 2D measurements, volumetric analysis may provide a more comprehensive response assessment. There is sparse research on the role of volumetrics in pediatric gliomas. Our purpose was to compare 2D and volumetric analysis with the assessment of neuroradiologists using the Brain Tumor Reporting and Data System (BT-RADS) in BRAF V600E-mutant pediatric gliomas. MATERIALS AND METHODS: Manual volumetric segmentations of whole and solid tumors were compared with 2D measurements in 31 participants (292 follow-up studies) in the Pacific Pediatric Neuro-Oncology Consortium 002 trial (NCT01748149). Two neuroradiologists evaluated responses using BT-RADS. Receiver operating characteristic analysis compared classification performance of 2D and volumetrics for partial response. Agreement between volumetric and 2D mathematically modeled longitudinal trajectories for 25 participants was determined using the model-estimated time to best response. RESULTS: Of 31 participants, 20 had partial responses according to BT-RADS criteria. Receiver operating characteristic curves for the classification of partial responders at the time of first detection (median = 2 months) yielded an area under the curve of 0.84 (95% CI, 0.69-0.99) for 2D area, 0.91 (95% CI, 0.80-1.00) for whole-volume, and 0.92 (95% CI, 0.82-1.00) for solid volume change. There was no significant difference in the area under the curve between 2D and solid (P = .34) or whole volume (P = .39). There was no significant correlation in model-estimated time to best response (ρ = 0.39, P >.05) between 2D and whole-volume trajectories. Eight of the 25 participants had a difference of ≥90 days in transition from partial response to stable disease between their 2D and whole-volume modeled trajectories. CONCLUSIONS: Although there was no overall difference between volumetrics and 2D in classifying partial response assessment using BT-RADS, further prospective studies will be critical to elucidate how the observed differences in tumor 2D and volumetric trajectories affect clinical decision-making and outcomes in some individuals.

A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information.

Resection and whole brain radiotherapy (WBRT) are standard treatments for brain metastases (BM) but are associated with cognitive side effects. Stereotactic radiosurgery (SRS) uses a targeted approach with less side effects than WBRT. SRS requires precise identification and delineation of BM. While artificial intelligence (AI) algorithms have been developed for this, their clinical adoption is limited due to poor model performance in the clinical setting. The limitations of algorithms are often due to the quality of datasets used for training the AI network. The purpose of this study was to create a large, heterogenous, annotated BM dataset for training and validation of AI models. We present a BM dataset of 200 patients with pretreatment T1, T1 post-contrast, T2, and FLAIR MR images. The dataset includes contrast-enhancing and necrotic 3D segmentations on T1 post-contrast and peritumoral edema 3D segmentations on FLAIR. Our dataset contains 975 contrast-enhancing lesions, many of which are sub centimeter, along with clinical and imaging information. We used a streamlined approach to database-building through a PACS-integrated segmentation workflow.

Comparison of volumetric and 2D-based response methods in the PNOC-001 pediatric low-grade glioma clinical trial.

Background: Although response in pediatric low-grade glioma (pLGG) includes volumetric assessment, more simplified 2D-based methods are often used in clinical trials. The study's purpose was to compare volumetric to 2D methods. Methods: An expert neuroradiologist performed solid and whole tumor (including cyst and edema) volumetric measurements on MR images using a PACS-based manual segmentation tool in 43 pLGG participants (213 total follow-up images) from the Pacific Pediatric Neuro-Oncology Consortium (PNOC-001) trial. Classification based on changes in volumetric and 2D measurements of solid tumor were compared to neuroradiologist visual response assessment using the Brain Tumor Reporting and Data System (BT-RADS) criteria for a subset of 65 images using receiver operating characteristic (ROC) analysis. Longitudinal modeling of solid tumor volume was used to predict BT-RADS classification in 54 of the 65 images. Results: There was a significant difference in ROC area under the curve between 3D solid tumor volume and 2D area (0.96 vs 0.78, P = .005) and between 3D solid and 3D whole volume (0.96 vs 0.84, P = .006) when classifying BT-RADS progressive disease (PD). Thresholds of 15-25% increase in 3D solid tumor volume had an 80% sensitivity in classifying BT-RADS PD included in their 95% confidence intervals. The longitudinal model of solid volume response had a sensitivity of 82% and a positive predictive value of 67% for detecting BT-RADS PD. Conclusions: Volumetric analysis of solid tumor was significantly better than 2D measurements in classifying tumor progression as determined by BT-RADS criteria and will enable more comprehensive clinical management.

Application of novel PACS-based informatics platform to identify imaging based predictors of CDKN2A allelic status in glioblastomas.

Gliomas with CDKN2A mutations are known to have worse prognosis but imaging features of these gliomas are unknown. Our goal is to identify CDKN2A specific qualitative imaging biomarkers in glioblastomas using a new informatics workflow that enables rapid analysis of qualitative imaging features with Visually AcceSAble Rembrandtr Images (VASARI) for large datasets in PACS. Sixty nine patients undergoing GBM resection with CDKN2A status determined by whole-exome sequencing were included. GBMs on magnetic resonance images were automatically 3D segmented using deep learning algorithms incorporated within PACS. VASARI features were assessed using FHIR forms integrated within PACS. GBMs without CDKN2A alterations were significantly larger (64 vs. 30%, p = 0.007) compared to tumors with homozygous deletion (HOMDEL) and heterozygous loss (HETLOSS). Lesions larger than 8 cm were four times more likely to have no CDKN2A alteration (OR: 4.3; 95% CI 1.5-12.1; p < 0.001). We developed a novel integrated PACS informatics platform for the assessment of GBM molecular subtypes and show that tumors with HOMDEL are more likely to have radiographic evidence of pial invasion and less likely to have deep white matter invasion or subependymal invasion. These imaging features may allow noninvasive identification of CDKN2A allele status.