ArticleCancer imaging : the official publication of the International Cancer Imaging Society2019
Prediction of hepatocellular carcinoma response to
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 19 citations in OpenAlex.
- Role of MRI in Imaging Assessment of Radiation-Based Treatment of Hepatocellular Carcinoma.Cancers · 2026Review
- Can ADC changes help mRECIST or LI-RADS treatment response algorithm better diagnose pathological response of HCC after preoperative radiotherapy? Secondary analysis of a prospective phase 2 trial.Insights into imaging · 2025Article
- Predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients based on ultrasound longitudinal temporal depth network fusion model.Breast cancer research : BCR · 2025Article
- Current status of magnetic resonance imaging radiomics in hepatocellular carcinoma: A quantitative review with Radiomics Quality Score.World journal of gastroenterology · 2024Review
- Response Assessment of Primary Liver Tumors to Novel Therapies: an Imaging Perspective.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2023Review
- Quantitative and qualitative evaluation of liver metastases with intraprocedural cone beam CT prior to transarterial radioembolization as a predictor of treatment response.Research in diagnostic and interventional imaging · 2022Article
- Radiomics-Based Machine Learning Models for Predicting P504s/P63 Immunohistochemical Expression: A Noninvasive Diagnostic Tool for Prostate Cancer.Frontiers in oncology · 2022Article
- Early effect ofEuropean radiology · 2021Article
- Radiomics of hepatocellular carcinoma: promising roles in patient selection, prediction, and assessment of treatment response.Abdominal radiology (New York) · 2021Review
- Radiomics of hepatocellular carcinoma.Abdominal radiology (New York) · 2021Review
- Assessment of Hepatocellular Carcinoma Response toRadiology. Imaging cancer · 2020Article
- Lesion Volume Divided by ADC Measures Is an Independent Prognostic Marker in Colorectal Liver Metastasis Treated by Y90-radioembolization.In vivo (Athens, Greece)Article
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Authors and funding
8 authors at 6 institutions in 5 countries.
Funding
Abstract
purposeTo assess the predictive value of volumetric apparent diffusion coefficient (vADC) histogram quantification obtained before and 6 weeks (6w) post-treatment for assessment of hepatocellular carcinoma (HCC) response to
methodsIn this retrospective study, 22 patients (M/F 15/7, mean age 65y) who underwent lobar RE were included between October 2013 and November 2014. All patients underwent routine liver MRI pre-treatment and 6w after RE. Two readers assessed index tumor response at 6 months after RE in consensus, using mRECIST criteria. vADC histogram parameters of index tumors at baseline and 6w, and changes in vADC (ΔvADC) histogram parameters were calculated. The predictive value of ADC metrics was assessed by logistic regression with stepwise parameter selection and ROC analyses.
resultsTwenty two HCC lesions (mean size 3.9 ± 2.9 cm, range 1.2-12.3 cm) were assessed. Response at 6 months was as follows: complete response (CR, n = 6), partial response (PR, n = 3), stable disease (SD, n = 12) and progression (PD, n = 1). vADC median/mode at 6w (1.81-1.82 vs. 1.29-1.35 × 10
conclusionDiffusion histogram parameters obtained at 6w and early changes in ADC from baseline are predictive of subsequent response of HCCs treated with RE, while pre-treatment vADC histogram parameters are not. These results need confirmation in a larger study.
trial registrationThis retrospective study was IRB-approved and the requirement for informed consent was waived.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.