European Radiology最新文献

{"title":"Relationship between [¹⁸F]FDG PET/CT findings and claudin 18.2 expression in metastatic gastric cancer.","authors":"Hongyan Yin, Rongkui Luo, Jing Lv, Wujian Mao, Hongcheng Shi","doi":"10.1007/s00330-024-11186-5","DOIUrl":"10.1007/s00330-024-11186-5","url":null,"abstract":"<p><strong>Aim: </strong>Given that claudin 18.2 (CLDN18.2) is a cell surface protein specifically expressed by gastric cancer cells, anti-CLDN18.2 antibodies have demonstrated significant antitumor effects in patients with advanced gastric adenocarcinoma. The correlation of [¹⁸F]FDG PET/CT with CLDN18.2 expression remains unexplored. This study aimed to investigate whether CLDN18.2 expression was associated with [¹⁸F]FDG uptake and whether [¹⁸F]FDG PET/CT can be used to predict the CLDN18.2 status of gastric cancer.</p><p><strong>Methods: </strong>A retrospective analysis of [¹⁸F]FDG PET/CT images from 163 patients diagnosed with metastatic gastric cancer was conducted, and the expression of CLDN18.2 was assessed immunohistochemically. SUV_max, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated in 3D mode using vendor-provided software. The relationship between PET metabolic parameters and CLDN18.2 status was analyzed.</p><p><strong>Results: </strong>CLDN18.2-negative tumors showed a higher median SUV_max of 13.2 (1.8-46.7) compared to CLDN18.2-positive tumors at 7.55 (2.3-34.8), with a significant difference (p < 0.001). The median TLG was significantly higher in CLDN18.2-negative tumors (231.6) than in CLDN18.2-positive ones (81.14), indicating greater metabolic activity (p = 0.001). Multivariate analysis suggested that SUV_max remained significantly correlated with the status of CLDN18.2 (p = 0.01). CLDN18.2 expression was predicted with an accuracy of 69.9% when the SUV_max value of 10.9 was used as a cutoff point for analysis.</p><p><strong>Conclusion: </strong>Relatively reduced [¹⁸F]FDG uptake in metastatic gastric cancers correlates with positive CLDN18.2 expression compared to those with negative CLDN18.2 expression. [¹⁸F]FDG PET/CT may be useful for predicting the CLDN18.2 status of gastric cancer and thus aid in optimal treatment decisions.</p><p><strong>Key points: </strong>Question The study resolves the clinical issue of determining the correlation between [¹⁸F]FDG PET/CT imaging and claudin 18.2 expression in metastatic gastric cancer. Findings Claudin 18.2-positive metastatic gastric cancers exhibit relatively lower [¹⁸F]FDG uptake than negative ones. The SUV_max of 10.9 moderately predicts claudin 18.2 expression. Clinical relevance [¹⁸F]FDG PET/CT imaging could be a noninvasive way to predict claudin 18.2 status in metastatic gastric cancer, helping to improve personalized treatment plans.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"3442-3449"},"PeriodicalIF":4.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142686559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Musculoskeletal fracture detection: artificial intelligence and machine learning-based diagnostic advantages and pitfalls.","authors":"Truman Archer, Sawyer Archer, Samir S Shah","doi":"10.1007/s00330-024-11250-0","DOIUrl":"10.1007/s00330-024-11250-0","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"3649-3651"},"PeriodicalIF":4.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142784815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of a deep learning prostate cancer detection system on biparametric MRI against radiological reading.","authors":"Noëlie Debs, Alexandre Routier, Alexandre Bône, Marc-Miche Rohé","doi":"10.1007/s00330-024-11287-1","DOIUrl":"10.1007/s00330-024-11287-1","url":null,"abstract":"<p><strong>Objectives: </strong>This study aims to evaluate a deep learning pipeline for detecting clinically significant prostate cancer (csPCa), defined as Gleason Grade Group (GGG) ≥ 2, using biparametric MRI (bpMRI) and compare its performance with radiological reading.</p><p><strong>Materials and methods: </strong>The training dataset included 4381 bpMRI cases (3800 positive and 581 negative) across three continents, with 80% annotated using PI-RADS and 20% with Gleason Scores. The testing set comprised 328 cases from the PROSTATEx dataset, including 34% positive (GGG ≥ 2) and 66% negative cases. A 3D nnU-Net was trained on bpMRI for lesion detection, evaluated using histopathology-based annotations, and assessed with patient- and lesion-level metrics, along with lesion volume, and GGG. The algorithm was compared to non-expert radiologists using multi-parametric MRI (mpMRI).</p><p><strong>Results: </strong>The model achieved an AUC of 0.83 (95% CI: 0.80, 0.87). Lesion-level sensitivity was 0.85 (95% CI: 0.82, 0.94) at 0.5 False Positives per volume (FP/volume) and 0.88 (95% CI: 0.79, 0.92) at 1 FP/volume. Average Precision was 0.55 (95% CI: 0.46, 0.64). The model showed over 0.90 sensitivity for lesions larger than 650 mm³ and exceeded 0.85 across GGGs. It had higher true positive rates (TPRs) than radiologists equivalent FP rates, achieving TPRs of 0.93 and 0.79 compared to radiologists' 0.87 and 0.68 for PI-RADS ≥ 3 and PI-RADS ≥ 4 lesions (p ≤ 0.05).</p><p><strong>Conclusion: </strong>The DL model showed strong performance in detecting csPCa on an independent test cohort, surpassing radiological interpretation and demonstrating AI's potential to improve diagnostic accuracy for non-expert radiologists. However, detecting small lesions remains challenging.</p><p><strong>Key points: </strong>Question Current prostate cancer detection methods often do not involve non-expert radiologists, highlighting the need for more accurate deep learning approaches using biparametric MRI. Findings Our model outperforms radiologists significantly, showing consistent performance across Gleason Grade Groups and for medium to large lesions. Clinical relevance This AI model improves prostate detection accuracy in prostate imaging, serves as a benchmark with reference performance on a public dataset, and offers public PI-RADS annotations, enhancing transparency and facilitating further research and development.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"3134-3143"},"PeriodicalIF":4.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142853595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRI and zero or ultra-short echo-time sequences in secondary interstitial lung diseases: current applicability and future perspectives.","authors":"Nicholas Landini","doi":"10.1007/s00330-025-11378-7","DOIUrl":"10.1007/s00330-025-11378-7","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"2955-2957"},"PeriodicalIF":4.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143074379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ESR Essentials: Image evaluation of patients with seizures and epilepsy-practice recommendations by the European Society of Neuroradiology.","authors":"Núria Bargalló, Paolo Vitali, Juan Álvarez-Linera, Cristina Rosazza, Sofía González-Ortiz, Horst Urbach","doi":"10.1007/s00330-024-11266-6","DOIUrl":"10.1007/s00330-024-11266-6","url":null,"abstract":"<p><p>Epilepsy, a neurological disorder characterised by recurrent seizures, poses significant challenges in diagnosis, treatment, and management. Understanding the underlying causes and identifying precise anatomical locations of epileptogenic foci are critical for effective management strategies, particularly in drug-resistant patients. Neuroimaging techniques, particularly magnetic resonance (MR), play a pivotal role in the evaluation of epilepsy patients, offering insights into structural abnormalities, epileptogenic lesions, and functional alterations within the brain. Diverse clinical scenarios that warrant neuroimaging in epilepsy patients, ranging from first-onset seizures to drug-resistant epilepsy, will be presented, elucidating the considerations and recommendations for imaging modalities. The dedicated MR protocol for epilepsy patients will be discussed, justifying the rationale behind sequence selection and optimisation strategies and providing clues about how to read these magnetic resonance imaging (MRI) exams. Finally, MR findings associated with common epileptogenic lesions, such as hippocampal sclerosis, focal cortical dysplasia, and long-term epilepsy-associated tumours, will be described. This article reviews essential concepts, including definitions, classification, imaging indications, protocols, and neuroradiological findings, aiming to understand how neuroimaging contributes to diagnosing and managing epilepsy comprehensively. KEY POINTS: MR should be performed in adults and children with a recent diagnosis of epilepsy of unknown aetiology, a first seizure, and a negative CT. Performing a dedicated MR protocol in focal epilepsy is essential for increasing the detection of potentially epileptogenic lesions. For presurgical evaluations, MR abnormalities should correlate with the electric pattern, semiology data, or other neuroimaging examination to be considered the epileptogenic lesion.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"3385-3395"},"PeriodicalIF":4.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142853571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of intensity standardisation and ComBat batch size on clinical-radiomic prognostic models performance in a multi-centre study of patients with glioblastoma.","authors":"Kavi Fatania, Russell Frood, Hitesh Mistry, Susan C Short, James O'Connor, Andrew F Scarsbrook, Stuart Currie","doi":"10.1007/s00330-024-11168-7","DOIUrl":"10.1007/s00330-024-11168-7","url":null,"abstract":"<p><strong>Purpose: </strong>To assess the effect of different intensity standardisation techniques (ISTs) and ComBat batch sizes on radiomics survival model performance and stability in a heterogenous, multi-centre cohort of patients with glioblastoma (GBM).</p><p><strong>Methods: </strong>Multi-centre pre-operative MRI acquired between 2014 and 2020 in patients with IDH-wildtype unifocal WHO grade 4 GBM were retrospectively evaluated. WhiteStripe (WS), Nyul histogram matching (HM), and Z-score (ZS) ISTs were applied before radiomic feature (RF) extraction. RFs were realigned using ComBat and minimum batch size (MBS) of 5, 10, or 15 patients. Cox proportional hazards models for overall survival (OS) prediction were produced using five different selection strategies and the impact of IST and MBS was evaluated using bootstrapping. Calibration, discrimination, relative explained variation, and model fit were assessed. Instability was evaluated using 95% confidence intervals (95% CIs), feature selection frequency and calibration curves across the bootstrap resamples.</p><p><strong>Results: </strong>One hundred ninety-five patients were included. Median OS = 13 (95% CI: 12-14) months. Twelve to fourteen unique MRI protocols were used per MRI sequence. HM and WS produced the highest relative increase in model discrimination, explained variation and model fit but IST choice did not greatly impact on stability, nor calibration. Larger ComBat batches improved discrimination, model fit, and explained variation but higher MBS (reduced sample size) reduced stability (across all performance metrics) and reduced calibration accuracy.</p><p><strong>Conclusion: </strong>Heterogenous, real-world GBM data poses a challenge to the reproducibility of radiomics. ComBat generally improved model performance as MBS increased but reduced stability and calibration. HM and WS tended to improve model performance.</p><p><strong>Key points: </strong>Question ComBat harmonisation of RFs and intensity standardisation of MRI have not been thoroughly evaluated in multicentre, heterogeneous GBM data. Findings The addition of ComBat and ISTs can improve discrimination, relative model fit, and explained variance but degrades the calibration and stability of survival models. Clinical relevance Radiomics risk prediction models in real-world, multicentre contexts could be improved by ComBat and ISTs, however, this degrades calibration and prediction stability and this must be thoroughly investigated before patients can be accurately separated into different risk groups.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"3354-3366"},"PeriodicalIF":4.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12081554/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142738812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing three-dimensional zero echo time (3D-ZTE) lung MRI and chest CT in the evaluation of systemic sclerosis-related interstitial lung disease.","authors":"Furkan Ufuk, Burak Kurnaz, Hakki Peker, Ergin Sagtas, Zeynep Dundar Ok, Veli Cobankara","doi":"10.1007/s00330-024-11216-2","DOIUrl":"10.1007/s00330-024-11216-2","url":null,"abstract":"<p><strong>Objective: </strong>Systemic sclerosis (SSc) is a chronic disease that can cause interstitial lung disease (ILD), a poor prognostic factor in SSc patients. Given the concerns over radiation exposure from repeated CT scans, there is a growing interest in exploring radiation-free imaging alternatives like MRI for ILD evaluation. The aim of this study is to assess the efficacy of three-dimensional zero echo time (3D-ZTE) MRI in assessing SSc-related ILD compared to the thin-slice chest CT.</p><p><strong>Methods: </strong>This prospective single-center study investigated 65 SSc patients. SSc patients underwent CT, 3D-ZTE lung MRI, and pulmonary function tests (PFTs) within a week. Three independent reviews visually quantified ILD extent on ZTE and CT imaging and the correlation of ILD extent with PFTs was analyzed. Statistical analyses were performed, including the intraclass correlation coefficient (ICC), Kruskal-Wallis tests, Bland-Altmann analysis, and correlation analyses between imaging results and PFTs.</p><p><strong>Results: </strong>ILD was detected in 45 patients via CT. 3D-ZTE MRI identified ILD in 41 (91.1%) of these cases, demonstrating a strong correlation with CT in assessing ILD severity (r = 0.986, p < 0.001). The median ILD extent scores were 5% for CT and 6% for 3D-ZTE MRI. Interobserver reliability for 3D-ZTE MRI was excellent, with ICC values ranging from 0.853 to 0.969. The analysis also revealed significant negative correlations between ILD extent on ZTE MRI and lung function, particularly FVC.</p><p><strong>Conclusion: </strong>3D-ZTE lung MRI is a reliable and radiation-free alternative to chest CT for evaluating SSc-related ILD, with a strong correlation in assessing total fibrosis and ground-glass opacities, though limitations remain in detecting fine reticulations and coarseness.</p><p><strong>Key points: </strong>Question Can 3D-ZTE MRI replace thin-slice chest CT as a radiation-free method for assessing SSc-related ILD? Findings 3D-ZTE lung MRI showed an excellent agreement with thin-slice CT in evaluating ILD extent in SSc patients (r = 0.986, p < 0.001). Clinical relevance 3D-ZTE lung MRI provides a reliable, radiation-free alternative to CT for assessing ILD extent in SSc patients, ensuring safer longitudinal monitoring and management.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"2958-2967"},"PeriodicalIF":4.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142727274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of the Node Reporting and Data System (Node-RADS) for standardized CT evaluation of regional lymph nodes in esophageal squamous cell carcinoma patients.","authors":"Yu Fang, Ming Chen, XuFeng Zheng, Yubin Yao, Kainan Huang, Silian Chen, Tingting Xu, Zhuangyong Xu, Daiying Lin","doi":"10.1007/s00330-024-11234-0","DOIUrl":"10.1007/s00330-024-11234-0","url":null,"abstract":"<p><strong>Objectives: </strong>The accurate identification of positive lymph nodes in esophageal squamous cell carcinoma (ESCC) influences patient risk assessment and treatment decisions, but there is no standardized approach for radiological evaluation. The aim of this study was to verify the diagnostic performance of the new Node Reporting and Data System 1.0 (Node-RADS) in the assessment of lymph node metastasis in patients with ESCC, as verified by final histopathology.</p><p><strong>Methods: </strong>Node-RADS is a scoring system composed of different criteria for evaluating lymph node metastasis, with scores ranging from 1 to 5, corresponding to the degree of suspicion of lymph node involvement. In this single-center study, Node-RADS was used to retrospectively evaluate regional lymph nodes in 173 ESCC patients who underwent computed tomography (CT) before radical resection. In addition, the area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for the Node-RADS score and individual criteria.</p><p><strong>Results: </strong>Node-RADS outperformed the individual assessment criteria (AUC: 94.3%, sensitivity: 96.5%, specificity: 92.0%), with scores ≥ 3 indicating the maximum diagnostic effectiveness. The diagnostic efficiency of the highest Node-RADS score surpassed that of the short axis score (AUC: 94.3% vs. 81.9%, p < 0.001). Our results indicated that the best diagnostic cut-off points for the short axis, long axis and short axis/long axis ratio were 9 mm, 11 mm, and 0.74, respectively.</p><p><strong>Conclusion: </strong>Node-RADS has emerged as a practical, repetitive method for the early identification of high-risk metastatic lymph nodes, providing therapeutic guidance and predicting disease prognosis in ESCC patients.</p><p><strong>Key points: </strong>Question How does the Node Reporting and Data System 1.0 (Node-RADS) perform in the assessment of lymph node metastasis in patients with esophageal squamous cell carcinoma (ESCC)? Findings The maximum diagnostic efficiency was achieved with a Node-RADS score of ≥ 3. Clinical relevance The Node-RADS has improved diagnostic efficiency for distinguishing lymph node metastasis in patients with ESCC.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"2999-3009"},"PeriodicalIF":4.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142754815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Amide proton transfer weighted MRI measurements yield consistent and repeatable results in patients with gliomas: a prospective test-retest study.","authors":"Irada Pflüger, Aditya Rastogi, Stefano Casagranda, Christos Papageorgakis, Rouven Behnisch, Patrick Liebig, Marcel Prager, Franziska Maria Ippen, Daniel Paech, Wolfgang Wick, Martin Bendszus, Gianluca Brugnara, Philipp Vollmuth","doi":"10.1007/s00330-024-11197-2","DOIUrl":"10.1007/s00330-024-11197-2","url":null,"abstract":"<p><strong>Objectives: </strong>Chemical exchange saturation transfer (CEST) imaging has emerged as a promising imaging biomarker, but its reliability for clinical practice remains uncertain. This study aimed to investigate the robustness of CEST parameters in healthy volunteers and patients with brain tumours.</p><p><strong>Methods: </strong>A total of n = 52 healthy volunteers and n = 52 patients with histologically confirmed glioma underwent two consecutive 3-T MRI scans separated by a 1-min break. The CEST measurements were reconstructed using two models: with and without fluid suppression and included the evaluation of both amide (amidePTw) and amine (aminePTw) offsets. Mean intensity values in healthy volunteers were compared from volumetric segmentations (VOI) of grey matter, white matter, and the whole brain. Mean intensity values in brain tumour patients were assessed from VOI of the contrast-enhancing, non-enhancing and whole tumour, as well as from the normal-appearing white matter. Test-retest reliability was assessed using ICC and Bland-Altman plots.</p><p><strong>Results: </strong>The amidePTw/aminePTw signal intensity distribution was significantly affected by fluid suppression (p < 0.001 for each VOI). Test-retest reliability in healthy volunteers showed fair to excellent agreement (ICC = 0.53-0.74), with the highest signal intensity values observed by amidePTw (ICC = 0.73-0.74). In patients, an excellent agreement of both amidePTw and aminePTw measurements was observed across different tumour regions (ICC = 0.76-0.89), with the highest ICC for contrast-enhancing tumour measurements. Bland-Altman analysis indicated negligible systematic bias and no proportional bias in measurement errors.</p><p><strong>Conclusion: </strong>Measurements from amide/aminePTw imaging obtained from an adequately powered test-retest study yield consistent and reproducible results in glioma patients, as a prerequisite for robust imaging biomarker discovery in neuro-oncology.</p><p><strong>Key points: </strong>Question The clinical reliability of chemical exchange saturation transfer imaging remains uncertain, necessitating further investigation to establish its robustness as a biomarker in neuro-oncology. Findings This study demonstrates that amide/amine proton transfer imaging provides repeatable, high-agreement measurements in glioma patients, particularly in contrast-enhancing tumour regions. Clinical relevance This test-retest study demonstrates that chemical exchange saturation transfer imaging using two models and assessing amide and amine offsets yield consistent and repeatable results in glioma patients, as a prerequisite for robust imaging biomarker discovery for neuro-oncology studies and clinical practice.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"3367-3379"},"PeriodicalIF":4.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142853529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prognostic value of early response in predicting survival in hepatocellular carcinoma patients treated with selective internal radiation therapy.","authors":"Michel Dupuis, Axelle Dupont, Silvia Pizza, Valérie Vilgrain, Aurélie Bando Delaunay, Rachida Lebtahi, Mohamed Bouattour, Maxime Ronot, Jules Grégory","doi":"10.1007/s00330-024-11253-x","DOIUrl":"10.1007/s00330-024-11253-x","url":null,"abstract":"<p><strong>Objectives: </strong>This study evaluates the prognostic value of tumor response on CT at 3 months, assessed by Response Evaluation Criteria in Solid Tumors (RECIST), modified RECIST (mRECIST), and Liver Imaging Reporting and Data System Treatment Response Algorithm (LR-TRA) in patients with hepatocellular carcinoma (HCC) treated with selective internal radiation therapy (SIRT).</p><p><strong>Materials and methods: </strong>A retrospective analysis was conducted on 102 HCC patients treated with SIRT between 2018 and 2020. RECIST, mRECIST, and LR-TRA were assessed at 3 months post-SIRT. Overall survival (OS) and progression-free survival (PFS) were assessed using Kaplan-Meier analysis and Cox proportional-hazards models.</p><p><strong>Results: </strong>The median age was 71 years, and most patients (90%) had advanced-stage tumors (Barcelona Clinic Liver Cancer-C). After a median follow-up of 32.0 months (95% CI: 16.8-60.9), 60/102 patients died (59%), and 90/102 patients showed tumor progression (88%). Median OS was 20.4 months (95% CI: 15.4-33.0), and median PFS was 14.5 months (95% CI: 6.5-24.5); 1-year OS and PFS rates were 65.6% and 50.7%. Multivariable analysis revealed that early response according to RECIST 1.1 (HR 1.66, p = 0.30), mRECIST (HR 1.40, p = 0.215), and LR-TRA (HR 0.67, p = 0.30) were not predictors of OS. Disease progression evaluated by RECIST (HR 2.55, p < 0.001) and mRECIST (HR 2.53, p < 0.001), bilirubin levels (HR 1.03, p < 0.001), and prothrombin time (HR 0.98, p = 0.005) were predictors of OS. For PFS, neither RECIST nor mRECIST response, disease progression, nor LR-TRA viability were predictors.</p><p><strong>Conclusion: </strong>In this advanced-stage HCC population, early response assessed by RECIST, mRECIST, and LR-TRA criteria did not predict OS or PFS after SIRT. However, early disease progression and liver function indicators were prognostic factors for OS.</p><p><strong>Key points: </strong>QuestionHow well does early tumor response, assessed at 3 months post-selective internal radiation therapy (SIRT), predict survival in advanced hepatocellular carcinoma (HCC) patients? Findings Early response, assessed by RECIST, mRECIST, and LR-TRA, did not predict overall or progression-free survival; disease progression and liver function indicators were significant predictors. Clinical relevance This study highlights the limitations of early imaging criteria in predicting survival outcomes in advanced HCC post-SIRT, suggesting the need for alternative or complementary prognostic indicators to guide treatment decisions.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"3181-3191"},"PeriodicalIF":4.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142863806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}