Cancer Imaging最新文献

{"title":"Patient understanding of AI-simplified oncology imaging reports requires further validation.","authors":"Wei Wei, Changyu Du, Jiageng Shen","doi":"10.1186/s40644-026-01091-z","DOIUrl":"10.1186/s40644-026-01091-z","url":null,"abstract":"<p><p>Ribeiro and colleagues offer timely evidence that large language models can make oncology imaging reports more accessible to radiologists and patient and public involvement representatives. Their findings also highlight an important distinction between a report that is easier to read and one that patients understand accurately. As the authors acknowledge, the patient-facing assessment included three representatives with previous experience in oncology imaging research and was restricted to reports that had received high factual-correctness scores from radiologists. This approach was suitable for comparing presentation preferences, although it provides limited evidence about comprehension in routine practice, particularly for lower-scoring or clinically ambiguous outputs. Further studies could examine unselected reports in patients with varied health and digital literacy, using outcomes such as comprehension, recognition of uncertainty, emotional response, and intended action. In future adequately powered studies, accounting for ratings clustered by reader and report may provide more precise estimates. Such evidence would help clarify the role of AI-generated explanations in patient-facing oncology care.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"26 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13366811/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148435153","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":"Development and multicohort external validation of a preoperative [18F]PSMA-1007 PET-derived deep learning score and multimodal model for predicting biochemical recurrence-free survival after radical prostatectomy.","authors":"Tiancheng Li, Nina Xu, Xiaofang Yan, Guolin Wang, Zhenfeng Liu, Yinuo Liu, Kui Zhao, Xinhui Su","doi":"10.1186/s40644-026-01090-0","DOIUrl":"10.1186/s40644-026-01090-0","url":null,"abstract":"<p><strong>Purpose: </strong>To develop and validate a preoperative [18F]PSMA-1007 PET-derived deep learning score (DLS) and an integrated model combining DLS, D'Amico risk classification, and SUVmax for predicting biochemical recurrence-free survival (BRFS) after radical prostatectomy (RP).</p><p><strong>Materials and methods: </strong>This retrospective study included 697 patients with prostate cancer who underwent preoperative [18F]PSMA-1007 PET/CT before RP at three campuses within one healthcare network: Qingchun (training cohort, n = 445), Yuhang (validation cohort 1, n = 190), and Zhijiang (validation cohort 2, n = 62). Five convolutional neural networks were trained to predict 3-year biochemical recurrence from PET images, and the output of the best-performing network was defined as the DLS. Four preoperative prognostic models were evaluated: DLS alone, D'Amico classification alone, D'Amico plus SUVmax, and D'Amico plus SUVmax plus DLS. Performance was assessed using Harrell's C-index, inverse-probability-of-censoring-weighted time-dependent AUC, calibration, decision curve analysis, and nested model comparisons.</p><p><strong>Results: </strong>VGG19 showed the best fixed-time classification performance, with 3-year ROC AUCs of 0.834, 0.755, and 0.723 in the training and two validation cohorts, respectively. A higher DLS was associated with shorter BRFS in all cohorts. Biopsy ISUP Grade Group was significantly associated with BRFS (global P < 0.001). In multivariable analysis, intermediate- and high-risk D'Amico groups, SUVmax, and DLS were independently associated with BRFS. The integrated model achieved C-indices of 0.846, 0.806, and 0.774 and 36-month AUCs of 0.853, 0.801, and 0.779 in the training and two validation cohorts, respectively, outperforming D'Amico classification alone and D'Amico plus SUVmax.</p><p><strong>Conclusion: </strong>A fully preoperative model integrating an [18F]PSMA-1007 PET-derived DLS with D'Amico risk classification and SUVmax improved prediction of BRFS after RP. The model may support preoperative risk counseling and postoperative surveillance planning.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13487932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148418996","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":"Elastography for distinguishing lymphoma from benign and metastatic lymphadenopathy: a systematic review and Bayesian meta-analysis.","authors":"Fatemeh Mahdavi Sabet, Shayan Forghani, Amirhossein Shahsavand, Mohammadamin Kharaghani, Reza Samiee, Fahimeh Zeinalkhani, Elham Neshan","doi":"10.1186/s40644-026-01089-7","DOIUrl":"10.1186/s40644-026-01089-7","url":null,"abstract":"<p><strong>Background: </strong>Differentiating lymphoma from benign and metastatic lymphadenopathies using conventional ultrasound remains clinically challenging. Despite the utility of ultrasound elastography in assessing tissue stiffness, the intermediate stiffness profile of lymphoma frequently leads to misclassification. To address this diagnostic gap, we conducted a comprehensive systematic review and Bayesian diagnostic meta-analysis to evaluate the performance of various elastography modalities.</p><p><strong>Methods: </strong>Following PRISMA 2020 guidelines (PROSPERO: CRD420251184980), we systematically searched PubMed, Embase, Web of Science, and the Cochrane Library. Original studies evaluating elastography against valid reference standards were included, and methodological quality was assessed using the QUADAS-2 tool. Diagnostic performance was synthesized via a robust two-tiered Bayesian bivariate hierarchical random-effects model to calculate pooled sensitivity, specificity, diagnostic odds ratios (DOR), and likelihood ratios (PLR/NLR) for both overall and modality-specific analyses.</p><p><strong>Results: </strong>Twenty studies encompassing 2,342 patients and 2,626 superficial lymph nodes (981 benign, 895 lymphoma, 750 metastatic) were included. In differentiating lymphoma from benign lymphadenopathy, Shear Wave Velocity (SWV) exhibited the highest sensitivity (0.913) and lowest negative likelihood ratio (NLR, 0.117). Conversely, aggregated Strain Elastography (SE) scoring achieved the highest specificity (0.909) and positive likelihood ratio (PLR, 7.59). When distinguishing lymphoma from metastatic nodes, Virtual Touch Tissue Imaging (VTI) techniques demonstrated robust diagnostic yield for identifying lymphoma; specifically, the VTI ratio achieved the highest diagnostic odds ratio (DOR, 39.4), with a sensitivity of 0.92 and an NLR of 0.11.</p><p><strong>Conclusion: </strong>Ultrasound elastography provides significant modality-specific diagnostic value for stratifying lymphadenopathy. SWV effectively excludes lymphoma from benign nodes, whereas SE scoring optimizes its confirmation. Furthermore, VTI techniques robustly distinguish lymphoma from metastasis. However, given substantial inter-study heterogeneity, elastography should be integrated as a complementary multiparametric adjunct to guide biopsy triage, rather than replace definitive histopathological evaluation.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13644051/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148418939","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":"When PSMA is not enough: the diagnostic blind spots of PSMA PET/CT and the added value of [¹⁸F]FDG in high-risk prostate cancer: dual-tracer cohort study.","authors":"Efrah Ahmed Ibrahim, Eray Alper","doi":"10.1186/s40644-026-01084-y","DOIUrl":"10.1186/s40644-026-01084-y","url":null,"abstract":"<p><strong>Purpose: </strong>PSMA PET/CT has transformed prostate cancer management, yet its diagnostic utility is not absolute. It fails to detect PSMA-suppressed disease variants, including treatment-induced neuroendocrine prostate cancer (t-NEPC) and dedifferentiated tumors, and is inherently blind to second primary malignancies (SPMs). This study evaluated the additional diagnostic yield and direct clinical impact of incorporating [¹⁸F]FDG PET/CT into a systematic, indication-driven dual-tracer protocol in high-risk prostate cancer patients.</p><p><strong>Methods: </strong>In this retrospective, STROBE-compliant, single-center cohort study, 82 patients with histologically confirmed prostate cancer who underwent both [⁶⁸Ga]Ga-PSMA-11 and [¹⁸F]FDG PET/CT were analyzed. Clinical indications encompassed suspected SPM, suspected dedifferentiation or t-NEPC, initial staging of very high-risk disease, pre-[¹⁷⁷Lu]Lu-PSMA therapy evaluation, and equivocal PSMA findings. The primary endpoint was the proportion of patients in whom [¹⁸F]FDG PET/CT provided additional diagnostic information. Secondary endpoints included concordance analysis and the rate of management changes.</p><p><strong>Results: </strong>Median age was 72 years (IQR 65-75). [⁶⁸Ga]Ga-PSMA-11 demonstrated superior prostate cancer detection compared to [¹⁸F]FDG (70.7% vs. 25.6%; McNemar's p < 0.0001). However, [¹⁸F]FDG PET/CT provided clinically critical additional information and directly altered management in 51.2% of patients (95% CI: 40.6-61.7%). The most impactful contributions were histopathologically confirmed SPM detection (30.5%, predominantly lung and colorectal adenocarcinomas) and identification of PSMA-negative/FDG-positive discordant disease signaling dedifferentiation. No significant correlation was found between PSMA and FDG SUVmax values (Spearman rho = 0.149, p = 0.422), underscoring their biologically distinct and complementary targets.</p><p><strong>Conclusion: </strong>[¹⁸F]FDG PET/CT is not a redundant adjunct to PSMA imaging; it fills a critical diagnostic blind spot. When applied through an indication-driven framework, dual-tracer imaging directly reshapes clinical decision-making in more than half of selected high-risk prostate cancer patients, enabling detection of occult malignancies and guiding pivotal treatment decisions that PSMA PET/CT alone cannot support.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13599307/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148374777","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":"Evaluation of audiovisual and auditory interventions on exam anxiety during whole-body magnetic resonance imaging in cancer patients: a quasi-experimental study.","authors":"Lorenzo Conti, Paul Summers, Marta Mainetti, Sara Gandini, Cristiana Fodor, Giuseppe Petralia, Gabriella Pravettoni","doi":"10.1186/s40644-026-01060-6","DOIUrl":"10.1186/s40644-026-01060-6","url":null,"abstract":"<p><strong>Background: </strong>WB-MRI is a radiation-free imaging technique widely used in oncology. Despite clinical advantages, WB-MRI can cause significant patient anxiety and claustrophobia, affecting scan completion and patient adherence. Non-invasive interventions to reduce MRI-related distress are still limited in clinical practice. This study evaluates the use of audiovisual and auditory entertainment for reducing anxiety during WB-MRI.</p><p><strong>Methods: </strong>In this prospective, quasi-experimental trial, 213 cancer patients (median age: 52.0[44-60]; female 70%) undergoing WB-MRI were equally assigned to Video (nature landscapes and sounds), Music (relaxing instrumental), or Standard (no distraction) groups. Anxiety was assessed using the State Trait Anxiety Inventory (STAI) before and after the exam. Additional measures included the Distress Thermometer, WB-MRI acceptance questionnaire, and claustrophobia ratings. Data analysis compared anxiety changes, interactions between baseline anxiety and claustrophobia, and logistic regression for anxiety reduction likelihood.</p><p><strong>Results: </strong>Baseline anxiety was comparable across groups. Anxiety reduction was greater in the Video (mean STAI = -5.57) and Music (-2.48) groups compared to the Standard (0.33) group, with the Video group significantly outperforming the Music group (p = 0.006). Logistic regression showed patients in Video (95%CI:3.77-68.22, p < 0.001) and Music (95%CI:1.47-29.8, p = 0.02) groups were significantly more likely to reduce anxiety than controls. Patients with severe claustrophobia and high baseline STAI exhibited pronounced improvements, particularly with Video (β = - 0.38, p < 0.001). The alluvial plot shows that the Video and Music groups experienced a marked reduction in the proportion of patients with severe anxiety, while this proportion slightly increased in the standard condition after the exam.</p><p><strong>Conclusion: </strong>Audiovisual and auditory entertainment significantly reduced anxiety during WB-MRI, with audiovisual showing the greatest benefit. The simultaneous involvement of multisensory distraction enhances tolerance to procedures, especially in highly anxious and claustrophobic patients. These findings advocate for the adoption of a patient-centered audiovisual system as a non-invasive, practical strategy to enhance patient experience and increase the likelihood of successful scan completion in WB-MRI practice. The results hold significant implications for optimizing patient compliance, offering tangible clinical and economic benefits, including reduced sedation requirements, prevention of long-term phobic responses, minimized motion artifacts, and improved image quality.</p><p><strong>Trial registration: </strong>Retrospectively registered on ClinicalTrials.gov NCT06332001 [first posted March 26, 2024].</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13591891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148367198","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":"Predictive imaging biomarkers on whole-body diffusion-weighted MRI (WB-DWMRI) and [⁶⁸Ga]GaPSMA-PET/CT for [¹⁷⁷Lu]LuPSMA therapy in metastatic prostate cancer (mCRPC).","authors":"Minal Padden-Modi, Jan Taprogge, Peter Dutey-Magni, Carolina G S Cauduro, Matthew D Blackledge, Hoda Abdel-Aty, Iain Murray, Nabil Hujairi, Nina Tunariu, Nick James","doi":"10.1186/s40644-026-01066-0","DOIUrl":"10.1186/s40644-026-01066-0","url":null,"abstract":"<p><strong>Background: </strong>This study evaluates the utility of quantitative imaging biomarkers derived from whole-body diffusion-weighted MRI (WB-DWMRI) and [⁶⁸Ga]GaPSMA-PET/CT in predicting lesion-level response to [¹⁷⁷Lu]LuPSMA therapy in metastatic castration-resistant prostate cancer (mCRPC).</p><p><strong>Methods: </strong>Twenty-two patients with mCRPC who underwent WB-DWMRI and [⁶⁸Ga]GaPSMA-PET/CT within three months before [¹⁷⁷Lu]LuPSMA therapy were identified. The PSMA SUV (SUV_mean, SUV_SD, SUV_peak) and corresponding diffusion weighted imaging (DWI) parameters (ADC_mean, ADC_kurtosis, ADC_vol) were extracted from five hottest lesions (highest SUV_mean) on PSMA-PET/CT. Lesion response was assessed using modified PERCIST and MET-RADS-P criteria. Multilevel logistic regression and area under receiver operating characteristic (AUROC) analyses identified predictive biomarkers.</p><p><strong>Results: </strong>65 bone lesions and 30 lymph nodes were analysed pre- and post-therapy. Forty-four (68%) bone and 16 (53%) lymph nodes lesions responded to treatment. SUV_mean and SUV_peak were almost identical (rank-correlation = 0.97) and had high predictive performance for response with AUROC of 0.74 (95% CI: 0.62-0.86) and 0.75 (95% CI: 0.61-0.88) respectively. Lesion volume showed good performance (AUROC = 0.69, 95% CI 0.57-0.82) and moderately correlated with SUV_mean (rank-correlation = 0.43). Neither ADC_mean (AUROC = 0.45, p = 0.47) or ADC_kurtosis (AUROC = 0.49, p = 0.171) were predictive. On regression modelling, a 1-unit volume increase, raised response odds by 4.3 (95% CI 0.7-27) in bone lesions, and 6.2 (95% CI 0.6-67) in lymph nodes (p = 0.06). A 1-unit SUV_mean increase raised response odds by 1.5 (95% CI 1.1-2.0) in bone lesions and 1.2 (95% CI 1.0-1.4) in lymph nodes (p < 0.01). No evidence suggested combining volume with SUVmean enhanced predictive performance over SUV_mean alone (p = 0.58).</p><p><strong>Conclusions: </strong>Baseline PSMA SUV_mean, SUV_peak, and volume are promising predictive biomarkers for lesion-level response to [¹⁷⁷Lu]LuPSMA therapy. Combining functional and structural imaging biomarkers could improve treatment stratification and response assessment. Further validation in larger studies, alongside patient-level analysis, and expansion beyond the five lesions is needed to refine predictive models for clinical application.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13330063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148359665","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":"Correction to: [¹⁸F]PSMA-1007 and [¹⁸F]FDG PET/CT in patients with metastatic triple-negative breast cancer: a prospective head-to-head comparison and assessment of PSMA-targeted radioligand therapy applicability.","authors":"Tatiana Nikolaevna Lazutina, Aleksandr Igorevich Khalimon, Soslan Rolanovich Urtaev, Malika Maratovna Khodzhibekova, Daria Yurevna Khodakova, Gulnara Faridovna Khamadeeva, Anastasia Igorevna Nikiforuk, Irina Valentinovna Pylova, Aleksei Victorovich Leontev, Andrey Dmitrievich Kaprin","doi":"10.1186/s40644-026-01071-3","DOIUrl":"10.1186/s40644-026-01071-3","url":null,"abstract":"","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":"26 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13317341/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148359707","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":"Survival prediction of ¹⁸F-FDG PET/CT in pediatric patients with recurrent neuroblastoma.","authors":"Wenfang Tang, Zhonglin Liang, Chao Li, Yafu Yin, Hui Wang, Jinglue Song, Suyun Chen","doi":"10.1186/s40644-026-01085-x","DOIUrl":"10.1186/s40644-026-01085-x","url":null,"abstract":"<p><strong>Purpose: </strong>Our study aims to investigate the predictive potential of FDG PET/CT in pediatric patients with NB at the time of recurrence.</p><p><strong>Methods: </strong>Pediatric patients with suspected recurrence of NB underwent FDG PET/CT were included in this retrospective study. The clinicopathological data, PET visual analysis data and semiquantitative values (maximum standardized uptake value (SUVmax) of tumor, tumor-to-liver uptake ratio (TLR), metabolic tumor volume (MTV), total lesion glycolysis (TLG)), were analyzed. The Kaplan-Meier curves and Cox proportional hazard models were applied in the evaluation of the independent prognostic significance of FDG PET/CT.</p><p><strong>Results: </strong>A total of 45 NB patients who underwent FDG PET/CT due to suspected recurrence of NB and got later confirmation of recurrence clinically or pathologically were included in this retrospective study. Among the PET/CT parameters, recurrent primary site TLR cutoff at 5.64 and SUVmax cutoff at 4.10 derived from the receiver operating characteristic curve yielded significant difference (TLR HR = 2.692, p = 0.014; SUVmax HR = 7.698, 0.045) in overall survival (OS). Besides, INSS stage 4, the time from diagnosis to first relapse (TTFR) and recurrence interval were related with shorter survival time in the four established multivariate Cox regression models.</p><p><strong>Conclusion: </strong>FDG PET/CT showed great survival predictable performance in recurrent NB. SUVmax, TLR, INSS stage 4, TTFR and recurrence interval were independent risk factors for overall survival.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13591894/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148359631","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":"MRI-based perfusion-diffusion habitat analysis for characterizing intratumoral heterogeneity in rectal adenocarcinoma.","authors":"Cui Tang, Jingwen Zhang, Jie Kuang, Wenying Mou, Hua Hao, Dongmei Wu, Yongming Dai","doi":"10.1186/s40644-026-01081-1","DOIUrl":"10.1186/s40644-026-01081-1","url":null,"abstract":"<p><strong>Background: </strong>This study aimed to evaluate whether MRI-based perfusion-diffusion habitat imaging derived from dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) can characterize intratumoral heterogeneity and evaluate associations with pathologic stage, synchronous distant metastasis, and exploratory survival outcomes in rectal adenocarcinoma.</p><p><strong>Methods: </strong>This retrospective study included 73 patients with pathologically confirmed rectal adenocarcinoma who underwent preoperative DCE-MRI and DWI scans. The volume transfer constant (Ktrans) and apparent diffusion coefficient (ADC) maps were generated from DCE and DWI data, respectively. After manual tumor segmentation and image co-registration, voxel-wise Ktrans and ADC values were clustered using a k-means algorithm to identify distinct spatial habitats. Quantitative metrics extracted from each habitat were compared across pathologic subgroups and entered into multivariable logistic regression models for T staging and association with synchronous distant metastasis.</p><p><strong>Results: </strong>Three reproducible habitats were identified: Habitat 1, hyper-vasopermeability; Habitat 2, hypo-vasopermeability with hypo-cellularity; and Habitat 3, hypo-vasopermeability with hyper-cellularity. Compared with T1-2 tumors, T3-4 lesions showed significantly higher mean Ktrans and the extracellular-extravascular volume fraction (Ve) in Habitats 1 and 2 and lower mean ADC in Habitats 2 and 3. Multiple perfusion metrics from Habitat 1 significantly correlated with distant metastasis. The optimized logistic regression models achieved AUCs of 0.81 for T staging and 0.78 for distant metastasis prediction.</p><p><strong>Conclusion: </strong>Combined DCE-MRI and DWI habitat imaging enables voxel-level assessment of intratumoral heterogeneity in rectal cancer and may provide a noninvasive imaging biomarker for preoperative T staging and assessment of tumor heterogeneity and systemic disease-associated imaging features.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13587470/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148359624","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":"Can brain-to-tumour outer interface radiomics improve the efficiency of MRI in predicting the brain invasion of meningiomas?","authors":"Zongmeng Wang, Dingfu Wei, Weiwei Xia, Ye Li, Xiaofang Zhou, Mingwei Sun, Sihui Liu, Haixia Li, Yang Song, Jie Wu, Yuting Chen, Yunjing Xue, Lin Lin","doi":"10.1186/s40644-026-01078-w","DOIUrl":"10.1186/s40644-026-01078-w","url":null,"abstract":"<p><strong>Background: </strong>Brain invasion serves as an independent diagnostic criterion for the diagnosis of WHO grade 2 meningiomas. This study aimed to evaluate the value of radiomic models constructed with features extracted from different regions of the brain-to-tumor interface to predict potential brain invasion of meningiomas.</p><p><strong>Methods: </strong>The cohort of this retrospective multicenter study included 915 consecutive patients from three centers with histopathologically confirmed meningiomas. Brain invasion status was determined separately using predefined criteria based primarily on histopathological findings, with operative records used as supplementary information. Nine radiomic models were developed using radiomic features extracted from nine different regions of interest: 3-5 mm regions of the brain-to-tumor interface (BTI), brain-to-tumor inner interface (BTII), and brain-to-tumor outer interface (BTOI). The features were derived from T1W, T2-FLAIR, and CE-T1W images. A logistic regression classifier was trained for model development. Model discrimination was evaluated via receiver operating characteristic (ROC) analysis, while clinical utility and incremental predictive value were quantified using decision curve analysis (DCA) and the integrated discrimination improvement (IDI) index.</p><p><strong>Results: </strong>As compared to models constructed with features from the 3-5 mm BTII and BTI regions, the BTOI radiomic models demonstrated enhanced predictive capability for meningioma brain invasion. The area under the curve (AUC) values for the 3-, 4-, and 5-mm BTOI models were 0.845, 0.845, and 0.905 with the test cohort, and 0.818, 0.825, and 0.874 with the external validation cohort, respectively. DCA confirmed the clinical superiority of the BTOI models, which provided the highest net benefit across various threshold probabilities. Moreover, the IDI index indicated that the BTOI features offered statistically significant incremental value for invasion risk stratification as compared to the BTII and BTI models (p < 0.05).</p><p><strong>Conclusions: </strong>The BTOI radiomic models demonstrated superior performance in predicting brain invasion in meningiomas compared with models constructed from the BTI and BTII regions. These findings suggest that the peritumoral brain tissue adjacent to the tumor may contain particularly informative imaging characteristics related to invasion and provide imaging-based support for optimizing ROI delineation.</p>","PeriodicalId":9548,"journal":{"name":"Cancer Imaging","volume":" ","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13663188/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148350894","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}