Cancer-associated fibroblasts (CAFs) are influential elements of the tumor microenvironment with significant roles in tumor progression and therapy resistance. However, the effects that radiotherapy has on CAFs dynamics remain understudied. This study aimed to provide a non-invasive PET imaging approach to quantify radiation-induced changes in cancer-associated fibroblasts in preclinical tumor models. The FAP-specific radiotracer [18F]AlF-FAPI-74 was used to monitor CAFs dynamics following precision external beam radiotherapy (RT) in two syngeneic subcutaneous murine tumor models (LLC and CT26). Tumors were irradiated via two radiation regimens (1 × 12 Gy or 2 × 6 Gy), and dynamic PET/MR imaging was performed 7 days after RT. Additionally, the dynamics of FAP+ CAFs in tumors were quantified ex vivo via flow cytometry and immunohistochemistry. Tumor-targeted irradiation led to a significant reduction in tumor size. Uptake of [18F]AlF-FAPI-74 in subcutaneous tumors was low but significantly above muscle-background values. Quantification of standardized uptake values (SUVs) from static PET images revealed a twofold increase in the PET signal in LLC tumors irradiated with two fractions of medium-dose RT (2 × 6 Gy). Ex vivo analysis confirmed the low abundance of FAP+ cells in tumors and demonstrated similar RT-induced changes in CAF levels across the different models. Our findings suggest that CAFs constitute a relatively small cell population in subcutaneously transplanted tumor models, and that fractionated radiotherapy may induce a moderate increase in FAP+ cells in LLC tumors. Additionally, we demonstrated that [18F]AlF-FAPI-74 is a reliable biomarker for evaluating the number of FAP+ stromal cells in tumors and for addressing potential therapy-induced changes in CAFs.

BackgroundTo develop and validate a CT–based artificial intelligence (AI) score model integrating the R.E.N.A.L. nephrometry and contact surface area (CSA) for efficient, accurate prediction of perioperative outcomes in renal cell carcinoma (RCC) patients undergoing nephron–sparing surgery (NSS), addressing the subjectivity and inefficiency of manual score.MethodsRetrospectively collected data from two NSS cohorts (n1 = 500, n2 = 50): 90% of cases in Cohort n1 (450 cases) were randomly assigned to the training set (315 cases), validation set (45 cases), and test set (90 cases) at a ratio of 7:1:2, which were used to develop and validate the automated kidney/tumor segmentation models, as well as to derive the AI-calculated R.E.N.A.L. score (with the “A” parameter excluded) and AI-calculated CSA score; the remaining 10% of cases in Cohort n1 (50 cases) were combined with all 50 cases in Cohort n2 to form a mixed validation set (100 cases), which was used for risk stratification prediction of NSS perioperative outcomes via AI scores. Manual image annotation/scoring was conducted by experienced radiologists and urologists. Interrater consistency was evaluated via weighted kappa coefficients; risk stratification was performed via Kruskal–Wallis tests and Mann–Whitney U tests.ResultsA total of 550 patients were included in this study (median age, 56 [IQR: 46–66] years; 341 males). The segmentation model exhibited excellent performance: Dice similarity coefficient (DSC) was 0.95 for kidneys and 0.80 for tumors; normalized surface distance (NSD) was 0.923 ± 0.082 and 0.892 ± 0.096, respectively; 95th percentile Hausdorff distance (HD95) was 9.78 ± 0.63 mm and 12.65 ± 0.84 mm, respectively. The R, E, N, L, R.E.N.A.L., and CSA score models had good consistency compared with the manual score, and the kappa coefficients were 0.82, 0.49, 0.63, 0.60, 0.65, and 0.69, respectively (all P < 0.01). Risk stratification by AI score significantly predicted warm ischemia time, surgical duration, intraoperative blood loss, serum creatinine changes, pathological T stage, and nuclear grade (all P < 0.05).ConclusionsThis study successfully developed a CT-based automated kidney/tumor segmentation model, and on this basis constructed the AI-R.E.N.A.L. and AI-CSA scoring models, providing an efficient and objective preoperative risk assessment tool for the perioperative outcomes of NSS.Supplementary InformationThe online version contains supplementary material available at 10.1186/s40644-025-00961-2.

BackgroundWith the advancements in imaging technologies and the widespread use of magnetic resonance imaging (MRI), the detection rates of pancreatic cystic lesions (PCLs) have significantly increased. While most of these lesions are benign, branch-duct intraductal papillary mucinous neoplasms (BD-IPMNs) pose a potential risk for malignant transformation, necessitating regular clinical and radiological follow-up. However, conventional MRI protocols are time-consuming and resource-intensive, prompting the need for shorter, cost-effective alternatives without compromising diagnostic accuracy. This study aims to evaluate the diagnostic performance and clinical feasibility of abbreviated MRI (A-MRI) protocols for BD-IPMN surveillance compared to standard MRI (S-MRI).MethodsThis was a single-center, retrospective study including patients with BD-IPMN who underwent follow-up MRI between January 2022 and December 2024. Three MRI protocols were analyzed: (1) S-MRI, comprising T2-weighted imaging, dynamic contrast-enhanced (DCE) T1-weighted imaging, 3D MR cholangiopancreatography (MRCP), and diffusion-weighted imaging (DWI); (2) A-MRI protocol 1 (A-MRI-1), including MRCP and T2-weighted sequences; and (3) A-MRI protocol 2 (A-MRI-2), incorporating MRCP, T2-weighted, and DWI sequences. The images were evaluated for lesion size progression (≥ 5 mm in 2 years), mural nodules, cyst wall thickening, main pancreatic duct dilation, and parenchymal atrophy. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for A-MRI protocols in detecting degeneration signs.ResultsA total of 124 patients (mean age: 64 years, 55.6% female) and 124 lesions were analyzed. The detection rates of key degeneration markers were similar between S-MRI and A-MRI protocols, except for contrast-enhanced mural nodules, which were not identifiable with A-MRI due to the lack of DCE sequences. The overall sensitivity, specificity, PPV, and NPV for A-MRI in detecting BD-IPMN degeneration markers were 100%, 98.3%, 71.4%, and 100%, respectively. A-MRI protocols demonstrated a comparable diagnostic performance to S-MRI while significantly reducing scan time (from ~ 40–50 min to 7–12 min). However, false-positive mural nodule detection was higher with A-MRI, potentially leading to unnecessary follow-up imaging. The addition of DWI in A-MRI-2 did not provide a significant diagnostic advantage over A-MRI-1.ConclusionsA-MRI is a viable alternative for BD-IPMN follow-up, offering substantial reductions in imaging duration and costs while maintaining high diagnostic accuracy. However, the absence of DCE sequences may lead to false-positive mural nodule detection, necessitating further evaluation in selected cases.

BackgroundHigh-spatial-resolution T2-weighted imaging (HR-T2WI) has been demonstrated to overestimate the staging of early rectal cancer, which could lead to missed opportunities for organ-preserving treatments. This study aimed to investigate the value of diffusion kurtosis imaging (DKI) in distinguishing between T0-T1 and T2 rectal tumors.MethodsA total of 138 patients with pathologically confirmed T0-T2 rectal tumors who underwent surgery between 2018 and 2023 were included. The pathological findings on tumor staging obtained from surgical specimens were used as the reference standard. The depth of tumor invasion was assessed using HR-T2WI. Kurtosis and diffusivity from DKI and apparent diffusion coefficient (ADC) from diffusion-weighted imaging were measured for the entire tumor. Diffusion parameters were compared between pT0-T1 and pT2 tumors. Multivariable logistic regression and receiver operating characteristic curve analyses were conducted to evaluate the diagnostic performance of significant individual parameters and their combinations in determining pT0-T1 tumors.ResultsKurtosis was lower in pT0-T1 than in pT2 rectal tumors (0.799 vs. 0.950, P < 0.001), while diffusivity and ADC were higher than those of pT2 rectal cancer (1.732 × 10−3 mm2/s vs. 1.368 × 10−3 mm2/s, P < 0.001; 1.316 × 10−3 mm2/s vs. 1.043 × 10−3 mm2/s, P < 0.001). Diffusivity demonstrated the highest diagnostic efficacy in differentiating pT0-T1 from pT2 rectal tumors, with an AUC of 0.810, which was higher that of HR-T2WI (AUC = 0.752, P < 0.001) and kurtosis (AUC = 0.729, P = 0.007), but showed no difference compared to ADC (AUC = 0.785, P = 0.087). A multivariable logistic regression model incorporating HR-T2WI and diffusivity improved diagnostic performance compared with all other individual parameters, achieving an AUC of 0.885 (all P < 0.05).ConclusionThe combination of HR-T2WI and diffusivity can effectively detect pT0-T1 rectal tumors. HR-T2WI combined with diffusivity derived from DKI may serve as a potential biomarker for early assessment of rectal tumors, offering valuable insights for selecting suitable candidates for organ-preserving surgery.Supplementary InformationThe online version contains supplementary material available at 10.1186/s40644-025-00947-0.

BackgroundLymphovascular invasion (LVI) status in rectal cancer (RC) without lymph node metastasis (LNM) can significantly influence the patient’s treatment decisions. This study aims to develop and validate a combined model based on MRI radiomics features integrated with clinical immune-inflammatory biomarkers for the prediction of LVI status in RC without LNM. The Shapley Additive Explanation (SHAP) method was employed to visualize the prediction process and enhance interpretability for clinical application.MethodsWe retrospectively collected data from 257 RC patients without LNM from two centers. Univariate and multivariate logistic regression analyses were performed on clinical data to identify independent predictors of LVI. Volumes of interest were manually delineated on T2WI and ADC sequences, and corresponding radiomic features were extracted. A combined model was constructed by combining rad-score and clinical immune-inflammatory biomarkers, and the SHAP was used to visualize the prediction process.ResultsThe area under the curve (AUC) of the combined model was based on intratumoral features (training vs. testing vs. validation datasets: 0.813 vs. 0.854 vs. 0.807). The AUC of the combined model was based on both intra- and peritumoral features (training vs. testing vs. validation datasets: 0.855 vs. 0.841 vs. 0.860). After comparison, the combined model (C + Q) based on intra- and peritumoral MRI radiomics features integrated with clinical immune-inflammatory biomarkers demonstrated better predictive performance.ConclusionThe combined model (C + Q) has great potential in the non-invasive prediction of LVI in RC without LNM, providing a basis for stratified management and individualized treatment decisions for RC patients.Supplementary InformationThe online version contains supplementary material available at 10.1186/s40644-025-00946-1.

ObjectiveTo investigate the characteristics of pregnancy associated breast cancer (PABC) and correlation of parity with ultrasonic tumor and background echotexture, based on the analysis of diagnostic efficiency.MethodsThe ultrasonic images of 184 female patients with PABC and 47 female patients with benign lesions, all of whom were pregnant or within one year postpartum at diagnosis and underwent surgery for their breast conditions in our center from January 2016 to December 2023, were retrospectively analyzed. Ultrasound diagnostic performance was assessed by the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUROC). Breast ultrasound background echotexture was classified according to two criteria: the first classification was homogeneous-fat, homogeneous-fibroglandular, and heterogeneous, the other classification was hypoechoic dominated and hyperechoic dominated. The correlation between parity and ultrasonic characteristics (tumor and background echotexture) was analyzed.ResultsThe AUROC of ultrasound diagnosis for PABC was 0.939 (95%CI: 0.910-0.969). PABC tumors were predominantly irregular in shape, uncircumscribed, hypoechoic, heterogeneous, and solid. Compared with primiparous women, the PABC tumors were larger in multiparous women (4.00± 3.30cm vs. 3.09 ± 2.01cm, P = 0.037), with a higher rate of lymphatic metastasis (57.27% vs. 41.89%, P = 0.041). In terms of background echotexture, heterogeneous echotexture and hypoechoic dominated were more frequently observed in multiparas than in primiparas (52.73% vs. 37.84%, P= 0.047; 49.09% vs. 32.43%, P = 0.025). Multivariate analysis further indicated multiparous women were more likely to have heterogeneous (OR = 2.241, 95% CI:1.032-4.867, P= 0.041) and hypoechoic dominated (OR = 2.064, 95% CI:1.045-4.077, P = 0.037) breast ultrasound backgrounds than primiparous women, adjusted for confounders.ConclusionsUltrasound is effective for diagnosing PABC. Multiparas may show a more heterogeneous and predominantly hypoechoic background echotexture, an increased risk of lymphatic metastasis, and larger tumors. Graphical

BackgroundTo develop a predictive nomogram for differentiating pancreatic cancer from periampullary non-pancreatic cancers based on computed tomography (CT) imaging features.MethodsThis retrospective study included 171 patients diagnosed with periampullary carcinoma (90 pancreatic cancer and 81 non-pancreatic cancer). Variables assessed included CT imaging features along with relevant clinical data. Statistically significant variables were identified through multivariable logistic regression analysis, and a predictive nomogram was developed and internally validated based on these factors.ResultsMultivariable analysis identified the following independent risk factors: the distance from the distal end of the dilated pancreatic duct to the medial wall of the papilla (DPDP) (odds ratio [OR] 8.76, P < 0.05), the distance from the distal end of the dilated bile duct to the medial wall of the papilla (DBDP) (OR 31.83, P < 0.05), papillary enlargement (OR 0.03, P < 0.05), and visibility of pancreatic and/or bile ducts between the tumor and the papilla (VPBD) (OR 3.97, P < 0.05). A nomogram was constructed based on these four significant features. In both the development and validation cohorts, the nomogram demonstrated robust predictive performance, with areas under the receiver operating characteristic curve (AUCs) of 0.84 (95% CI, 0.77–0.91) and 0.81 (95% CI, 0.67–0.96), respectively.ConclusionsThis study underscores the value of CT imaging features in distinguishing pancreatic cancer from periampullary non-pancreatic cancers. The identification of key imaging markers with significant diagnostic value facilitated the development and validation of a nomogram that integrates these features, providing a more reliable tool for clinical decision-making.Supplementary InformationThe online version contains supplementary material available at 10.1186/s40644-025-00917-6.

PurposeThis study assessed the effectiveness and prognostic factors of CT-guided ¹²⁵I seed implantation for primary hepatocellular carcinoma (HCC).MethodsA retrospective analysis of 71 patients (57 males, 14 females, median age 64) treated at three Chinese hospitals from 2018 to 2024 was conducted. The main outcomes were local progression-free survival (LPFS) and overall survival (OS). Treatment involved a 16-slice Spiral CT and Radioactive Particle Treatment Planning System (TPS), with seeds of 18.5–29.6 MBq implanted via freehand puncture. Efficacy was evaluated using the modified Response Evaluation Criteria in Solid Tumors (mRECIST) at three months, with follow-ups every three months for three years, then biannually until December 2024. Data analysis utilized SPSS 22.0, Kaplan-Meier, and Cox models.ResultsWith a median follow-up of 37 months, the complete response (CR) rate was 57.7%, partial response (PR) 31.0%, stable disease (SD) 5.6%, and progressive disease (PD) 5.6%. Local control was 94.3%. LPFS rates at 1, 3, and 5 years were 74.6%, 29.5%, and 1.4% (median LPFS 22 months), while overall survival (OS) rates were 88.7%, 47.8%, and 12.6% (median OS 35 months). CR was a key protective factor for LPFS and OS. Significant factors included the Barcelona Clinic Liver Cancer (BCLC) stage C, intrahepatic progression, and extrahepatic metastasis. Postoperative complications occurred in 35.2% of patients, with no severe cases.ConclusionCT-guided ¹²⁵I seed implantation is effective and safe for primary HCC, with CR being crucial for survival. Large-scale studies are needed to confirm these results.