Technology in Cancer Research & Treatment最新文献

IntroductionAxillary nodal burden reflects the biological aggressiveness and prognostic behavior of breast cancer. This study aimed to develop a subregional habitat radiomics model based on multiparametric magnetic resonance imaging (MRI) and to evaluate its performance in predicting high axillary nodal burden in patients with breast cancer.MethodsIn this retrospective study, a total of 221 patients who underwent axillary lymph node dissection were categorized as having limited (0-2 metastatic nodes) or high (≥3 metastatic nodes) nodal burden based on pathological findings. Morphological MRI features were visually evaluated by experienced radiologists. A clinical model was established using univariate and multivariate logistic regression analyses. Conventional radiomics (C-radiomics) and habitat radiomics features were extracted from the whole tumor and its subregions, respectively, based on multiparametric MRI. The clinical, C-radiomics, and habitat radiomics models were then integrated into a comprehensive nomogram for quantitative prediction of axillary nodal burden.ResultsIn predicting axillary nodal burden, the habitat radiomics model outperformed both the C-radiomics and clinical models, achieving areas under the curve (AUCs) of 0.791 (0.712-0.870) and 0.798 (0.686-0.911) in the training and validation cohorts, respectively. The C-radiomics model achieved AUCs of 0.733 (0.631-0.836) and 0.738 (0.612-0.865), while the clinical model achieved AUCs of 0.753 (0.663-0.843) and 0.733 (0.596-0.870). The combined nomogram demonstrated the highest diagnostic performance, with AUCs of 0.895 (0.839-0.951) and 0.885 (0.802-0.969) in the training and validation cohorts, respectively.ConclusionsThe integrated nomogram combining clinical, C-radiomics, and habitat radiomics models demonstrated strong predictive efficacy for preoperative assessment of axillary nodal burden in breast cancer. Future multicenter prospective studies are warranted to validate these results and refine the model's clinical applicability.

IntroductionThis study aimed to retrospectively evaluate and compare the accuracy, complication rate, and feasibility of computed tomography (CT)-guided introducer-assisted percutaneous lung biopsy with those of freehand percutaneous lung biopsy for the diagnosis of pulmonary nodules ≤ 2 cm.MethodsWe retrospectively analysed clinical data of 307 patients with pulmonary nodules ≤ 2 cm who underwent percutaneous lung biopsy between January 2015 and August 2024. The patients were divided into two groups: A, 153 patients undergoing freehand puncture, and B, 154 patients in whom the procedure was assisted by a guidance device. A statistical analysis was performed to assess the success rate, diagnostic accuracy, and complication rate of the two techniques and to evaluate the feasibility of using a guide device-assisted puncture biopsy for small pulmonary nodules.ResultsAll 307 patients successfully completed the percutaneous biopsy procedure (100% technical success rate). Diagnostic accuracy was 95.4% and 96.8% in Groups A and B, respectively (p = .161). Groups A and B required an average of 9.04 ± 2.58 and 8.14 ± 1.72 intraoperative CT scans, respectively (p < .001). Mean procedural durations for Groups A and B were 12.77 ± 4.51 and 10.83 ± 2.51 min, respectively (p < .001). In Groups A and B, the immediate need for closed thoracic drainage was 4.6% (7/153) and 1.9% (3/154), respectively (p = .165), and incidence of haemoptysis was 10.5% (16/153) and 9.7% (15/154), respectively (p = .492). Neither group experienced complications such as air embolism or needle tract seeding metastasis.ConclusionBoth CT-guided needle biopsy performed using a guidance device and freehand biopsy demonstrated high diagnostic accuracy for pulmonary nodules ≤ 2 cm. Procedures conducted with a guidance device contributed to shorter operation times, fewer CT scans, and lower radiation exposure.

IntroductionNiraparib and bevacizumab are two principal maintenance therapies for newly diagnosed advanced ovarian cancer (AOC) patients with BRCA wild-type (BRCAwt) status, regardless of homologous recombination deficiency (HRD). In China, however, a considerable proportion of BRCAwt patients have unknown or untested HRD status, complicating treatment selection.MethodsTo evaluate and compare the efficacy of niraparib and bevacizumab as maintenance therapy for BRCAwt AOC, we conducted a retrospective cohort study using real-world clinical data. Descriptive statistics were used to summarize clinical and demographic characteristics. Progression-free survival (PFS) was estimated using Kaplan-Meier analysis and compared using a stratified Cox proportional hazards model. A multivariable Cox regression was performed to adjust for potential confounding variables. Exploratory subgroup analyses were conducted, and propensity score matching (PSM) was applied as a sensitivity analysis.ResultsA total of 94 patients were included, with 51 receiving niraparib and 43 receiving bevacizumab. The median PFS was not reached in the niraparib group versus 13.77 months (95% CI, 4.12-23.41) in the bevacizumab group (HR = 0.240, 95% CI, 0.128-0.451; P < .001). After covariate adjustment, the median PFS was 19.55 months (95% CI, 9.40-NA) with niraparib and 8.64 months (95% CI, 4.53-NA) with bevacizumab, with an adjusted HR of 0.282 (95% CI, 0.136-0.587; P = .001). In the PSM sensitivity analysis, the median PFS was not reached (95% CI, 19.55-NR) in the niraparib group and was 18.33 months (95% CI, 8.90-25.26) in the bevacizumab group (HR = 0.360, 95% CI, 0.176-0.736; P = .005).ConclusionThis analysis suggests that niraparib may provide a progression-free survival advantage compared with bevacizumab in BRCAwt AOC patients, with both regimens appearing to be generally well tolerated in the real-world setting. These findings offer preliminary reference value for maintenance treatment selection in patients with newly diagnosed BRCAwt AOC.

ObjectiveThis study aimed to assess renal cell carcinoma (RCC) complexity using the R.E.N.A.L. nephrometry score and evaluate the feasibility and safety of the non-clamping sutureless technique combined with a radiofrequency ultrasound scalpel (RFUS) for low-complexity RCC.MethodsThis retrospective, multi-center cohort study categorized patients into three groups: Group I (suture laparoscopic partial nephrectomy [LPN] with clamping renal artery), Group II (sutureless LPN without renal artery clamping, combined with monopolar electrocoagulation), and Group Ⅲ (sutureless laparoscopic nephron-sparing surgery [LNSS] without renal artery clamping combined with RFUS). Key outcomes included operative time, intraoperative blood loss, postoperative hospital stays, serum creatinine (Scr) levels, and the estimated glomerular filtration rate (eGFR) of the affected kidney. Post hoc power analysis was used to evaluate eGFR variation across groups, and a multiple linear regression model was employed to analyze factors influencing postoperative eGFR alterations.ResultsThe study included 60 patients with exophytic and low-complexity RCC. Blood loss in Group III was comparable to that in Group I but less than that in Group II (P = 0.035). Operative time and postoperative hospital stays were significantly shorter in Group III than in the other groups (P < 0.01). A statistically significant increase in Scr levels was observed during the early postoperative period, continuing through the 6-month follow-up assessment compared with preoperative levels (P < 0.01). The 6-month postoperative eGFR of the affected kidney in Group III was significantly higher than that in the other groups (P < 0.01). The decrease in preoperative and 6-month postoperative eGFR values was greatest in Group I (P < 0.01), followed closely by Group II (P < 0.01), while no significant reduction was observed in Group III. The post hoc power analysis revealed high detection power (0.912 or 1.0). Warm ischemia time emerged as the sole significant eGFR predictor (R² = 0.814, P < 0.05).ConclusionThe non-clamping sutureless technique combined with RFUS for RCC effectively alleviates renal ischemia-reperfusion injury, offering superior renal function protection while achieving comparable oncological outcomes.

ObjectiveThis work introduces MamoRef, an innovative whole-field, near infrared spectroscopy based device for adjunctive breast examination, aiming to help classify benign and malignant lesions in women. Utilizing low-power, non-ionizing red and near-infrared lasers, it provides metabolic information to aid physicians in characterizing lesions in BI-RADS II to IV patients, offering a non-invasive screening alternative.ApproachClinical studies were conducted, benchmarking MamoRef against conventional imaging and core biopsies. The device generates 2D maps of relative oxyhemoglobin, deoxyhemoglobin, and oxygen saturation. NIRS-specialized professionals, with basic clinical training, independently scored MamoRef images using a 6-point scale analog to BI-RADS. Scores were averaged and normalized for biopsy comparison.Main resultsThe studied clinical cases show promising outcomes. For neoproliferative lesions, MamoRef images reveals high deoxygenated hemoglobin and diffuse high oxygenated/total hemoglobin, suggesting neovascularization around necrotic tissue. Preliminary receiver operating characteristic analysis yielded an area under the curve of 0.77. At a 0.6 threshold, MamoRef showed 70% accuracy and 74% specificity.SignificancePreliminary results suggest MamoRef can potentially differentiate benign from malignant lesions detected by standard imaging. Trained clinicians might detect and characterize lesions using these metabolic maps. Further larger-scale studies are needed to validate these findings and improve the technology, positioning MamoRef as a potential low-cost, accessible adjunctive screening tool.

BackgroundBy integrating Digitally Reconstructed Radiograph (DRR) images of pulmonary tumors with Electronic Portal Imaging Device (EPID) images to assist in target segmentation, and subsequently comparing morphological changes in segmented targets across different radiotherapy stages, this approach enables precise quantification of dynamic variations in target volume and shape. This methodological integration provides objective evidence for treatment response evaluation and dynamic optimization of treatment plans, thereby significantly enhancing the precision of radiotherapy delivery.MethodsThe proposed multimodal segmentation framework, named EPIDSeg-Net, comprises an encoder, a multi-scale feature layer, and a decoder. The encoder utilizes a dual-branch architecture: a CNN branch for extracting local texture features and a Swin-Transformer branch for capturing global semantic features. The model first calibrates multimodal input features through a Dual Attention Mechanism (DAM) to adaptively adjust modality-specific weights, thereby enhancing tolerance to missing image information in multi-sequence segmentation. Subsequently, two key modules are implemented within the multi-scale feature layer: a Large-Kernel Grouped Attention Gating (LKG-Gate) module to strengthen local contextual awareness, and a Multi-Path Feature Extraction (MPFE) module to improve feature robustness via a parallel structure. These designs enable the model to effectively focus on lung tumor target regions, optimize segmentation accuracy, and achieve high-performance reconstruction.ResultsThe framework effectively integrates multimodal features, enabling high-precision localization and sharp boundary delineation while preserving anatomical details. Quantitative evaluations demonstrate superior performance: DICE = 93.2 (92.4∼93.9), CE = 0.352, HD95 = 9.42 (6.03∼12.8), IOU = 86.0 (84.1∼87.9), and SENCE = 0.828. Overall, the model excels at preserving gradient information, regional integrity, and fine details; effectively suppresses feature loss; and reduces missed segmentation rates, leading to improvements in both subjective and objective performance metrics.ConclusionThe proposed segmentation method effectively integrates information from EPID and DRR images, enabling more precise localization and segmentation of lesion regions within EPID images while enhancing segmentation accuracy.

ObjectiveTo validate the diagnostic performance of anti-BNLF2b antibody for detecting nasopharyngeal carcinoma (NPC) compared with healthy controls (HC).MethodsWe conducted a retrospective study including 220 patients with NPC, 61 with tongue cancer (TC), and 88 HC patients. We collected demographic and clinical data, including anti-BNLF2b antibody, EBV DNA, VCA-IgA, EBNA1-IgA, and Rta-IgG. Propensity score matching (PSM) was used to balance baseline characteristics between NPC and comparison groups. Associations between biomarkers and NPC diagnosis were examined using logistic regression. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis.ResultsAfter PSM, 88 patients with NPC were matched to 88 HC with balanced baseline characteristics. Anti-BNLF2b antibody levels were significantly higher in NPC and remained independently associated with NPC diagnosis. For NPC versus HC, anti-BNLF2b antibody showed excellent discrimination (AUC = 0.990; sensitivity 98.9%; specificity 92.0% at a cut-off of 0.210), exceeding the performance of the EBV dual antibody risk probability (AUC: 0.872; P < 0.001). In addition, patients with NPC had higher anti-BNLF2b antibody levels and other EBV-related markers than those with TC.ConclusionIn this retrospective study, anti-BNLF2b antibody demonstrated excellent discrimination for NPC. It may serve as a complementary serologic marker, pending external validation and prospective assessment of clinically optimized cutoffs.

ObjectivesThis retrospective study presents an integrative transcriptomic approach for recurrent and/or metastatic head and neck squamous cell carcinoma (R/M HNSCC) by developing an immune response predictive score (IORPS) derived from tumor microenvironment (TME) transcriptomic profiles.MethodsA total of 30 R/M HNSCC patients treated with pembrolizumab or nivolumab, with available immune TME profiling data, were analyzed. IORPS was constructed based on the cumulative weighting of differentially expressed gene (DEG) expression levels. The predictive performance of conventional biomarkers, individual DEGs, and IORPS was evaluated for immunotherapy response and prognostic outcomes. The clinical relevance of IORPS was further validated using two external cohorts from the GEO database (CLB-IHN: GSE159067 and GHPS: GSE159141).ResultsBy comparing immune tumor microenvironment (TME) profiles between good and poor responders, GZMH, IFNG, and FASLG were identified as key DEGs with significantly higher expression in favorable immunotherapy responders. The IORPS, derived from transcriptomic profiling, demonstrated robust predictive accuracy for both immunotherapy response and survival outcomes in patients with R/M HNSCC.ConclusionCompared with the variable predictive performance of current biomarkers such as TPS and CPS, IORPS provides improved accuracy and reliability in identifying and stratifying patients most likely to benefit from immune checkpoint blockade therapy.