Radiotherapy and Oncology

BackgroundAccurate contouring of target volumes and organs at risk is critical for radiotherapy. While deep learning (DL) models offer efficient automation, their generalizability to real-world clinical cases containing anatomical variations and artifacts requires rigorous validation. PurposeTo evaluate the clinical accuracy and robustness of RatoGuide, a novel DL-based auto-segmentation software, using a dataset derived from routine clinical practice including atypical cases. MethodsThis single-center retrospective study included 36 patients treated for head and neck, thoracic, abdominal, and pelvic cancers. The cohort was intentionally selected to encompass diverse anatomies and artifacts (e.g., pacemakers, artificial femoral head replacement). Auto-contours generated by RatoGuide were compared with expert-approved manual contours. Performance was evaluated quantitatively using the Dice Similarity Coefficient (DSC) and 95th percentile Hausdorff Distance (HD95), and qualitatively via a 5-point visual assessment scale (higher is better) by four independent reviewers. A score of [≤]2 by multiple reviewers was defined as failure. ResultsOverall, the mean DSC, HD95, and visual assessment score were 0.79 {+/-} 0.19, 6.35 {+/-} 12.2 mm, and 3.65 {+/-} 0.88, respectively. The mean DSC exceeded 0.8 in 62% (23/37 organ structures) of the evaluated structure types, and a total of 93.5% (315/337) of all contours were considered clinically acceptable based on visual evaluation . However, lower performance was observed in small structures (e.g., optic chiasm) and low-contrast organs (e.g., esophagus). ConclusionsRatoGuide demonstrated favorable performance for major organs across various anatomical regions, consistent with benchmarks reported in the literature. However, performance variability in atypical cases underscores the necessity of rigorous visual verification by experts for clinical implementation.

PurposeThis study evaluated the safety and effectiveness of an intraoral light-emitting diode (LED)-based photobiomodulation (PBM) device to reduce the incidence and severity of oral mucositis (OM) from intensity modulated radiation therapy (IMRT) for head and neck cancer (HNC). MethodsThis randomized, double-blind, sham-controlled trial enrolled patients with HNC undergoing high-dose IMRT over 6-8 weeks, with or without concurrent chemotherapy. Participants received daily 10-minute PBM or sham treatments immediately before IMRT sessions. Assessments were conducted at baseline, daily and weekly during IMRT, and two weeks post-IMRT. ResultsEighty-five participants (42 PBM; 43 sham) were enrolled across 12 US sites. No device-related adverse events were observed, and 99.5% of initiated sessions were completed. In the intent-to-treat population, severe OM (WHO Grade [≥]3) incidence was significantly lower with PBM across six weeks of IMRT (36.8% vs 57.1%; p = 0.046) and at two weeks post-treatment (10.8% vs 36.4%; p = 0.042). In the per-protocol population, the PBM arm reported significantly greater taste preservation (p = 0.034), lower increases in mouth/throat soreness (p = 0.029) and throat pain (p = 0.028) and needed fewer feeding tube placements (p = 0.073) than the control arm. ConclusionDaily intraoral PBM therapy using an LED-based device was safe, well tolerated, and significantly reduced the incidence of severe OM and associated complications in HNC patients undergoing IMRT with or without concurrent chemotherapy. These findings align with guidelines recommending daily intraoral PBM therapy for preventing cancer therapy-related OM, a dose-limiting toxicity for which effective preventive interventions are needed. Trial RegistrationClinicalTrials.gov Registration Number NCT03972527. Registered on June 3, 2019. Concise SummaryDaily intraoral PBM therapy using an LED-based device was safe, well tolerated, and significantly reduced the incidence of severe OM and associated complications in HNC patients undergoing IMRT with or without concurrent chemotherapy. These findings align with guidelines recommending daily intraoral PBM therapy for preventing cancer therapy-related OM, a dose-limiting toxicity for which effective preventive interventions are needed.

BackgroundLattice radiotherapy (LRT) delivers heterogeneous dose distribution through a three-dimensional array of vertices within the tumor. It is typically applied in 1[~]5 fractions for patients with large tumor volumes. However, conventional LRT generally employs only a single vertex set, which may limit the biological advantages of this technique in multi-fraction treatments. PurposeThis study proposes a novel vertex arrangement strategy in LRT aimed at improving intratumoral dose homogeneity and enhancing coverage of high-dose regions through alternating irradiation of different vertex sets. Materials and methodsPatients with the gross tumor volume (GTV) between 300 cm3 to 2000 cm3 who received radiotherapy treatment at our institution were considered for inclusion. An "NaCl"-type structure was employed. Two sets of vertices ("Na"-type and "Cl"-type) were distributed within the tumor volume following a face-centered cubic (FCC) close-packed pattern analogous to the NaCl crystal structure. For each of the 10 patients with large tumor volumes (range: 319.23-1649.47 cc), two plans were generated: Plan A (optimized for "Na" vertices) and Plan B (optimized for "Cl" vertices). Each plan delivered 15 Gy per fraction to the vertices. Physical doses from Plans A and B were converted to EQD2 (/{beta} = 10 for GTV, /{beta} = 3 for normal tissues) and summed into three composite plans: A+A, A+B, and B+B. Plan quality was assessed using generalized equivalent uniform dose (EUD), homogeneity index (HI), D2, D98, and mean normal tissue dose (Dmean of NT). ResultsThe alternating composite plan (A+B) achieved significantly greater dose homogeneity compared to non-alternating plans (A+A and B+B), with a lower HI (1.23 {+/-} 0.08 vs. 1.70 {+/-} 0.08 and 1.70 {+/-} 0.09, p < 0.05) and higher EUD (3.76 {+/-} 0.38 Gy vs. 3.48 {+/-} 0.40 Gy and 3.42 {+/-} 0.25 Gy, p < 0.05). The low-dose metric D98 was also higher in A+B (4.23 {+/-} 0.27 Gy) than in A+A (3.92 {+/-} 0.25 Gy) and B+B (3.94 {+/-} 0.25 Gy). No significant difference was observed in NT Dmean among the three composite plans. ConclusionAlternating irradiation of two geometrically complementary vertex sets significantly improves dose coverage in high-dose regions and overall dose homogeneity without increasing normal tissue toxicity and potentially enhances therapeutic efficacy in spatially fractionated radiotherapy for large tumors.

Background and purposeStereotactic body radiotherapy (SBRT) has become a standard treatment option for localized prostate cancer, with low rates of clinically relevant late toxicity. However, the identification of robust dosimetric predictors of toxicity remains challenging due to the high dimensionality and collinearity of dose-volume histogram (DVH) metrics. This study aimed to explore whether principal component analysis (PCA) of DVHs can identify dose regions associated with late gastrointestinal and genitourinary toxicity after prostate SBRT. Materials and methodsWe analysed a single-institution cohort of patients treated with prostate SBRT. Rectum, rectal wall, bladder and bladder wall DVHs were extracted with a dose bin resolution of 0.5 Gy. PCA was applied separately to each structure to identify dominant patterns of dose-volume variability. PCA-derived dose metrics were subsequently evaluated using Spearman correlation analyses, receiver operating characteristic (ROC) curves, and exploratory logistic regression models. Late toxicity was scored according to CTCAE version 5.0, with grade [&ge;] 2 events at 12 months as the primary endpoint. ResultsPCA demonstrated that a limited number of components accounted for most DVH variability, with the largest contributions arising from intermediate-dose regions. For the whole rectum, intermediate-dose metrics showed the strongest association with late rectal toxicity. Rectal V18.1 Gy yielded the highest discriminative performance (AUC = 0.87), followed by V29 Gy (AUC = 0.83), whereas low-dose (V1.5 Gy) and high-dose (V42.5 Gy) metrics showed limited or no discrimination. Rectal wall metrics demonstrated weaker and less robust associations, and no clinically meaningful discriminative performance was observed for bladder or bladder wall DVH metrics. Exploratory regression analyses supported the association between intermediate rectal dose exposure and late rectal toxicity. ConclusionIn prostate SBRT, PCA of DVHs highlights intermediate rectal dose exposure as the primary dosimetric determinant of late rectal toxicity. Whole-rectum intermediate-dose metrics outperform both low- and high-dose parameters, as well as rectal wall and bladder-derived metrics. These findings support a parsimonious, data-driven focus on intermediate-dose rectal volumes for toxicity risk assessment and hypothesis generation in prostate SBRT planning.

BackgroundCurrently, no comprehensive tool exists to systematically assess patient safety in radiation oncology (RO). To address this gap, we developed the Patient Safety in Radiation Oncology questionnaire (PaSaRO), a German instrument enabling RO professionals to evaluate patient safety within their departments. MethodsBuilding on a literature review identifying 145 patient safety indicators (PSIs), we determined further PSIs via two focus groups with RO professionals, patient interviews, and expert consultations. RO professionals were recruited through professional networks and societies, while patients were recruited as a convenience sample at a university hospital centre. Content validity was ensured by assessing relevance and comprehensiveness through a Delphi study and comprehensibility through cognitive interviews with RO professionals. FindingsTwo focus groups generated 48 new PSIs, while nine patient interviews contributed 15 PSIs, and three experts suggested 12 more. In combination with the PSI from the review, a total of 213 PSIs were compiled and subsequently rated in the Delphi study by 84 professionals in the first round and 72 in the second. During this process, seven additional PSIs were suggested, and 158 were ultimately deemed relevant. In cognitive interviews, 43 PSIs were linguistically refined to improve clarity. InterpretationThis study produced a pilot version of the PaSaRO, comprising 158 consensus-based PSIs--the first comprehensive questionnaire specifically developed for RO. The rigorous multi-method development process ensures strong content validity. Future research will conduct psychometric evaluation, after which PaSaRO may serve as a standardized tool for assessing, monitoring, and improving patient safety in RO.

ObjectivesTo evaluate the clinical performance of a cadmium-zinc-telluride-(CZT-) based photon-counting computed tomography (PCCT) system for low-dose lung cancer screening (LCS-LDCT) using patient-specific 3D-printed lung phantoms, and to compare its image quality and radiomics consistency with a conventional energy-integrating detector CT (EIDCT) system. MethodsSix 3D-printed lung phantoms, derived from patient CT datasets and representing various lesion types (solid, part-solid, and ground-glass), were imaged on PCCT and EIDCT scanners at matched dose levels (1.6 - 20.4 mGy). Quantitative image metrics, Hounsfield unit (HU) accuracy, image noise, and contrast-to-noise ratio (CNR), were assessed across dose levels. Radiomic features were extracted for each lesion and analyzed via principal component analysis to quantify feature consistency (within-cluster distance) and lesion type separability. ResultsPCCT demonstrated significantly lower image noise and higher CNR compared with EIDCT, particularly at lower dose levels. HU values were consistent across doses for both systems, with reduced variability in PCCT (coefficient of variation < 0.004). Radiomics analysis revealed tighter clustering (reduced within-cluster distances) and comparable lesion type separability between PCCT and EIDCT, indicating enhanced feature stability and lesion differentiation. Qualitative review confirmed superior lesion conspicuity and margin delineation with PCCT. ConclusionsCZT-based PCCT outperforms conventional EIDCT in quantitative and qualitative imaging metrics for LCS-LDCT, enabling superior image quality and radiomics reproducibility at reduced radiation doses. These findings support the clinical translation of PCCT for lung cancer screening and radiomics-based lesion characterization. Key pointsO_LIPCCT offers reduced image noise and improved CNR performance, especially at ultra-low doses. C_LIO_LIHU stability and radiomics reproducibility are enhanced with PCCT. C_LI Clinical relevance statementO_LIPCCT may enable further dose reduction without compromising diagnostic accuracy in LCS-LDCT. C_LI

Glioblastoma is increasingly treated with Tumor Treating Fields (TTFields), but how post-craniotomy anatomy and fixation hardware alter delivered fields is unclear. We used finite-element modeling in a realistic head model to simulate TTFields after a standard bone flap with either a non-penetrating fixation plate or a penetrating skull clamp, and compared results to an intact-skull baseline across a range of clinically used array layouts. Bone gaps increased mean brain electric-field magnitude by [~]10-20%. Non-penetrating plates caused only minimal, localized changes relative to the bone-gap condition. In contrast, penetrating clamps produced strong but spatially confined increases: local mean fields were [~]6-8x higher within 5-10 mm of the device, with [&ge;] 50% enhancement extending [~]50-60 mm depending on whether the gap was modeled as healed scalp (soft-tissue-like) or healed bone; this enhancement decayed with distance. These simulations, performed in a single head model with literature-based tissue conductivities, suggest that penetrating hardware can substantially modulate local TTFields delivery, whereas non-penetrating plates have minimal impact. Accounting for post-surgical anatomy and hardware in TTFields planning may improve dose targeting.

BackgroundThe incidence of human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC) has increased substantially, predominantly affecting younger patients with favourable survival outcomes. As long-term survival improves, minimizing treatment-related morbidity has become a key clinical objective. Transoral robotic surgery (TORS) provides precise pathological staging that may facilitate treatment de-escalation; however, integrated evidence on oncologic, functional, and economic outcomes remains limited. ObjectiveTo systematically evaluate oncologic, functional, and economic outcomes of TORS-based treatment strategies in patients with HPV-positive OPSCC through systematic review and meta-analysis. MethodsA systematic review and meta-analysis were conducted in accordance with PRISMA 2020 guidelines. PubMed, Wiley Online Library, MDPI, Cureus, and MedRxiv were searched for English-language studies published between 2019 and 2025. Meta-analyses were performed for 2-, 3-, and 5-year overall survival, postoperative tracheostomy rates, long-term gastrostomy dependence, and postoperative hemorrhage using random-effects models. Study quality was assessed using validated tools, including RoB 2.0, NOS, MINORS, and JBI checklists. ResultsTwenty-two studies (20 clinical and 2 economic analyses), comprising over 7,000 patients, were included. Meta-analysis demonstrated pooled overall survival rates exceeding 95% at 2 years and favourable survival at 3 and 5 years. Pooled rates of long-term gastrostomy dependence and tracheostomy were low (<5%), and postoperative hemorrhage was infrequent. Pathological upstaging following TORS frequently identified adverse features, enabling risk-adapted adjuvant therapy. De-escalation strategies were associated with substantial reductions in severe treatment-related toxicity while preserving swallowing function and quality of life. Economic analyses suggested that higher upfront surgical costs may be offset by reduced adjuvant therapy and long-term morbidity. ConclusionTORS represents an oncologically sound primary treatment for HPV-positive OPSCC that enables accurate pathological risk stratification and supports treatment de-escalation. Meta-analytic evidence indicates excellent survival outcomes with low rates of major functional morbidity, and TORS may offer long-term economic advantages in appropriately selected patients treated at experienced centres.

PurposeTo develop and evaluate a novel double bowtie filter integrating a K-edge material layer with a conventional Teflon filter for pediatric spectral computed tomography (CT). The proposed design aims to enhance spectral signal-to-noise ratio (SNR) and spectral separation while maintaining radiation dose levels suitable for pediatric imaging. MethodsA simulation framework was set up and used to model a rapid kVp-switching CT system operating at 70/110 kVp with realistic tube power and geometry constraints. Pediatric phantoms of three sizes (100- 200 mm anterior-posterior width) were used to evaluate performance. Five accessible and safe filter materials-gadolinium (Gd), holmium (Ho), erbium (Er), silver (Ag), and tin (Sn)-were tested in combination with a Teflon bowtie. System performance was quantified using virtual monoenergetic image (VMI) SNR at 40 keV and 70 keV, and the area under the monoenergetic SNR curve (AUMC) as a comprehensive spectral image quality metric. Dose consistency with a traditional Teflon bowtie reference was enforced. ResultsThe Teflon + Gd configuration achieved the highest performance, improving AUMC by 47.5 % on average and up to 56 % for the largest phantom. VMI SNR increased by approximately 49 % at 40 keV and 42 % at 70 keV. ConclusionsThe double-bowtie concept substantially enhances spectral performance. The Teflon + Gd design provides a manufacturable, pediatric-optimized solution adaptable to kVp-switching and other spectral CT architectures, offering improved diagnostic quality at low dose levels.

BackgroundVision Foundation Models (VFM) have emerged as a promising approach for computational pathology, offering scalable feature representations that may reduce labelled-data requirements and improve robustness to variation in tissue preparation and digitisation. However, VFM decoder and dataset size requirements as well as the performance under real-world domain shifts remain unclear. MethodsWe evaluated six contemporary VFMs on a protocol-variant Prostate Cancer (PCa) dataset comprising 37 683 tissue microarray spot images from 10 412 patients. The dataset includes six controlled domain shifts arising from differences in staining duration, section thickness, scanner type, and sampling location. Two clinically relevant downstream tasks were examined: ISUP grading and 5-year relapse prediction. We compared two decoder architectures, quantified dataset-size requirements using a saturation analysis (45-5727 samples), and assessed cross-domain robustness using out-of-domain test sets. FindingsLarger VFMs consistently outperformed smaller models in peak accuracy and robustness metrics. Contrary to expectations of data efficiency, all models showed strong dependence on training-set size, requiring at least 1000 samples to approach stable results. All VFMs showed notable degradation under protocol-level domain shifts, with performance reductions of 4 to 13 percentage points in both cancer grading and relapse prediction, although larger models exhibited somewhat greater robustness. Furthermore, KNN-based probing performed substantially worse than a decoder-based approach across all architectures. InterpretationsDespite their strong representational capacity, current VFMs do not yet provide reliable domain generalisation or data-efficient performance in computational pathology. Decoder design remains essential, and substantial amounts of labelled data are still required to achieve clinically meaningful accuracy. Further advances in pre-training strategies, decoder architectures, and domain adaptation methods will be crucial for translating VFMs into robust clinical tools. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThis study focuses on pathology foundation models, which offer promising improvements in performance, data requirements, and robustness to domain shifts for computational pathology. To identify relevant studies, we searched in Google Scholar for research published before 1 April 2025. We searched for studies introducing novel foundation models trained on pathology images, or reviews comparing those models in terms of performance or robustness. The search terms used were computational pathology, benchmarking, review and foundation model, as well combinations of these terms. We found that many studies focus on increasing the complexity of pathology foundation models while using increasingly extensive and heterogeneous pre-training datasets. Various benchmarking studies demonstrate the superior performance and robustness of more recent and larger foundation models. However, these studies have limitations in their evaluation datasets. Either they cover only a domain shift due to a different scanner device, or they have small sample sizes. We also identified a research gap regarding the requirement for large datasets to train a decoder based on a pathology foundation model for a specific downstream task. Added value of this studyThe goal of this study was to evaluate the necessity of large downstream task datasets and the domain shift robustness of multiple pathology foundation models. For this purpose, we used our internal protocol-variant prostate cancer dataset, which provides a controlled evaluation setup as multiple domain shift types have been intentionally and separately introduced for different sub-datasets. Our saturation analysis revealed that at least 1000 samples were necessary to achieve good performance. Furthermore, our findings show that none of the evaluated foundation models are robust against all of our domain shifts, though larger models generally perform better. Implications of all the available evidenceThis study reveals that increasing the capacity of pathology foundation models improves performance and robustness. However, we demonstrated that all models exhibit some degree of performance degradation for certain domain shifts and require substantial datasets for training on downstream tasks. These limitations demonstrate that pathology foundation models do not fully address the issues of robustness and data requirements.

ObjectiveTo evaluate the dose efficiency of cadmium-zinc-telluride (CZT) based photon-counting CT (PCCT) compared to energy-integrating detector CT (EID-CT) across phantom sizes. MethodsA patient-specific 3D-printed pancreas phantom and a phantom with tissue mimicking inserts were placed in extension rings corresponding to the 50th, 75th, 85th, and 95th percentile adult waist circumferences. Phantoms were scanned on both PCCT and EID-CT with CTDIvol ranging from 0.5 to 19.4 mGy. Noise was measured in both phantoms to evaluate dose efficiency. Non-Poisson noise at low doses (<2 mGy) was quantified using root mean square error from linear fits of the noise-dose relationship. Potential dose reduction was then assessed by matching noise levels between scanners across phantom sizes. ResultsPCCT demonstrated reduced noise compared to EID-CT across all phantom sizes and doses with average noise reductions of 22%, 23%, 25%, and 28% for the 50th, 75th, 85th, and 95th percentile phantoms, respectively. Noise reduction intensified at lower doses and larger phantom sizes, reaching 88 HU at 1 mGy for the 95th percentile phantom. Non-Poisson noise decreased significantly with PCCT compared to EID-CT for all phantom sizes (p < 0.013). At matched noise levels, PCCT enabled dose reductions of 33% and 44% for the 50th and 95th percentile phantoms, respectively. ConclusionsPCCT exhibited superior dose efficiency compared to EID-CT across a range of phantom sizes. The enhanced dose efficiency enables both noise reduction and potential dose reduction for the imaging of obese patients and low-dose imaging applications. Key PointsO_ST_ABSQuestionC_ST_ABSPhoton-counting CT (PCCT) enables improved quantum detection and eliminates electronic noise, but its benefits have not been evaluated for obese patient sizes. FindingsCompared to EID-CT, PCCT enhanced dose efficiency with noise reduction and potential dose reduction across all phantom sizes and doses. Clinical RelevanceThe improved dose efficiency of PCCT facilitates noise reduction that enables diagnostic image quality, and thereby the diagnostic accuracy, for obese patients.

IntroductionPI-RADS 3 ( equivocal) prostate MRI lesions pose a diagnostic challenge, particularly in non-referral settings with variable MRI quality. We evaluated whether prostate-specific antigen density (PSAD) and the Stockholm3 blood test can aid biopsy decisions for men with PI-RADS 3 lesions in a prospective, non-referral Swiss cohort. MethodsRetrospective analysis of a prospective registry at a non-referral urology practice in Switzerland. From 2023-2025, men with PSA >1.5 ng/mL or suspicious digital rectal examination underwent Stockholm3 testing, MRI, and MRI-fusion plus systematic prostate biopsy. Clinically significant prostate cancer (csPCa) was defined as ISUP grade [&ge;]2. Diagnostic accuracy and decision curve analysis compared Stockholm3 ([&ge;]13%, [&ge;]15%, [&ge;]18%) and PSAD thresholds (0.10, 0.15, 0.20ng/mL/cc) within the PI-RADS 3 subgroup. ResultsOverall, 50/174 (29%) men had PI-RADS 3 lesions, 59/174 (34%) were diagnosed with csPCa. Among PI-RADS 3 lesions, csPCa prevalence was 14%. Outcome distributions shifted towards higher ISUP grades with increasing PSAD thresholds when compared to baseline ([&ge;]0.15ng/mL/cc: 44% ISUP[&ge;]2; p=0.009), whereas Stockholm3 cut-offs showed no significant change for csPCa. As continuous measures, PSAD demonstrated superior discrimination (AUC 0.751; 95% CI 0.46-0.95) than Stockholm3 (AUC 0.595; 95% CI 0.30-0.88), confirming higher overall diagnostic accuracy within the PI-RADS 3 subgroup. Decision curve analysis demonstrated higher net benefit for PSAD-based approaches. ConclusionIn non-referral practice, Stockholm3 did not reliably exclude csPCa among men with PI-RADS 3 lesions. PSAD-based triage, particularly at [&ge;]0.15ng/mL/cc, showed superior diagnostic utility and may support safe biopsy deferral in selected cases. Prospective validation in broader non-referral settings is warranted.

BackgroundLarge-scale CT-based reference standards for abdominal organ volume, incorporating age, sex, and body size, are limited. PurposeTo establish sex- and age-specific reference distributions for major abdominal organ volumes on non-contrast abdominopelvic CT in a nationwide Japanese cohort to provide a foundation for automated clinical assessment and dose optimization. Materials and MethodsIn this retrospective, multicenter study, using the Japan Medical Image Database, we identified all non-contrast abdominopelvic CT examinations performed in 2024. Unique adults with available data on age, sex, height, and weight were included in this study. The final sample comprised 49,764 examinations (26,456 men and 23,308 women) conducted at nine institutions. Automated segmentation (TotalSegmentator v2.10.0) was used to produce organ volumes, excluding hollow viscera. The sex-specific 10th, 25th, 50th, 75th, and 90th percentiles were calculated. Age-volume relationships of body surface area (BSA)-normalized volumes (mL/m2) were modeled using natural cubic splines (four degrees of freedom) separately by sex. ResultsMedian (mL) male vs female volumes were as follows: liver, 1194.7 vs 1024.0; pancreas, 63.6 vs 52.2; spleen, 118.1 vs 95.1; kidneys (total), 268.3 vs 221.2; adrenals (total), 6.6 vs 4.2; iliopsoas (total), 483.4 vs 317.7; prostate, 24.9 (men only). Age-volume relationships of BSA-normalized volumes showed convex patterns for the liver, pancreas, and kidneys in both sexes and for male adrenal glands; lower values in older age groups for the spleen and iliopsoas in both sexes; and higher values in older age groups for the prostate and female adrenal glands. ConclusionThis nationwide Japanese CT cohort provides sex- and age-resolved volumetric reference standards. These standards enable objective identification of abnormalities, support personalized medicine, and facilitate automated AI-based reporting to reduce radiologist workload and optimize radiation dose protocols. Key ResultsO_LIMedian volumes (men vs women, mL): liver 1195/1024; pancreas 64/52; spleen 118/95; kidneys 268/221; adrenals 6.6/4.2; iliopsoas 483/318; prostate 25. C_LIO_LIBody surface area-normalized age-volume relationships were convex for liver, pancreas, and kidneys in both sexes and for male adrenal glands. C_LIO_LISpleen and iliopsoas declined monotonically with age in both sexes, whereas prostate and female adrenal glands increased monotonically. C_LI

PurposeBladder cancer is associated with significant morbidity and mortality in the US, with 85,000 new cases and 17,400 deaths expected in 2025. Black patients are more likely than White patients to be diagnosed with bladder cancer at advanced stages, as are female patients compared with male patients. We examine whether differences in cancer diagnosis rates by race and sex can explain the observed variability using a simulation model and project outcomes of potential improvement in diagnosis. MethodsWe developed a state transition model for bladder cancer to simulate four cohorts based on sex (males, females) and race (Blacks, Whites) from birth through various health states, including disease-free, preclinical stages (0a/0is - IV), clinical stages (0a/0is - IV), and death (bladder cancer or other cause death). Parameters related to disease onset, progression, and diagnosis were estimated by calibrating the model to race- and sex-specific incidence rates by age, and stage distribution at diagnosis for cases diagnosed between 2015 and 2019 in SEER 17 registry areas. We conducted a scenario analysis to examine the impact of differences in diagnosis rates on stage distribution and life expectancy, assuming that Black males (or females) and White females had diagnosis rates similar to those of White males. ResultsThe calibrated model attributes the differences in stage distribution to lower diagnosis rates in White females (hazard ratio, [HR] = 0.95, 95% credible interval [CI]: 0.92 - 0.96), Black males (0.80, 95% CI: 0.75 - 0.81) and Black females (0.56, 95% CI: 0.53 - 0.58), relative to White males. If diagnosis rates for all demographic groups were similar to White males, the expected life span of a 65-year-old bladder cancer patient would increase by 0.2 years for White females (from 13.8 to 13.9 years), 0.6 years for Black males (from 10.6 to 11.1 years), and 1.9 years for Black females (from 10.5 to 12.4 years). ConclusionsDifferences in diagnosis rates of bladder cancer by race and sex explain the observed differences in stage distribution at diagnosis. Targeted interventions aimed at improving diagnosis rates have the potential to substantially improve survival for patients with bladder cancer.

Medical image segmentation remains a critical bottleneck in clinical workflows, from diagnostic radiology to radiation oncology treatment planning. We present Onco-Seg, a medical imaging adaptation of Metas Segment Anything Model 3 (SAM3) that leverages promptable concept segmentation for automated tumor and organ delineation across multiple imaging modalities. Unlike previous SAM adaptations limited to single modalities, Onco-Seg introduces a unified framework supporting CT, MRI, ultrasound, dermoscopy, and endoscopy through modality-specific preprocessing and parameter-efficient fine-tuning with Low-Rank Adaptation (LoRA). We train on 35 datasets comprising over 98,000 cases across 8 imaging modalities using sequential checkpoint chaining on a 4-GPU distributed training infrastructure. We evaluate Onco-Seg on 12 benchmark datasets spanning breast, liver, prostate, lung, skin, and gastrointestinal pathologies, achieving strong performance on breast ultrasound (Dice: 0.752{+/-}0.24), polyp segmentation (Dice: 0.714{+/-}0.32), and liver CT (Dice: 0.641{+/-}0.12). We further propose two clinical deployment patterns: an interactive "sidecar" for diagnostic radiology and a "silent assistant" for automated radiation oncology contouring. We release an open-source napari plugin enabling interactive segmentation with DICOM-RT export for radiation oncology workflows. Code and models are available at https://github.com/inventcures/onco-segment.

DNA repair capacity (DRC), particularly at the pathway level, varies among individuals. While previous studies explored DRC in relation to environmental exposures and cancer risk, few measured DRC in patient-focused cohorts and were focused on one or two repair pathways only. We comprehensively profiled DRC for all the major repair pathways and DNA lesions in 100 lung cancer patients undergoing radiotherapy (RT) using advanced Fluorescence Multiplex based Host Cell Reactivation assays in blood cells before and after RT and investigated how DRC responded to RT and was influenced by clinical variables. Variation between individuals was significant in all pathways and smaller than variation within-person. DNA glycosylase activity decreased immediately following RT and subsequently returned to baseline in patients receiving high-intensity RT during the follow-up months. Lower DRC against oxidative lesions was found in cancer patients compared to healthy controls. These results highlight oxidative DNA damage repair as a sensitive marker of RT response and cancer burden upon profiling the DNA repair landscape. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/26343971v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1ddcd5forg.highwire.dtl.DTLVardef@d642fdorg.highwire.dtl.DTLVardef@c7f38corg.highwire.dtl.DTLVardef@1469bea_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background and Purpose: Magnetic resonance imaging (MRI) for radiation therapy treatment planning is currently being used in many anatomical sites to better visualize soft tissue landmarks, a technique known as an MRI simulation. A core component of modern MRI simulation configurations are the use of external laser positioning systems (ELPS) to help set up the patient. Though necessary for accurate and reproducible patient setup, the ELPS, if left on during imaging, may interfere negatively with image quality due to leaking electronic noise, of which MRI is sensitive to. It is currently unknown whether this leakage of electronic noise may further affect quantitative values derived from clinically employed relaxometric, diffusion, and fat fraction sequences. Therefore, in this study, we aim to characterize the impact of MRI simulation lasers on general image quality and quantitative imaging accuracy. Materials and Methods: First, a cine acquisition was used to visualize the real-time changes in image signal-to-noise ratio (SNR) from when the ELPS was deactivated to activated. To validate this effect quantitatively, the SNR was measured using the American College of Radiology (ACR) recommended protocol in a homogeneous phantom with the integrated body, 18-channel UltraFlex small, 18-channel UltraFlex large, 32-channel spine, and 16-channel shoulder coils. Next, a geometric distortion algorithm was tested in two vendor-provided phantoms while using the integrated body coil and the ACR Large Phantom protocol was tested. Finally, a series of quantitative MRI scans were performed using a CaliberMRI Model 137 Mini Hybrid phantom to validate quantitative T1, T2, and ADC while a Calimetrix PDFF-R2* phantom was used for quantitative PDFF and R2*. All scans were performed with both the ELPS both deactivated and activated. Results: Visible electronic noise artifacts were seen when using the integrated body coil when the ELPS was activated on the cine acquisition which led to a four-fold decrease in SNR using the ACR protocol. This SNR drop was not seen when using the remaining tested coils. The automatic fiducial detection algorithm was affected negatively by ELPS activation leading to misidentification when identified perfectly with the ELPS deactivated. Degradation in image intensity uniformity, percent signal ghosting, and low contrast object detectability was seen during ACR Large Phantom testing using the 20-channel Head/Neck coil. Concordance across quantitative MRI values was similar when the ELPS was both deactivated and activated while a consistent increase in standard deviation inside the ADC vials was seen when the ELPS was activated. Discussion: The extra noise induced from the activation of the ELPS during imaging should be avoided due to its potential to unnecessarily increase image noise. This is particularly true when conducting mandatory quality assurance testing for image quality and geometric distortion which utilize the integrated body coil which is most susceptible to ELPS-induced noise. Clear clinical guidelines should be implemented to make this issue known to the MRI technologists, physicists, and other relevant staff using an MRI with a supplementary ELPS for patient alignment.

Background and ObjectiveRisk stratification in localized prostate cancer relies primarily on Grade group (GG). In GG2-4 disease, risk assignment depends on the proportions of pattern 3 and pattern 4. We hypothesized that total pattern 4 length on biopsy would better predict oncologic outcome than GG, percent pattern 4, and multivariable models ("nomograms") based on clinical variables. MethodsWe identified 2499 patients with GG2-4 prostate cancer on biopsy who underwent radical prostatectomy. Discrimination for predictors was calculated for adverse pathologic stage (seminal vesicle invasion or lymph node invasion) and biochemical recurrence (BCR). Key Findings and LimitationsTotal pattern 4 length for the case demonstrated the highest discrimination for adverse pathologic stage in comparison with GG (AUC 0.779 vs 0.658; p<0.0001), percent pattern 4 (0.719), and a model including prostate-specific antigen level, clinical stage, GG, PI-RADS score, and number of positive cores (0.762). Results were similar for BCR, with total pattern 4 length outperforming GG (C-index 0.716 vs 0.662), percent pattern 4 (0.695), and the clinical model (0.699). Neither mm of pattern 3 nor the clinical model added discrimination to total mm of pattern 4. Conclusions and Clinical ImplicationsTotal length of Gleason pattern 4 on biopsy best predicts oncologic outcome in GG2-4 prostate cancer. Other common clinicopathologic variables do not further aid discrimination. Further research is warranted to determine the optimal method for quantifying pattern 4 before incorporation into risk stratification algorithms. O_LIWhat does the study add?: Patients with Grade group 2-4 prostate cancer constitute both the largest group and the one in which treatment decision-making is most difficult. For such patients, total length of Gleason pattern 4 on biopsy predicted oncologic outcomes better than Grade group or multivariable models including the standard predictors of stage, grade, PSA, PI-RADS and number of positive cores. Neither mm of pattern 3 nor the standard predictors add discrimination once total length of pattern 4 is known. C_LIO_LIPatient Summary: Treatment decisions in prostate cancer are often determined by the ratio of pattern 4 to pattern 3 disease. We showed that, in GG2-4 disease, using the total amount of pattern 4 for the case better predicts risk and therefore provides a better basis for treatment decisions. C_LI Take Home MessageIn Grade group 2-4 prostate cancer, total Gleason pattern 4 length for the case is a stronger predictor of adverse pathologic stage and biochemical recurrence than Grade group and other standard clinical variables. Further research is warranted to determine the optimal method for quantifying pattern 4 before incorporation into risk stratification algorithms.

ObjectiveTo establish the local diagnostic reference levels (LDRLs) for trunk multi-slice CT (MSCT) examinations in the Gaza Strip, Palestine. MethodA cross-sectional study of adult oncology patients undergoing trunk MSCT at two governmental hospitals in Gaza Strip; Al Shifa Medical Complex (SMC) and Al Aqsa Hospital (AMH), using an adapted dose survey booklet. Data collected from July 2019 to March 2020 included patient characteristics, volumetric CT dose index (CTDIvol) and dose length product (DLP). Descriptive, univariate and multivariate analyses identified key factors affecting radiation dose, and the coefficient of variation between scanner and software-derived dose values was also determined. ResultsA total of 170 trunk CT examinations were analysed (57.1% SMC, 42.9% AMH). 73% were female; the mean age of the participants is 53.1{+/-}15.8 years, and the mean body mass index (BMI) was 30{+/-}6.1. The estimated LDRLs for trunk CT were 13 mGy for CTDIvol and 1010.4 mGy{middle dot}cm for DLP. There was notable variation between hospitals in CTDIvol and DLP (p<0.001). At SMC, factors such as tube current, peak kilovoltage, scan length, pitch and BMI significantly affected dose indices. In contrast, at AMH, the main influences were tube current and scan length. CTDIvol had a greater impact on DLP than scan length at both locations. ConclusionLDRLs for trunk CT scans in the Gaza Strip were established and found to be generally comparable to international benchmarks. Notable variation in doses between hospitals indicates potential for improvement through standardising protocols, managing scan lengths and using techniques tailored to patient size.

Abstract Background: Conventional MRI cannot reliably distinguish radiation necrosis (RN) from recurrent metastasis after cranial radiotherapy, as both can show similar enhancement despite different biology. We tested whether these entities are mechanically non-equivalent in vivo and separable by MRE-derived viscoelastic metrics and perilesional interface-instability features. Methods: In a prospective, histopathology-anchored cohort, 11 post-radiotherapy enhancing lesions were classified as RN (n=3) or recurrent/progressive tumor (n=8). MRE was acquired at 3.0 T with single-frequency 60-Hz excitation to derive storage modulus (G'), loss modulus (G''), and complex shear modulus magnitude (|G*|). Co-primary endpoints were median tumor G' and |G*|, each tested one-sided (RN > tumor) with Holm correction across the two co-primary tests. Median tumor G'' was tested two-sided. A prespecified secondary 6-endpoint family (absolute and tumor/NAWM-normalized G', G'', and |G*|) was analyzed with Benjamini-Hochberg FDR control. Exploratory instability mapping in a 0- 6 mm peritumoral shell generated interface-topology metrics, including convexity. Results: Absolute tumor-core medians were higher in RN than tumor for |G*| (1.79 vs 1.32 kPa; Cliff's {delta} = 0.67; q = 0.10), G' (1.62 vs 1.09 kPa; {delta} = 0.50; q = 0.14), and G'' (0.81 vs 0.46 kPa; {delta} = 0.75; q = 0.10). NAWM normalization improved separation: tumor/NAWM |G*| (2.26 vs 1.41; {delta} = 0.92; q = 0.04) and tumor/NAWM G'' (2.67 vs 0.87; {delta} = 1.00; q = 0.04) were FDR-significant. Convexity also differentiated RN from tumor (0.49 vs 0.36; {delta} = 1.00; MWU p = 0.01). Conclusions: Tumor/NAWM G'', tumor/NAWM |G*|, convexity, and tumor G'' emerged as the strongest candidate features, indicating that RN is mechanically harder and more dissipative than recurrent metastasis. Signal strength was high (Cliff's {delta} up to 1.00) but should be interpreted cautiously given sample size. Exploratory analyses further suggest that instability mapping captures biologically relevant interface behavior. These findings support a mechanics-based RN-versus-recurrence framework and justify prespecified, preregistered external validation.