The study, led by Ali H. Duzkalir and Selcuk Peker of Koc University Hospital in Istanbul, pooled data from twelve institutions spanning the United States, Canada, Europe, the Middle East, and East Asia. Because male breast cancer accounts for less than one percent of all breast cancer cases, and because brain metastases arise in only a subset of those patients, no single center could ever accumulate enough cases to draw meaningful conclusions. By aggregating decades of experience from flagship radiosurgery programs, including the University of Pittsburgh Medical Center, the University of Virginia, NYU Langone, Na Homolce Hospital in Prague, Taipei Veterans General Hospital, and Sheba Medical Center in Israel, the researchers assembled a cohort large enough to interrogate with modern statistical tools. Nineteen patients carrying a total of 185 individually treated lesions formed the final analytical dataset.

The technical architecture of the analysis deserves attention, because it reflects how radiosurgery outcomes are increasingly evaluated in the era of big-data oncology. Rather than treating each patient as a single independent data point, the team used generalized estimating equations with robust variance estimation, a method that correctly accounts for the fact that one patient may contribute several lesions whose outcomes are statistically correlated. Overall survival was estimated with Kaplan-Meier curves, the standard approach for handling censored follow-up times. Changes in neurological symptoms before and after treatment were tested with McNemar’s exact test, a paired analysis suited to before-and-after binary outcomes in a small cohort. To identify which radiation dose characteristics predicted treatment failure, the investigators turned to receiver operating characteristic analysis, which measures how well a continuous variable, such as tumor volume, discriminates between lesions that recur and those that do not.

The headline finding is the crude local control rate of 97.3 percent, meaning that nearly every irradiated tumor stopped growing after a single radiosurgical session. For context, brain metastases from many other cancer types often recur locally in ten to twenty percent of treated lesions even at experienced centers, so a failure rate below three percent is remarkable. The median age of the patients at the time of radiosurgery was 59.0 years, and the cohort’s median overall survival reached 28.0 months, a figure that compares favorably with published survival data for breast cancer brain metastases more broadly, where whole-brain radiation therapy cohorts frequently show far shorter survival.

Perhaps the most clinically consequential result concerns what happened outside the brain. Patients whose systemic disease, meaning cancer elsewhere in the body, was under control at the time of radiosurgery lived a median of 40.0 months, compared with just 22.0 months for those with uncontrolled systemic disease, a difference that reached statistical significance at p equals 0.032. This pattern echoes a growing body of evidence from female breast cancer cohorts, including the SYBRA study published in npj Breast Cancer in 2024, which found that systemic disease status strongly influences central nervous system outcomes after radiosurgery. The message for clinicians is unambiguous: the brain is only one battlefield, and survival in oligometastatic disease is ultimately governed by whether the cancer can be contained throughout the body.

On the dosimetric side, the study identified target volume as the single most important predictor of both treatment failure and radiation toxicity. Receiver operating characteristic analysis showed that lesion volume significantly discriminated between controlled and failed lesions, with an optimal threshold of 0.98 cubic centimeters, roughly a sphere just over a centimeter in diameter. Lesions smaller than this threshold were far more likely to be permanently controlled. The same variable independently predicted adverse radiation effects on multivariable analysis at p equals 0.013, confirming a principle well established in the radiosurgery literature: the larger the target, the harder it becomes to deliver an ablative dose without injuring adjacent brain tissue, because dose falloff is finite and larger volumes inevitably expose more normal parenchyma.

The safety and neurological data add an important human dimension. Before treatment, 63.2 percent of patients carried a neurological symptom burden attributable to their brain metastases, ranging from headaches and seizures to focal deficits. After radiosurgery, that figure fell to 26.3 percent, a statistically significant improvement at p equals 0.016. Equally important, the median Karnofsky Performance Status, a standard zero-to-one-hundred scale of functional independence used across oncology, remained stable over follow-up. In a population where brain-directed treatment can sometimes trade cognitive function for tumor control, the combination of symptom relief and preserved performance status is exactly the profile clinicians hope to see.

Why does this matter beyond the nineteen patients studied? Male breast cancer is biologically distinct in several respects. Population-based analyses of SEER registry data and recent reviews have shown that men are more often diagnosed at later stages, more frequently carry hormone receptor positive tumors, and may experience different metastatic patterns than women. Molecular studies have even documented subtype conversion in metastatic lesions, meaning the tumor’s receptor profile can shift between the primary breast tumor and its brain deposits, complicating targeted therapy. Because men are typically excluded from breast cancer trials by design or by accident, evidence for their care is often extrapolated from female cohorts. This study provides direct, lesion-level evidence that the established practice parameters for stereotactic radiosurgery, developed and refined over decades largely in women, translate safely and effectively to men.

The findings also arrive at a moment of ferment in the field of brain metastasis management. Randomized trials comparing whole-brain radiation with radiosurgery are ongoing, and the rising use of antibody-drug conjugates and other potent systemic agents has raised new questions about combined treatment toxicity, including radiation necrosis risk highlighted in a 2026 systematic review in Neurosurgical Reviews. Against that backdrop, the current study anchors one corner of the evidence base: for men with breast cancer brain metastases, focused radiosurgery achieves near-total local control, shrinks the neurological symptom burden, and preserves function, provided that lesions are kept within the volume range where the technique excels.

The authors are careful about the limitations inherent to their design. A retrospective cohort of nineteen patients cannot establish causation, cannot capture every variable that influences survival, and cannot substitute for prospective registration. The study received no external funding, was approved by the Institutional Review Board of Koc University, and was conducted in accordance with the Declaration of Helsinki, with informed consent waived due to the de-identified, retrospective nature of the data. Yet in a disease so rare that even the largest single institutions may see one case every few years, the multicenter retrospective approach is not a compromise but the only realistic path forward. The study, published as volume 179, article 73 of the Journal of Neuro-Oncology on 9 September 2026, gives clinicians treating this overlooked population something they have never had before: numbers they can stand on.

Subject of Research: Stereotactic radiosurgery outcomes for brain metastases arising from male breast cancer

Article Title: Stereotactic radiosurgery for brain metastases from male breast cancer: a multicenter retrospective study

Article References: Duzkalir, A. H., Askeroglu, M. O., Yildirim, D. C., Marciniuk, K., Bernstein, K., Tos, S. M., Reyes, J. S., Liscak, R., Simonova, G., Sumi, T., Kano, H., Kilic, T., Kilic, D., Bowden, G. N., Shemesh, S. Z., Kaisman-Elbaz, T., Lee, C.-C., Yang, H.-C., Kutuk, T., … Peker, S. (2026). Stereotactic radiosurgery for brain metastases from male breast cancer: a multicenter retrospective study. Journal of Neuro-Oncology, 179(2), Article 73. https://doi.org/10.1007/s11060-026-05795-x

Image Credits: AI Generated

DOI: 10.1007/s11060-026-05795-x

Keywords: male breast cancer, brain metastases, stereotactic radiosurgery, local control, overall survival, Gamma Knife, radiation oncology, neuro-oncology, target volume, adverse radiation effects, Karnofsky Performance Status, multicenter study

The research team set out to characterize obesity within pediatric sleep medicine evaluations using a multicenter, real-world design, drawing on clinical data from three geographically and demographically distinct institutions: Rady Children’s Health in San Diego, Vanderbilt Children’s Hospital in Nashville, and Seattle Children’s Hospital. Rather than relying on the highly selected populations that populate randomized trials, the investigators analyzed children who were actually referred for sleep medicine care, a population that reflects the day-to-day reality of pediatric sleep clinics in the United States. The study received institutional review board exemption at all three participating centers, and the analysis was led by Landeo-Gutierrez and Maida Lynn Chen, with conceptualization and manuscript preparation contributions from Rakesh Bhattacharjee, Julie Ryu, Mariana Bedoya, and Erin MacKintosh.

The clinical stakes of this work are considerable. Obesity among children and adolescents in the United States has reached a prevalence that leading pediatric organizations now describe as a public health emergency, a framing advanced in a 2023 Pediatrics commentary by Emily Bomberg, Trina Kyle, and Fatima Cody Stanford. Against that backdrop, sleep disorders and obesity are not merely co-occurring conditions that happen to arrive in the same clinic; they are physiologically intertwined in ways that make each harder to treat in isolation. Understanding how frequently obesity appears among children evaluated in sleep clinics, and in what contexts, is therefore a question with direct implications for how pediatric sleep programs are staffed, how referrals are triaged, and how treatment plans are constructed.

The most extensively documented link between obesity and pediatric sleep pathology is obstructive sleep apnea, the condition in which the upper airway repeatedly narrows or collapses during sleep, interrupting breathing and fragmenting sleep architecture. In children with obesity, excess adipose tissue around the neck, tongue, and abdominal cavity increases mechanical load on the airway and reduces lung volumes, particularly in the supine position during rapid eye movement sleep, when muscle tone naturally falls. Adenotonsillar hypertrophy remains the classic driver of pediatric sleep apnea, but the obesity epidemic has shifted the epidemiology: an increasing proportion of children referred for snoring and suspected sleep-disordered breathing carry excess weight, and obesity-associated sleep apnea tends to be more persistent and less likely to resolve completely after tonsillectomy and adenoidectomy than the disease seen in lean children.

The relationship also runs in the opposite direction, a bidirectionality that has been established through large prospective studies. Systematic reviews and meta-analyses, including a 2018 synthesis by Maria del Carmen Miller, Francesco Cappuccio, and colleagues in the journal Sleep, and an updated dose-response meta-analysis by Xiaoli Deng and colleagues in Sleep Medicine in 2021, have consistently shown that short sleep duration in infants, children, and adolescents predicts subsequent weight gain and incident obesity. The proposed mechanisms are metabolic and behavioral at once: sleep restriction dysregulates the hormones leptin and ghrelin that govern appetite and satiety, increases insulin resistance, extends the waking window during which calories are consumed, and promotes fatigue that displaces physical activity. Cappuccio’s earlier 2008 meta-analysis in Sleep reached the same conclusion across both children and adults, cementing short sleep as a recognized modifiable risk factor for obesity.

Beyond apnea and sleep duration, obesity shapes nearly every other complaint that brings a child to a sleep clinic. A 2022 study by Kelly Duraccio, Dean Beebe, and colleagues in the Journal of Clinical Sleep Medicine examined clinically referred pediatric samples and found meaningful relationships between overweight and obesity status and insomnia severity, sleep quality, and the degree to which insomnia improved with treatment. Children with obesity also show poorer circadian health overall: a 2024 study in World Journal of Pediatrics by María Rodríguez-Martín, Nuria Martínez-Lozano, and colleagues applied a global circadian health score and found that children with obesity fared worse across multiple circadian dimensions, including sleep timing, meal timing, and light exposure patterns. These findings collectively suggest that obesity is not a single comorbidity to be noted in passing but a thread running through the entire fabric of pediatric sleep pathology.

Professional guidelines have begun to reflect this reality. The 2023 American Academy of Pediatrics clinical practice guideline for the evaluation and treatment of children and adolescents with obesity, authored by Sarah Hampl, Sandra Hassink, and an expert panel, recommends intensive health behavior and lifestyle treatment as the foundation of care, with pharmacotherapy and metabolic and bariatric surgery now endorsed as options for appropriate candidates. In adult sleep medicine, the American Thoracic Society’s 2018 clinical practice guideline on weight management for obstructive sleep apnea, led by David Hudgel and Sanjay Patel, formally established weight loss as a component of apnea treatment. Pediatric sleep medicine has been moving in the same direction, but the new multicenter analysis underscores how much of that work now happens, implicitly or explicitly, inside sleep clinics themselves.

Pharmacology is also changing the calculus. The 2024 SURMOUNT-OSA trial, published in the New England Journal of Medicine by Atul Malhotra, Ronald Grunstein, Ingo Fietze, and colleagues, demonstrated that tirzepatide, a dual glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist, significantly reduced the apnea-hypopnea index in adults with obstructive sleep apnea and obesity, with effects evident both among users and non-users of positive airway pressure therapy. The result electrified the sleep medicine community because it suggested that treating the metabolic disease could directly treat the sleep disorder. Whether incretin-based therapies will prove safe and effective for adolescents with obesity-associated sleep apnea remains an open question, but the adult evidence has already intensified interest in accurate weight characterization at the moment of pediatric sleep referral, precisely the kind of real-world data the new research letter provides.

The multicenter design of the study matters for how its insights should be read. Single-center pediatric sleep cohorts are inevitably shaped by local referral patterns, regional demographics, and institutional practice, so findings from three large programs in San Diego, Nashville, and Seattle carry more weight as a description of the national picture. The authors report that the data informing their figures and tables are available upon reasonable request, and the study was supported in part by a Robert A. Winn Excellence in Clinical Trials Career Development Award to the lead author and a Health Resources and Services Administration training grant supporting the Seattle team. The research letter format means the analysis is deliberately concise, but its framing points toward a larger conclusion: pediatric sleep medicine can no longer be practiced without embedded weight-related assessment and, ideally, integrated weight management pathways.

For clinicians and families, the practical message is one of shared vigilance. A child referred for snoring should have height, weight, and body mass index documented and interpreted against growth curves, because the presence of obesity changes the probability of sleep apnea, the likelihood of surgical cure, and the range of treatment options worth discussing. Conversely, a child being evaluated for obesity should be screened for snoring, witnessed apneas, daytime sleepiness, and sleep duration, because untreated sleep disorder can undermine even the most carefully constructed weight management plan. As the obesity epidemic continues to reshape pediatric medicine, studies like this one, grounded in the unselected reality of clinic populations rather than trial cohorts, provide the evidence base for that integration. The three-center collaboration behind the new analysis signals a growing recognition that the future of pediatric sleep medicine and the future of pediatric obesity care are, in a very literal sense, the same future.

Subject of Research: The prevalence and clinical implications of obesity among children evaluated in pediatric sleep medicine clinics

Article Title: Obesity in pediatric sleep medicine evaluations: insights from a real-world multicenter analysis

Article References: Obesity in pediatric sleep medicine evaluations: insights from a real-world multicenter analysis. (n.d.). https://doi.org/10.1007/s44470-026-00138-z

Image Credits: AI Generated

DOI: 10.1007/s44470-026-00138-z

Keywords: pediatric sleep medicine, obesity, obstructive sleep apnea, children, sleep duration, insomnia, circadian health, tirzepatide, adenotonsillectomy, weight management, multicenter study, Journal of Clinical Sleep Medicine

The study, coordinated by Volkan Hazar of Memorial Health Care in Antalya together with dozens of colleagues across the country, enrolled 132 children under 21 years of age who experienced their first relapse of acute lymphoblastic leukemia between February 2017 and June 2022. Patients were treated at 27 different centers nationwide, and their data were collected through a shared registry, giving researchers an unusually complete view of real-world practice outside the controlled environment of a single specialized hospital.

Each child was assigned to either a standard-risk or high-risk group based on well-established criteria, including how quickly the leukemia returned and where it reappeared. Of the total, 67 patients fell into the standard-risk category and 65 into the high-risk group. This risk stratification, a cornerstone of modern relapse therapy, is designed to intensify treatment for those least likely to respond while sparing others from unnecessary toxicity.

All patients were managed according to the ALL-IC REL 2016 guideline, a protocol developed through international collaboration that prescribes multi-agent chemotherapy induction followed by risk-adapted consolidation, often including hematopoietic stem cell transplantation. The researchers tracked several key endpoints: whether children achieved a second complete remission, how long they survived without new events, and how many died from complications of treatment itself.

The headline result is that 81.8 percent of patients achieved a second complete remission after induction, although 17.4 percent failed to reach remission at all. Achieving remission is the essential gateway to potentially curative consolidation, typically transplantation, so a success rate above 80 percent confirms that the protocol remains feasible and effective at re-establishing disease control for the majority of relapsed patients, even in a middle-income setting.

The estimated five-year overall survival for the entire cohort was 51.4 percent, with event-free survival of 43.2 percent. That means roughly half of the children treated under this protocol were alive five years after relapse, a figure that reflects both genuine therapeutic progress and the persistent lethality of relapsed disease. During follow-up, 37.1 percent of patients suffered a second relapse, and 64 of the 132 children died over the study period.

The risk-group divide proved stark. Standard-risk patients enjoyed a five-year overall survival of 65.4 percent and event-free survival of 57.3 percent, while their high-risk counterparts fared far worse, with corresponding rates of just 37.5 percent and 29.0 percent. Both differences were highly statistically significant. The authors conclude that the ALL-IC REL 2016 guideline delivered encouraging outcomes for standard-risk children but left a substantial gap for the high-risk group.

Two factors emerged as powerful predictors of poor outcome: very early relapse, meaning the leukemia returned shortly after initial treatment, and age of 10 years or older at the time of relapse. Additionally, measurable residual disease detected by flow cytometry at the end of induction, at a threshold of 0.1 percent or higher, showed an adverse trend for both overall and event-free survival. Minimal residual disease, the microscopic trace of leukemia cells that survives therapy, is increasingly recognized as one of the most informative prognostic markers in relapsed ALL, capable of revealing treatment failure long before overt relapse.

The study also sounded an alarm about treatment-related mortality and deaths occurring while patients were officially in remission. These deaths, often driven by infections and organ toxicity during intensive chemotherapy or following transplantation, remained substantial in the Turkish cohort. Such losses underscore that survival in relapsed leukemia depends not only on eradicating the cancer but also on the quality of supportive care, including infection prevention, transfusion support, and intensive care availability.

Perhaps the most consequential implication of the study concerns access to modern immunotherapies. Agents such as blinatumomab, inotuzumab ozogamicin, and chimeric antigen receptor T-cell therapy have transformed outcomes for high-risk relapsed ALL in high-income countries, but they remain difficult to access in many parts of the world. The authors argue that the survival gap they documented for high-risk patients highlights the urgent need for standardized minimal residual disease monitoring, improved supportive care, refined transplantation strategies, and broader access to immunotherapy. As real-world evidence accumulates from diverse health systems, studies like this one provide an essential benchmark for measuring progress toward closing the survival gap between children treated in wealthy nations and those treated elsewhere.

Subject of Research: Real-world outcomes of pediatric first-relapsed acute lymphoblastic leukemia treated under the ALL-IC REL 2016 guideline in Türkiye

Article Title: Real-world outcomes of children with first relapsed acute lymphoblastic leukemia treated according to the ALL-IC REL 2016 guideline in Türkiye

Article References: Hazar, V., Güneş, A. M., Yaralı, H. N., Yalçın, K., Küpesiz, F. T., Karapınar, T. H., Ayçiçek, A., Zengin, E., Evim, M. S., Özbek, N. Y., Yılmaz, B., Özdemir, Z. C., Karasu, G. T., Küpesiz, O. A., Yıldırım, Z. K., Bıçakçı, Z., Kebudi, R., Özek, G., Tokgöz, H., … Gülen, H. (2026). Real-world outcomes of children with first relapsed acute lymphoblastic leukemia treated according to the ALL-IC REL 2016 guideline in Türkiye. Annals of Hematology. https://doi.org/10.1007/s00277-026-07281-w

Image Credits: AI Generated

DOI: 10.1007/s00277-026-07281-w

Keywords: relapsed acute lymphoblastic leukemia, pediatric oncology, ALL-IC REL 2016, minimal residual disease, hematopoietic stem cell transplantation, treatment-related mortality, overall survival, event-free survival, risk stratification, immunotherapy access, multicenter study, Türkiye

LVI describes the presence of tumor cell clusters inside endothelial-lined lymphatic vessels or blood vessels surrounding an invasive breast cancer. It is an independent predictor of local recurrence, distant metastasis, and poor prognosis, yet confirming it today depends entirely on postoperative pathology. Surgeons learn whether tumor cells had already entered vessels only after the tumor has been removed, which limits their ability to fine-tune the extent of axillary lymph node dissection or to personalize adjuvant treatment decisions. A reliable preoperative, noninvasive estimate of LVI status has therefore been a long-standing unmet need in breast oncology.

The new study tackles that gap using dynamic contrast-enhanced magnetic resonance imaging, or DCE-MRI, already a core preoperative modality thanks to its exceptional soft-tissue resolution and its sensitivity to tumor vascularization. The researchers combined DCE-MRI with radiomics, a technique that extracts large numbers of quantitative image features invisible to the human eye, and with machine learning, allowing algorithms to decode tumor heterogeneity from routine scans. While earlier efforts have used mammography-based tomosynthesis or single-center MRI cohorts, systematic comparisons of many algorithms on multicenter DCE-MRI data, with rigorous external validation, remained scarce.

Retrospectively, the team assembled 912 female patients aged 23 to 81 years from two independent medical centers, Guangdong Maternal and Child Health Hospital and The First Affiliated Hospital of Jinan University, all scanned with a Philips 3.0T scanner within two weeks before surgery. Data from 757 patients at the first center formed the model development set, split 7:3 into training and internal validation subsets using stratified sampling on LVI status. Data from 155 patients at the second center served as a completely unseen external test set, a design that directly probes how well the model generalizes to a different hospital population rather than merely memorizing patterns from its own data.

The radiomics pipeline began with manual, blinded contouring of the entire tumor on the arterial phase of the six-phase contrast sequence, producing a three-dimensional volume of interest reviewed by senior radiologists. Using PyRadiomics, the team extracted 1,197 features per patient, spanning 234 histogram, 14 morphological, 884 texture, and 65 higher-order descriptors. A multistep reduction process followed: correlation filtering removed redundant features, univariate analyses retained only those significantly associated with LVI, and LASSO regression with 10-fold cross-validation ultimately selected 18 features with the highest predictive value for modeling.

Crucially, the researchers did not commit to a single algorithm. They built and systematically compared 10 machine learning models, including logistic regression, support vector machine, K-nearest neighbors, random forest, ExtraTrees, XGBoost, LightGBM, gradient boosting, AdaBoost, and multilayer perceptron, tuning each via grid search and comparing them with ROC analysis and the DeLong test. The ExtraTrees model emerged as the best radiomics performer, achieving an AUC of 0.653 and accuracy of 0.640 on the validation set, a deliberately conservative benchmark compared with many single-center studies that report higher numbers without independent external testing.

In parallel, multivariate logistic regression identified three independent clinical risk factors for LVI: sentinel lymph node status, estrogen receptor status, and the time-intensity curve pattern of contrast enhancement. The team then integrated the ExtraTrees radiomics score with these clinical predictors to construct a combined model, visualized as a practical nomogram for individualized bedside estimation of LVI probability. The combined model outperformed either the radiomics or clinical model alone across all cohorts, reaching an AUC of 0.796 on the training set, 0.704 on internal validation, and 0.703 on the external test set, with calibration curves and decision curve analysis confirming good agreement and clinical net benefit across a broad range of threshold probabilities.

The authors argue that their relatively modest external AUC values are not a weakness but a feature of honest validation. Many published radiomics studies reporting AUCs above 0.80 relied on single-center data, lenient validation schemes, or highly homogeneous patient subsets. By enrolling all molecular subtypes, including luminal A, luminal B, HER2-overexpressing, and triple-negative cancers, and by testing on a genuinely independent center with real-world data heterogeneity, the study offers a more realistic assessment of how such models behave outside their birthplace. The researchers also note that no dedicated image harmonization strategy, such as ComBat, was applied before feature extraction, which may partly explain the performance drop on external data and marks a target for future improvement.

Limitations remain. The retrospective design carries inherent selection bias, the external cohort was relatively small, and tumor delineation still depends on manual contouring by experienced radiologists, a process that is time-consuming and subject to inter-observer variability. The two centers also used the same scanner vendor, and prospective validation in larger, more diverse populations will be essential before routine clinical deployment. The team outlines next steps that include incorporating diffusion-weighted MRI parameters, applying explainable AI to reveal the imaging basis of model decisions, and integrating the tool into clinical decision support systems to measure its actual impact on surgical planning and patient outcomes.

Even with those caveats, the study delivers a clinically meaningful proof of concept: a noninvasive, preoperative estimate of lymphovascular invasion is achievable when carefully selected radiomic features from DCE-MRI are combined with independent clinical risk factors and validated the hard way. For patients, that could mean smarter surgical decisions and more personalized adjuvant therapy planned before the operation rather than pieced together after it. For the growing field of radiomics, it is a reminder that multicenter external validation, systematic algorithm comparison, and honest reporting of performance are what separate a promising research model from one ready for the clinic.

Subject of Research: Preoperative prediction of lymphovascular invasion in breast cancer using DCE-MRI radiomics and machine learning

Article Title: Machine Learning Comparison and Combined Model Optimization Based on DCE‐MRI Radiomics for Preoperative Assessment of Lymphovascular Invasion in Breast Cancer: A Multicenter Study

Article References: Li, H., Xiao, Q., Zeng, Y., Wang, X., & Zhang, Y. (2026). Machine Learning Comparison and Combined Model Optimization Based on DCE ‐ MRI Radiomics for Preoperative Assessment of Lymphovascular Invasion in Breast Cancer: A Multicenter Study. Cancer Reports, 9(9), Article e70678. https://doi.org/10.1002/cnr2.70678

Image Credits: AI Generated

DOI: 10.1002/cnr2.70678

Keywords: breast cancer, lymphovascular invasion, DCE-MRI, radiomics, machine learning, ExtraTrees, nomogram, multicenter study, external validation, clinical risk factors, LASSO regression, preoperative assessment

The research, led by Chonggang Tong and Yuwei Su of the Beijing University of Posts and Telecommunications, together with colleagues, focused on homotopic functional connectivity, or HFC, the degree to which mirror-image regions in the left and right hemispheres synchronize their activity. This direct communication between corresponding brain areas is fundamental to integrating information across the two halves of the brain, supporting everything from motor coordination to language and attention. While previous studies had hinted at HFC alterations in Alzheimer’s disease, most were confined to small cohorts and simple statistical comparisons, producing inconsistent and often contradictory findings.

To overcome these limitations, the team assembled a dataset of 799 subjects drawn from seven different imaging sites, comprising 289 individuals with Alzheimer’s disease, 253 with mild cognitive impairment, and 257 cognitively normal controls. This scale matters. Multicenter designs introduce considerable variability in scanner hardware, acquisition protocols and participant demographics, but they also provide the statistical power and generalizability that small single-site studies lack. By pooling results across sites using random-effects meta-analysis, the researchers could distinguish robust disease effects from site-specific noise.

The team’s methodological pipeline began with functional magnetic resonance imaging, measuring blood-oxygen-level-dependent signals while participants rested in the scanner. From these data, they computed HFC for every participant, quantifying the temporal correlation between homotopic pairs of brain regions. They also derived a suite of structural asymmetry measures from structural MRI, including gray matter volume, fractal dimension, cortical thickness, sulcal depth and gyral index, allowing them to ask whether functional changes in cross-hemisphere communication track with structural differences between hemispheres.

For each imaging site, the researchers ran linear regression models with diagnosis as the main effect of interest and age and sex as covariates, then combined the resulting effect sizes across all seven sites through meta-analysis. The pattern that emerged was unambiguous and hierarchically organized. In posterior and subcortical regions, HFC was systematically reduced in Alzheimer’s patients. The reduction was particularly pronounced in the right hippocampus, with a Cohen’s d effect size of −0.541, and in the medial amygdala, with a Cohen’s d of −0.330, both surviving correction for false discovery rate. These regions, which include structures central to memory processing, showed the earliest and strongest erosion of interhemispheric synchronization.

In contrast, a focal and unexpected increase in HFC appeared in the prefrontal cortex, specifically in the medial anterior prefrontal area A9m, where the effect size reached a Cohen’s d of 0.391. This anterior-posterior gradient, with posterior and subcortical connectivity collapsing while certain prefrontal connections are strengthened, suggests that Alzheimer’s disease does not simply degrade cross-hemisphere communication uniformly. Instead, the brain appears to undergo a hierarchical reconfiguration, possibly reflecting compensatory mechanisms in frontal regions that attempt to offset deteriorating posterior networks, or perhaps a pathological redistribution of neural resources as the disease progresses.

Beyond mapping this pattern, the team tested whether HFC could serve as a practical diagnostic biomarker. They trained support vector machines, a widely used machine learning algorithm, to classify individuals as having Alzheimer’s disease or not, based on their HFC profiles. Crucially, they employed leave-one-site-out cross-validation, training the classifier on data from six sites and testing it on the held-out seventh, cycling through all seven configurations. This rigorous scheme ensures that the reported performance reflects genuine disease signals rather than scanner-specific artifacts. The classifier achieved a mean accuracy of 0.745 across sites, with an area under the curve of 0.815 and an F1 score of 0.774.

The researchers then asked whether adding structural asymmetry measures would sharpen the model’s diagnostic power. It did. Integrating gray matter volume, cortical thickness and the other structural metrics with HFC improved classification accuracy by up to 0.129, indicating that functional and structural signatures of hemispheric asymmetry carry complementary information about the disease. In a parallel analysis, support vector regression was applied to predict individual Mini-Mental State Examination scores, the standard bedside measure of cognitive status, from the same imaging features, probing whether the biomarker could capture disease severity rather than just diagnostic category.

The implications extend beyond the laboratory. Current biomarkers for Alzheimer’s disease, including cerebrospinal fluid assays and PET amyloid imaging, are expensive and invasive, while structural MRI alone captures late-stage neurodegeneration. A resting-state fMRI measure of homotopic connectivity, requiring no contrast agent and only a few minutes of scanning, could offer a cost-effective complement for early detection and for monitoring response to the growing arsenal of disease-modifying therapies. The finding that mild cognitive impairment sits between controls and Alzheimer’s disease in this hierarchy of connectivity changes further suggests HFC may track disease progression.

The study’s authors, whose work was supported by China’s National Science and Technology Major Project and the National Natural Science Foundation of China, caution that HFC is not yet a standalone diagnostic tool. Effect sizes at the individual level remain moderate, and clinical deployment will require validation in independent cohorts and harmonization of acquisition protocols. Nevertheless, the demonstration that interhemispheric dialogue is hierarchically reconfigured in Alzheimer’s disease, reproducibly across seven sites and nearly eight hundred brains, deepens understanding of the neural mechanisms underlying the disease and provides a concrete, measurable target for future therapeutic investigations and individualized assessment.

Subject of Research: Multicenter analysis of homotopic functional connectivity changes between brain hemispheres in Alzheimer's disease

Article Title: Hierarchical reconfiguration of interhemispheric dialogue in Alzheimer’s disease: a multicenter analysis

Article References: Tong, C., Su, Y., Zhang, W., Hu, P., Zhao, C., Liu, Y., & Zhong, S. (2026). Hierarchical reconfiguration of interhemispheric dialogue in Alzheimer’s disease: a multicenter analysis. BMC Medicine. https://doi.org/10.1186/s12916-026-05234-8

Image Credits: AI Generated

DOI: 10.1186/s12916-026-05234-8

Keywords: Alzheimer's disease, homotopic functional connectivity, interhemispheric communication, neuroimaging biomarker, resting-state fMRI, mild cognitive impairment, support vector machine, multicenter study, brain asymmetry, hippocampus, prefrontal cortex, machine learning

The research, led by Belarmino Gonçalves of the Portuguese Oncology Institute of Porto and Thiago Franchi Nunes of Interventix in Campo Grande, Brazil, brought together ten tertiary referral centers across South America and Europe. Between January 2018 and July 2025, the investigators analyzed 68 diagnostic percutaneous transhepatic cholangioscopy, or PTCS, procedures performed in patients whose cross-sectional imaging and prior endoscopic evaluation had been nondiagnostic, or whose anatomy made standard endoscopic access impossible. Crucially, cases performed primarily to treat gallstones were excluded, isolating a cohort in which the sole purpose of the camera voyage into the ducts was to determine whether cancer was present.

The technique itself is a remarkable feat of interventional radiology. Using ultrasound and fluoroscopic guidance, physicians thread a needle through the liver into the bile ducts and establish a percutaneous tract, typically secured with a 10 to 12 French introducer sheath. Through that sheath, flexible cholangioscopes, single-operator platforms, or single-use ultra-slim endoscopes measuring roughly 2.8 to 3.5 millimeters in outer diameter are advanced directly into the biliary tree. Saline irrigation clears the field, allowing the operator to inspect the duct lining in real time — something computed tomography and magnetic resonance cholangiopancreatography fundamentally cannot do, since they offer only indirect views of the biliary mucosa. Some centers perform the cholangioscopic inspection in the same session when tract and sheath conditions permit; others prefer a staged approach roughly 48 to 72 hours later to allow decompression and reduce infection risk in patients with cholangitis or complex anatomy.

During each procedure, operators recorded two kinds of optical judgments before any tissue results were known. The first was a global impression — a binary real-time call of benign versus malignant that integrated everything seen during the examination. The second was a checklist of five predefined visual criteria: tumor vessels appearing as tortuous neovessels, hypervascular mucosa, nodular or polypoid masses, papillary projections, and infiltrative lesions marked by irregular mucosa and loss of normal duct architecture. When recorded images or videos were available, blinded investigators independently reviewed the material against the checklist, with disagreements resolved by consensus, adding a layer of methodological rigor to what has historically been a subjective art.

The results against the gold standard of histopathology were striking. Malignancy was ultimately confirmed in 57 of the 68 procedures, reflecting the referral-enriched, high-risk nature of the population. Against that benchmark, the operator’s global impression achieved 84.2 percent sensitivity, 90.9 percent specificity, and 85.3 percent accuracy. Most notable was the positive predictive value of 98.0 percent: when an experienced operator called a lesion malignant on direct visualization, that call was almost always right. The negative predictive value of 52.6 percent, by contrast, shows that a benign-appearing duct cannot safely rule out cancer — tissue sampling remains essential. The authors caution that these predictive values must be interpreted in light of the unusually high cancer prevalence in this cohort.

Among the individual visual criteria, two emerged as the most trustworthy warning signs. An infiltrative appearance showed 90.9 percent specificity and was strongly associated with malignant histopathology, carrying an odds ratio of 13.75 and a positive predictive value of 97.1 percent. Tumor vessels were also significantly linked to cancer, with an odds ratio of 4.57. Hypervascular mucosa, by comparison, offered little discriminatory power. The researchers then explored combined decision rules: using the permissive rule of tumor vessels or infiltrative appearance raised sensitivity to 84.2 percent at moderate specificity, while the restrictive rule requiring both features achieved 100 percent specificity — a powerful rule-in finding when tissue is scarce — albeit with sensitivity dropping to 36.8 percent. These PTCS-specific heuristics remain hypothesis-generating and await prospective validation.

Safety data were equally informative. Adverse events occurred in 10 of 68 procedures, or 14.7 percent, graded using the modified CIRSE classification system. Two events were grade I, five were grade II, and three were grade IV — the latter all infectious complications requiring intensive care-level support such as vasopressors or ventilation, rather than mechanical injury from the instruments themselves. The predominance of low-grade complications underscores the importance of standardized antibiotic prophylaxis, careful biliary decompression, controlled irrigation strategies, and structured post-procedure monitoring for anyone undergoing antegrade cholangioscopy.

The study’s context matters. In patients with surgically altered anatomy — bilioenteric anastomoses or Roux-en-Y reconstructions accounted for nearly a third of the cohort — conventional endoscopic retrograde cholangiopancreatography is often impossible or has already failed. Traditional blind or fluoroscopy-guided biopsies perform poorly for infiltrative, flat, or submucosal tumors, frequently returning nondiagnostic or discordant samples. Prior meta-analyses have shown that cholangioscopy-guided targeted biopsy outperforms fluoroscopy-guided sampling for indeterminate strictures, and consensus guidelines now frame cholangioscopy as a problem-solving tool. What has been missing, the authors argue, is multicenter real-world evidence about how the percutaneous, antegrade version of the technique performs across diverse devices, operators, and health systems — a gap this Brazil-and-Europe network directly addresses.

The investigators are candid about the limitations. The retrospective design limits control of confounding and standardization, and partial verification bias is possible. The high prevalence of malignancy limits generalizability to lower-risk populations, and procedural heterogeneity — different scopes, sheath sizes, sedation protocols, and timing — reflects the reality of a varied referral network but complicates interpretation. Confidence intervals around some analyses were wide, and inter-observer reproducibility was not formally assessed. Still, the single-session design, which avoided within-patient clustering, and the combination of operator impression with structured criteria strengthen the findings considerably.

Looking ahead, the authors call for prospective validation of PTCS-specific optical reporting frameworks, standardized documentation of procedural variables such as tract maturation and irrigation strategy, and quantification of how cholangioscopic findings actually change patient management. Emerging technologies, including standardized image annotation and artificial intelligence-assisted pattern recognition, could sharpen interobserver agreement and refine the visual criteria tailored to percutaneous referral populations. For now, the message for patients with mysterious bile duct blockages is encouraging: a camera threaded through the liver, guided by a trained eye and a disciplined checklist, can bring clarity where scans and standard endoscopy leave only doubt — with a safety profile that is, in most cases, reassuringly benign.

Subject of Research: Diagnostic performance and safety of percutaneous transhepatic cholangioscopy for complex, indeterminate biliary lesions

Article Title: Percutaneous transhepatic cholangioscopy for complex biliary lesions: multicenter real-world diagnostic performance and safety study

Article References: Percutaneous transhepatic cholangioscopy for complex biliary lesions: multicenter real-world diagnostic performance and safety study. (n.d.). https://doi.org/10.1007/s44343-026-00045-3

Image Credits: AI Generated

DOI: 10.1007/s44343-026-00045-3

Keywords: percutaneous transhepatic cholangioscopy, biliary strictures, cholangiocarcinoma, indeterminate biliary lesions, targeted biopsy, interventional radiology, diagnostic accuracy, adverse events, multicenter study, bile duct cancer, Percutaneous, transhepatic