Medical large language models are vulnerable to data-poisoning attacks.

The adoption of large language models (LLMs) in healthcare demands a careful analysis of their potential to spread false medical knowledge. Because LLMs ingest massive volumes of data from the open Internet during training, they are potentially exposed to unverified medical knowledge that may include deliberately planted misinformation. Here, we perform a threat assessment that simulates a data-poisoning attack against The Pile, a popular dataset used for LLM development.

Congress of Neurological Surgeons systematic review and evidence based guideline on neuropathology for WHO grade II diffuse glioma: update.

Unlabelled: QUESTIONS AND RECOMMENDATIONS FROM THE PRIOR VERSION OF THESE GUIDELINES WITHOUT CHANGE: TARGET POPULATION: Adult patients (age ≥ 18 years) who have suspected low-grade diffuse glioma.

Question: What are the optimal neuropathological techniques to diagnose low-grade diffuse glioma in the adult?

Recommendation: Level I Histopathological analysis of a representative surgical sample of the lesion should be used to provide the diagnosis of low-grade diffuse glioma. Level III Both frozen section and cytopathologic/smear evaluation should be used to aid the intra-operative assessment of low-grade diffuse glioma diagnosis.

Stimulated Raman Histology and Artificial Intelligence Provide Near Real-Time Interpretation of Radical Prostatectomy Surgical Margins.

Introduction: Balancing surgical margins and functional outcomes is crucial during radical prostatectomy for prostate cancer. Stimulated Raman Histology (SRH) is a novel, real-time imaging technique that provides histologic images of fresh, unprocessed, and unstained tissue within minutes, which can be interpreted by either humans or artificial intelligence.

Methods: Twenty-two participants underwent robotic-assisted laparoscopic radical prostatectomy (RALP) with intraoperative SRH surgical bed assessment.

Foundation models for fast, label-free detection of glioma infiltration.

A critical challenge in glioma treatment is detecting tumour infiltration during surgery to achieve safe maximal resection. Unfortunately, safely resectable residual tumour is found in the majority of patients with glioma after surgery, causing early recurrence and decreased survival. Here we present FastGlioma, a visual foundation model for fast (<10 s) and accurate detection of glioma infiltration in fresh, unprocessed surgical tissue.

Intraoperative margin assessment with near real time pathology during partial gland ablation of prostate cancer: A feasibility study.

Background: In-field or in-margin recurrence after partial gland cryosurgical ablation (PGCA) of prostate cancer (PCa) remains a limitation of the paradigm. Stimulated Raman histology (SRH) is a novel microscopic technique allowing real time, label-free, high-resolution microscopic images of unprocessed, un-sectioned tissue which can be interpreted by humans or artificial intelligence (AI). We evaluated surgical team and AI interpretation of SRH for real-time pathologic feedback in the planning and treatment of PCa with PGCA.

Localization of protoporphyrin IX during glioma-resection surgery via paired stimulated Raman histology and fluorescence microscopy.

The most widely used fluorophore in glioma-resection surgery, 5-aminolevulinic acid (5-ALA), is thought to cause the selective accumulation of fluorescent protoporphyrin IX (PpIX) in tumour cells. Here we show that the clinical detection of PpIX can be improved via a microscope that performs paired stimulated Raman histology and two-photon excitation fluorescence microscopy (TPEF). We validated the technique in fresh tumour specimens from 115 patients with high-grade gliomas across four medical institutions.

Ultra-Rapid Droplet Digital PCR Enables Intraoperative Tumor Quantification.

The diagnosis and treatment of tumors often depends on molecular-genetic data. However, rapid and iterative access to molecular data is not currently feasible during surgery, complicating intraoperative diagnosis and precluding measurement of tumor cell burdens at surgical margins to guide resections. To address this gap, we developed Ultra-Rapid droplet digital PCR (UR-ddPCR), which can be completed in 15 minutes from tissue to result with an accuracy comparable to standard ddPCR.

T2-FLAIR Mismatch Sign Predicts DNA Methylation Subclass and CDKN2A/B Status in IDH-Mutant Astrocytomas.

Purpose: DNA methylation profiling stratifies isocitrate dehydrogenase (IDH)-mutant astrocytomas into methylation low- and high-grade groups. We investigated the utility of the T2-fluid-attenuated inversion recovery (T2-FLAIR) mismatch sign for predicting DNA methylation grade and cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion, a molecular biomarker for grade 4 IDH-mutant astrocytomas, according to the 2021 World Health Organization classification.

Experimental Design: Preoperative MRI scans of IDH-mutant astrocytomas subclassified by DNA methylation profiling (n = 71) were independently evaluated by two radiologists for the T2-FLAIR mismatch sign.

Prognostic value of DNA methylation subclassification, aneuploidy, and CDKN2A/B homozygous deletion in predicting clinical outcome of IDH mutant astrocytomas.

Background: Isocitrate dehydrogenase (IDH) mutant astrocytoma grading, until recently, has been entirely based on morphology. The 5th edition of the Central Nervous System World Health Organization (WHO) introduces CDKN2A/B homozygous deletion as a biomarker of grade 4. We sought to investigate the prognostic impact of DNA methylation-derived molecular biomarkers for IDH mutant astrocytoma.

Impact of Rare and Multiple Concurrent Gene Fusions on Diagnostic DNA Methylation Classifier in Brain Tumors.

Unlabelled: DNA methylation is an essential molecular assay for central nervous system (CNS) tumor diagnostics. While some fusions define specific brain tumors, others occur across many different diagnoses. We performed a retrospective analysis of 219 primary CNS tumors with whole genome DNA methylation and RNA next-generation sequencing.

Hierarchical discriminative learning improves visual representations of biomedical microscopy.

Learning high-quality, self-supervised, visual representations is essential to advance the role of computer vision in biomedical microscopy and clinical medicine. Previous work has focused on self-supervised representation learning (SSL) methods developed for instance discrimination and applied them directly to image patches, or fields-of-view, sampled from gigapixel whole-slide images (WSIs) used for cancer diagnosis. However, this strategy is limited because it (1) assumes patches from the same patient are independent, (2) neglects the patient-slide-patch hierarchy of clinical biomedical microscopy, and (3) requires strong data augmentations that can degrade downstream performance.

Unlocking glioma genetics with deep learning.

The AI era in medicine has ushered in new opportunities to improve the diagnosis and treatment of human disease. CHARM, an AI algorithm described in this issue, has the potential to streamline molecular classification, intraoperative diagnosis, surgical decision making, and trial enrollment for glioma patients.

Clinical utility of whole-genome DNA methylation profiling as a primary molecular diagnostic assay for central nervous system tumors-A prospective study and guidelines for clinical testing.

Background: Central nervous system (CNS) cancer is the 10th leading cause of cancer-associated deaths for adults, but the leading cause in pediatric patients and young adults. The variety and complexity of histologic subtypes can lead to diagnostic errors. DNA methylation is an epigenetic modification that provides a tumor type-specific signature that can be used for diagnosis.

Stimulated Raman histology as a method to determine the adequacy of renal mass biopsy and identify malignant subtypes of renal cell carcinoma.

Introduction: Renal tumor biopsy requires adequate tissue sampling to aid in the investigation of small renal masses. In some centers the contemporary nondiagnostic renal mass biopsy rate may be as high as 22% and may be as high as 42% in challenging cases. Stimulated Raman Histology (SRH) is a novel microscopic technique which has created the possibility for rapid, label-free, high-resolution images of unprocessed tissue which may be viewed on standard radiology viewing platforms.

Stimulated Raman histology, a novel method to allow for rapid pathologic examination of unprocessed, fresh prostate biopsies.

Introduction: Delay between targeted prostate biopsy (PB) and pathologic diagnosis can lead to a concern of inadequate sampling and repeated biopsy. Stimulated Raman histology (SRH) is a novel microscopic technique allowing real-time, label-free, high-resolution microscopic images of unprocessed, unsectioned tissue. This technology holds potential to decrease the time for PB diagnosis from days to minutes.

OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology.

Accurate intraoperative diagnosis is essential for providing safe and effective care during brain tumor surgery. Our standard-of-care diagnostic methods are time, resource, and labor intensive, which restricts access to optimal surgical treatments. To address these limitations, we propose an alternative workflow that combines stimulated Raman histology (SRH), a rapid optical imaging method, with deep learning-based automated interpretation of SRH images for intraoperative brain tumor diagnosis and real-time surgical decision support.

Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging.

Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic testing for patients with brain tumors is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. In this study, we developed DeepGlioma, a rapid (<90 seconds), artificial-intelligence-based diagnostic screening system to streamline the molecular diagnosis of diffuse gliomas.

Toward digital histopathological assessment in surgery for central nervous system tumors using stimulated Raman histology.

Objective: Intraoperative neuropathological assessment with conventional frozen sections supports the neurosurgeon in optimizing the surgical strategy. However, preparation and review of frozen sections can take as long as 45 minutes. Stimulated Raman histology (SRH) was introduced as a novel technique to provide rapid high-resolution digital images of unprocessed tissue samples directly in the operating room that are comparable to conventional histopathological images.

Association of hyperglycemia and molecular subclass on survival in IDH-wildtype glioblastoma.

Background: Hyperglycemia has been associated with worse survival in glioblastoma. Attempts to lower glucose yielded mixed responses which could be due to molecularly distinct GBM subclasses.

Methods: Clinical, laboratory, and molecular data on 89 IDH-wt GBMs profiled by clinical next-generation sequencing and treated with Stupp protocol were reviewed.

Rapid Automated Analysis of Skull Base Tumor Specimens Using Intraoperative Optical Imaging and Artificial Intelligence.

Background: Accurate specimen analysis of skull base tumors is essential for providing personalized surgical treatment strategies. Intraoperative specimen interpretation can be challenging because of the wide range of skull base pathologies and lack of intraoperative pathology resources.

Objective: To develop an independent and parallel intraoperative workflow that can provide rapid and accurate skull base tumor specimen analysis using label-free optical imaging and artificial intelligence.

A Data-Driven Approach to Predicting 5-Aminolevulinic Acid-Induced Fluorescence and World Health Organization Grade in Newly Diagnosed Diffuse Gliomas.

Background: A growing body of evidence has revealed the potential utility of 5-aminolevulinic acid (5-ALA) as a surgical adjunct in selected lower-grade gliomas. However, a reliable means of identifying which lower-grade gliomas will fluoresce has not been established.

Objective: To identify clinical and radiological factors predictive of intraoperative fluorescence in intermediate-grade gliomas.