AIMC Topic: Brain Neoplasms

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Postoperative Karnofsky performance status prediction in patients with IDH wild-type glioblastoma: A multimodal approach integrating clinical and deep imaging features.

PloS one
BACKGROUND AND PURPOSE: Glioblastoma is a highly aggressive brain tumor with limited survival that poses challenges in predicting patient outcomes. The Karnofsky Performance Status (KPS) score is a valuable tool for assessing patient functionality an...

Deep learning based apparent diffusion coefficient map generation from multi-parametric MR images for patients with diffuse gliomas.

Medical physics
PURPOSE: Apparent diffusion coefficient (ADC) maps derived from diffusion weighted magnetic resonance imaging (DWI MRI) provides functional measurements about the water molecules in tissues. However, DWI is time consuming and very susceptible to imag...

Segmentation and classification of brain tumor using Taylor fire hawk optimization enabled deep learning approach.

Electromagnetic biology and medicine
The brain is a crucial organ that controls the body's neural system. The tumor develops and spreads across the brain as a result of irregular cell generation. The provision of substantial treatment to patients requires the early diagnosis of malignan...

The Segment Anything foundation model achieves favorable brain tumor auto-segmentation accuracy in MRI to support radiotherapy treatment planning.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
BACKGROUND: Promptable foundation auto-segmentation models like Segment Anything (SA, Meta AI, New York, USA) represent a novel class of universal deep learning auto-segmentation models that could be employed for interactive tumor auto-contouring in ...

FT-FEDTL: A fine-tuned feature-extracted deep transfer learning model for multi-class microwave-based brain tumor classification.

Computers in biology and medicine
The microwave brain imaging (MBI) system is an emerging technology used to detect brain tumors in their early stages. Multi-class microwave-based brain tumor (MBT) identification and classification are crucial due to the tumor's patterns and shape. M...

Enhancing MRI brain tumor classification: A comprehensive approach integrating real-life scenario simulation and augmentation techniques.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Brain cancer poses a significant global health challenge, with mortality rates showing a concerning surge over recent decades. The incidence of brain cancer-related mortality has risen from 140,000 to 250,000, accompanied by a doubling in new diagnos...

Efficient brain tumor grade classification using ensemble deep learning models.

BMC medical imaging
Detecting brain tumors early on is critical for effective treatment and life-saving efforts. The analysis of the brain with MRI scans is fundamental to the diagnosis because it contains detailed structural views of the brain, which is vital in identi...

Development of a web-based tool for estimating individualized survival curves in glioblastoma using clinical, mRNA, and tumor microenvironment features with fusion techniques.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
OBJECTIVE: Glioblastoma (GBM), one of the most common brain tumors, is known for its low survival rates and poor treatment responses. This study aims to create a robust predictive model that integrates multiple feature types, including clinical data,...

Machine learning approach to assess brain metastatic burden in preclinical models.

Methods in cell biology
Brain metastases (BrM) occur when malignant cells spread from a primary tumor located in other parts of the body to the brain. BrM is a deadly complication for cancer patients and severely lacks effective therapies. Due to the limited access to patie...

Machine learning-based new classification for immune infiltration of gliomas.

PloS one
BACKGROUND: Glioma is a highly heterogeneous and poorly immunogenic malignant tumor, with limited efficacy of immunotherapy. The characteristics of the immunosuppressive tumor microenvironment (TME) are one of the important factors hindering the effe...