Deep Learning for Detecting Brain Metastases on MRI: A Systematic Review and Meta-Analysis.
Burak Berksu OzkaraMelissa M ChenChristian FederauMert KarabacakTina M BriereJing LiMax WintermarkPublished in: Cancers (2023)
Since manual detection of brain metastases (BMs) is time consuming, studies have been conducted to automate this process using deep learning. The purpose of this study was to conduct a systematic review and meta-analysis of the performance of deep learning models that use magnetic resonance imaging (MRI) to detect BMs in cancer patients. A systematic search of MEDLINE, EMBASE, and Web of Science was conducted until 30 September 2022. Inclusion criteria were: patients with BMs; deep learning using MRI images was applied to detect the BMs; sufficient data were present in terms of detective performance; original research articles. Exclusion criteria were: reviews, letters, guidelines, editorials, or errata; case reports or series with less than 20 patients; studies with overlapping cohorts; insufficient data in terms of detective performance; machine learning was used to detect BMs; articles not written in English. Quality Assessment of Diagnostic Accuracy Studies-2 and Checklist for Artificial Intelligence in Medical Imaging was used to assess the quality. Finally, 24 eligible studies were identified for the quantitative analysis. The pooled proportion of patient-wise and lesion-wise detectability was 89%. Articles should adhere to the checklists more strictly. Deep learning algorithms effectively detect BMs. Pooled analysis of false positive rates could not be estimated due to reporting differences.
Keyphrases
- deep learning
- artificial intelligence
- brain metastases
- machine learning
- magnetic resonance imaging
- big data
- convolutional neural network
- contrast enhanced
- small cell lung cancer
- case control
- case report
- diffusion weighted imaging
- healthcare
- end stage renal disease
- computed tomography
- ejection fraction
- public health
- high resolution
- emergency department
- chronic kidney disease
- systematic review
- magnetic resonance
- prognostic factors
- newly diagnosed
- randomized controlled trial
- photodynamic therapy
- clinical practice
- phase iii
- data analysis
- label free
- fluorescence imaging
- loop mediated isothermal amplification