PT  - JOURNAL ARTICLE
AU  - Heyn, Chris
AU  - Moody, Alan R.
AU  - Tseng, Chia-Lin
AU  - Wong, Erin
AU  - Kang, Tony
AU  - Kapadia, Anish
AU  - Howard, Peter
AU  - Maralani, Pejman
AU  - Symons, Sean
AU  - Goubran, Maged
AU  - Martel, Anne
AU  - Chen, Hanbo
AU  - Myrehaug, Sten
AU  - Detsky, Jay
AU  - Sahgal, Arjun
AU  - Soliman, Hany
TI  - Segmentation of Brain Metastases Using Background Layer Statistics (BLAST)
AID  - 10.3174/ajnr.A7998
DP  - 2023 Oct 01
TA  - American Journal of Neuroradiology
PG  - 1135--1143
VI  - 44
IP  - 10
4099  - http://www.ajnr.org/content/44/10/1135.short
4100  - http://www.ajnr.org/content/44/10/1135.full
SO  - Am. J. Neuroradiol.2023 Oct 01; 44
AB  - BACKGROUND AND PURPOSE: Accurate segmentation of brain metastases is important for treatment planning and evaluating response. The aim of this study was to assess the performance of a semiautomated algorithm for brain metastases segmentation using Background Layer Statistics (BLAST).MATERIALS AND METHODS: Nineteen patients with 48 parenchymal and dural brain metastases were included. Segmentation was performed by 4 neuroradiologists and 1 radiation oncologist. K-means clustering was used to identify normal gray and white matter (background layer) in a 2D parameter space of signal intensities from postcontrast T2 FLAIR and T1 MPRAGE sequences. The background layer was subtracted and operator-defined thresholds were applied in parameter space to segment brain metastases. The remaining voxels were back-projected to visualize segmentations in image space and evaluated by the operators. Segmentation performance was measured by calculating the Dice-Sørensen coefficient and Hausdorff distance using ground truth segmentations made by the investigators. Contours derived from the segmentations were evaluated for clinical acceptance using a 5-point Likert scale.RESULTS: The median Dice-Sørensen coefficient was 0.82 for all brain metastases and 0.9 for brain metastases of ≥10 mm. The median Hausdorff distance was 1.4 mm. Excellent interreader agreement for brain metastases volumes was found with an intraclass correlation coefficient = 0.9978. The median segmentation time was 2.8 minutes/metastasis. Forty-five contours (94%) had a Likert score of 4 or 5, indicating that the contours were acceptable for treatment, requiring no changes or minor edits.CONCLUSIONS: We show accurate and reproducible segmentation of brain metastases using BLAST and demonstrate its potential as a tool for radiation planning and evaluating treatment response.BLbackground layerBLASTBackground Layer StatisticsBMbrain metastasesDLdeep learningDSCDice-Sørensen coefficientHDHausdorff distanceICCintraclass correlation coefficientIQRinterquartile rangeSRSstereotactic radiosurgeryTHthreshold