Fully automated delineation of the optic radiation for surgical planning using clinically feasible sequences.
Lee B ReidEloy Martinez-HerasJose V ManjónRosalind L JeffreeHamish AlexanderJulie TrinderElisabeth SolanaSara LlufriuStephen E RoseMarita PriorJurgen FrippPublished in: Human brain mapping (2021)
Quadrantanopia caused by inadvertent severing of Meyer's Loop of the optic radiation is a well-recognised complication of temporal lobectomy for conditions such as epilepsy. Dissection studies indicate that the anterior extent of Meyer's Loop varies considerably between individuals. Quantifying this for individual patients is thus an important step to improve the safety profile of temporal lobectomies. Previous attempts to delineate Meyer's Loop using diffusion MRI tractography have had difficulty estimating its full anterior extent, required manual ROI placement, and/or relied on advanced diffusion sequences that cannot be acquired routinely in most clinics. Here we present CONSULT: a pipeline that can delineate the optic radiation from raw DICOM data in a completely automated way via a combination of robust pre-processing, segmentation, and alignment stages, plus simple improvements that bolster the efficiency and reliability of standard tractography. We tested CONSULT on 696 scans of predominantly healthy participants (539 unique brains), including both advanced acquisitions and simpler acquisitions that could be acquired in clinically acceptable timeframes. Delineations completed without error in 99.4% of the scans. The distance between Meyer's Loop and the temporal pole closely matched both averages and ranges reported in dissection studies for all tested sequences. Median scan-rescan error of this distance was 1 mm. When tested on two participants with considerable pathology, delineations were successful and realistic. Through this, we demonstrate not only how to identify Meyer's Loop with clinically feasible sequences, but also that this can be achieved without fundamental changes to tractography algorithms or complex post-processing methods.
Keyphrases
- deep learning
- computed tomography
- machine learning
- transcription factor
- end stage renal disease
- optical coherence tomography
- white matter
- contrast enhanced
- magnetic resonance imaging
- primary care
- chronic kidney disease
- ejection fraction
- optic nerve
- peritoneal dialysis
- radiation induced
- newly diagnosed
- convolutional neural network
- ultrasound guided
- dual energy