Identification of Preoperative Language Tracts for Intrinsic Frontotemporal Diseases: A Pilot Reconstruction Algorithm in a Middle-Income Country

Objective Diffusion tensor imaging (DTI) tractography provides useful information that can be used to optimize surgical planning and help avoid injury during subcortical dissection of eloquent tracts. The objective is to provide a safe, timely, and affordable algorithm for preoperative DTI language reconstruction for intrinsic frontotemporal diseases. Methods We reviewed a prospectively acquired database of preoperative DTI reconstruction for resection of left frontotemporal lesions over 3 years at Hospital de San Jose and Hospital Infantil Universitario San Jose, Fundacion Universitaria de Ciencias de la Salud, Bogota, Colombia. Preoperative and postoperative clinical and radiographic features were determined from retrospective chart review. A comprehensive review of the structural and functional anatomy of the language tracts was performed. Separate reconstruction of both ventral (semantic) and dorsal (phonologic) stream pathways is described: arcuate fasciculus, superior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, and inferior longitudinal fasciculus. Results Between January 2015 and January 2018, 44 tumor cases were found to be resected with preoperative fiber tracking planning and neuronavigation-guided surgery. Ten patients (7 women, 3 men) aged 28–65 years underwent resection of an intrinsic frontotemporal lesion with preoperative DTI tractography reconstruction of language tracts. Eight cases (80%) were high-grade gliomas and 2 (20%) were cavernous malformations. In 5 cases (50%), the lesion was in the frontal lobe and in 5 (50%), it was in the temporal lobe. The extent of resection was classified as gross total resection (100%), subtotal resection (>90%), or partial resection ( Conclusions We present a safe and efficacious preoperative DTI language reconstruction algorithm that could be used as a feasible treatment strategy in a challenging subset of tumors in low- to middle-income countries.