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Knowledge-based automated planning system for StereoElectroEncephaloGraphy: A center-based scenario.

Abstract：

:Surgical planning for StereoElectroEncephaloGraphy (SEEG) is a complex and patient specific task, where the experience and medical workflow of each institution may influence the final planning choices. To account for this variability, we developed a data-based Computer Assisted Planning (CAP) solution able to exploit the knowledge extracted by past cases. By the analysis of retrospective patients' data sets, our system proposes a pool of trajectories commonly used by the institution, which can be selected to initialize a new patient plan. An optimization framework adapts those to the patient's anatomy by optimizing clinical requirements (e.g. distance from vessel, gray matter recording and insertion angle), and adapting its strategy based on the trajectory type selected.The system has been customized based on the data of a single institution. Two neurosurgeons, working in a high-volume hospital, have validated it by using 15 retrospective patient data sets, with more than 200 trajectories reviewed. Both surgeons considered ~81% of the optimized trajectories as clinically feasible (75% inter-rater reliability). Quantitative comparison of distance from vessels, insertion angle and gray matter recording index showed that the optimized trajectories reached superior or comparable values with respect to the original manual plans. The results suggest that a tailored center-based solution could increase the acceptance rate of the automated trajectories proposed.

journal_name

J Biomed Inform

journal_title

Journal of biomedical informatics

authors

Scorza D,Rizzi M,De Momi E,Cortés C,Bertelsen Á,Cardinale F

doi

10.1016/j.jbi.2020.103460

subject

Has Abstract

pub_date

2020-08-01 00:00:00

pages

103460

eissn

1532-0464

issn

1532-0480

pii

S1532-0464(20)30088-5

journal_volume

108

pub_type

杂志文章

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