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고려대학교 의과대학

Biosens. Bioelectron., Sep 10 2024, 267 S0956-5663(24)00779-6 | https://doi.org/10.1016/j.bios.2024.116773 Explainable artificial intelligence-driven prostate cancer screening using exosomal multi-marker based dual-gate FET biosensor

Jae Yi Choi ^a,b,1, Sungwook Park ^a,1, Ji Sung Shim ^c,1, Hyung Joon Park ^a,d,1, Sung Uk Kuh ^b,e, Youngdo Jeong ^a,f, Min Gu Park ^c, Tae Il Noh^c, Sung Goo Yoon ^c, Yoo Min Park^g, Seok Jae Lee^g, Hojun Kim ^a,h, Seok Ho Kang ^c, Kwan Hyi Lee ^a,d,h

^aCenter for Advanced Biomolecular Recognition, Biomedical Research Division, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea

^bDepartment of Medical Device Engineering and Management, College of Medicine, Yonsei University, Seoul, 06229, Republic of Korea

^cDepartment of Urology, College of Medicine, Korea University, Seoul, 02841, Republic of Korea

^dKU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul, 02481, Republic of Korea

^eDepartment of Neurosurgery, College of Medicine, Yonsei University, Seoul, 03722, Republic of Korea

^fDepartment of HY-KIST Bio-convergence, Hanyang University, Seoul, 04763, Republic of Korea

^gCenter for Nano Bio Development, National Nanofab Center (NNFC), Daejeon, 34141, Republic of Korea

^hDivision of Bio-Medical Science and Technology, KIST School, University of Science and Technology (UST), Daejeon, 34113, Republic of Korea

¹These authors contributed equally to this work.

Corresponding authors: Hojun Kim, Seok Ho Kang, Kwan Hyi Lee

Abstract

Prostate Imaging Reporting and Data System (PI-RADS) score, a reporting system of prostate MRI cases, has become a standard prostate cancer (PCa) screening method due to exceptional diagnosis performance. However, PI-RADS 3 lesions are an unmet medical need because PI-RADS provides diagnosis accuracy of only 30-40% at most, accompanied by a high false-positive rate. Here, we propose an explainable artificial intelligence (XAI) based PCa screening system integrating a highly sensitive dual-gate field-effect transistor (DGFET) based multi-marker biosensor for ambiguous lesions identification. This system produces interpretable results by analyzing sensing patterns of three urinary exosomal biomarkers, providing a possibility of an evidence-based prediction from clinicians. In our results, XAI-based PCa screening system showed a high accuracy with an AUC of 0.93 using 102 blinded samples with the non-invasive method. Remarkably, the PCa diagnosis accuracy of patients with PI-RADS 3 was more than twice that of conventional PI-RADS scoring. Our system also provided a reasonable explanation of its decision that TMEM256 biomarker is the leading factor for screening those with PI-RADS 3. Our study implies that XAI can facilitate informed decisions, guided by insights into the significance of visualized multi-biomarkers and clinical factors. The XAI-based sensor system can assist healthcare professionals in providing practical and evidence-based PCa diagnoses.

논문정보

형식Research article
게재일2024년 09월 (BRIC 등록일 2024-09-19)
연구진국내 연구진
분야 바이오·의료융합 > 바이오센싱 및 나노바이오물질

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