Uncovering associations between data-driven learned qMRI biomarkers and chronic pain.

ABSTRACT: Knee pain is the most common and debilitating symptom of knee osteoarthritis (OA). While there is a perceived association between OA imaging biomarkers and pain, there are weak or conflicting findings for this relationship. This study uses Deep Learning (DL) models to elucidate associations between bone shape, cartilage thickness and T₂ relaxation times extracted from Magnetic Resonance Images (MRI) and chronic knee pain. Class Activation Maps (Grad-CAM) applied on the trained chronic pain DL models are used to evaluate the locations of features associated with presence and absence of pain. For the cartilage thickness biomarker, the presence of features sensitive for pain presence were generally located in the medial side, while the features specific for pain absence were genera

SUBMITTER: Morales AG 

PROVIDER: S-EPMC8578418 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature