Detection and localization of hyperfunctioning parathyroid glands on [¹⁸F]fluorocholine PET/ CT using deep learning - model performance and comparison to human experts.

ABSTRACT:

Background

In the setting of primary hyperparathyroidism (PHPT), [¹⁸F]fluorocholine PET/CT (FCH-PET) has excellent diagnostic performance, with experienced practitioners achieving 97.7% accuracy in localising hyperfunctioning parathyroid tissue (HPTT). Due to the relative triviality of the task for human readers, we explored the performance of deep learning (DL) methods for HPTT detection and localisation on FCH-PET images in the setting of PHPT.

Patients and methods

We used a dataset of 93 subjects with PHPT imaged using FCH-PET, of which 74 subjects had visible HPTT while 19 controls had no visible HPTT on FCH-PET. A conventional Resnet10 as well as a novel mPETResnet10 DL model were trained and tested to detect (present, not present) and localise (upper left, l

SUBMITTER: Jarabek L 

PROVIDER: S-EPMC9784363 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature