• Korean Journal of Radiology
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• v.23 no.7
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• pp.720-731
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• 2022

Objective: We aimed to develop and test a deep learning algorithm (DLA) for fully automated measurement of the volume and signal intensity (SI) of the liver and spleen using gadoxetic acid-enhanced hepatobiliary phase (HBP)-magnetic resonance imaging (MRI) and to evaluate the clinical utility of DLA-assisted assessment of functional liver capacity. Materials and Methods: The DLA was developed using HBP-MRI data from 1014 patients. Using an independent test dataset (110 internal and 90 external MRI data), the segmentation performance of the DLA was measured using the Dice similarity score (DSS), and the agreement between the DLA and the ground truth for the volume and SI measurements was assessed with a Bland-Altman 95% limit of agreement (LOA). In 276 separate patients (male:female, 191:85; mean age ± standard deviation, 40 ± 15 years) who underwent hepatic resection, we evaluated the correlations between various DLA-based MRI indices, including liver volume normalized by body surface area (LV_BSA), liver-to-spleen SI ratio (LSSR), MRI parameter-adjusted LSSR (aLSSR), LSSR × LV_BSA, and aLSSR × LV_BSA, and the indocyanine green retention rate at 15 minutes (ICG-R15), and determined the diagnostic performance of the DLA-based MRI indices to detect ICG-R15 ≥ 20%. Results: In the test dataset, the mean DSS was 0.977 for liver segmentation and 0.946 for spleen segmentation. The Bland-Altman 95% LOAs were 0.08% ± 3.70% for the liver volume, 0.20% ± 7.89% for the spleen volume, -0.02% ± 1.28% for the liver SI, and -0.01% ± 1.70% for the spleen SI. Among DLA-based MRI indices, aLSSR × LV_BSA showed the strongest correlation with ICG-R15 (r = -0.54, p < 0.001), with area under receiver operating characteristic curve of 0.932 (95% confidence interval, 0.895-0.959) to diagnose ICG-R15 ≥ 20%. Conclusion: Our DLA can accurately measure the volume and SI of the liver and spleen and may be useful for assessing functional liver capacity using gadoxetic acid-enhanced HBP-MRI.

• International journal of thyroidology
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• v.11 no.2
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• pp.92-98
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• 2018

Intraoperative identification and localization of parathyroid glands are crucial step in preventing postoperative hypocalcemia during thyroid and parathyroid surgery. If there is a method to predict the parathyroid's location rather than detecting and verifying with naked eye, it would make the operator easier to find and identify the parathyroid. Recently, near-infrared light imaging technologies have been introduced in the fields of thyroid and parathyroid surgery to predict the localization of the parathyroid. These are being conducted in two ways: autofluorescence imaging with a unique intrinsic fluorophore in the parathyroid tissues and fluorescence imaging with external fluorescence materials specially absorbed into parathyroid tissues. We are suggest that parathyroid glands can be detected by surgeon with NIR autofluorescence imaging even if they are covered by fibrofatty tissues before they are detected by surgeon's naked eye. These novel techniques are very useful to identify and preserve parathyroid glands during thyroidectomy. In this article, we reviewed the latest papers that describe autofluorescence imaging and exogenous ICG fluorescence imaging of parathyroid glands during thyroid and parathyroid surgery.