• Profile
Close

Risk stratification of indeterminate thyroid nodules using ultrasound and machine learning algorithms

Clinical Endocrinology Oct 19, 2021

Gild ML, Chan M, Gajera J, et al. - Findings support the use of novel radiomic and radiologic strategies to assist with preoperative diagnosis of indeterminate thyroid nodules.

  • Indeterminate thyroid nodules (Bethesda III) are difficult to characterize without diagnostic surgery.

  • This retrospective review included 88 patients with Bethesda III nodules who underwent diagnostic surgery with final pathological diagnosis.

  • Via TI-RADS (Thyroid Imaging, Reporting and Data System), retrospective scoring of each nodule was performed, and two deep learning models were tested.

  • For benign and for malignant nodules, the mean TI-RADS score was 3 and 4, respectively, and radiological high risk (TI-RADS 4,5) and low risk (TI-RADS 2,3) categories were defined.

  • PPV for the high radiological risk class in those with >10 mm nodules was 85%, and NPV for low radiological risk in those >60 years (mean age) was 100%.

  • Area under the curve value of the novel classifier was identified to be 0.75 and differed significantly from the chance-level.

Go to Original
Only Doctors with an M3 India account can read this article. Sign up for free or login with your existing account.
4 reasons why Doctors love M3 India
  • Exclusive Write-ups & Webinars by KOLs

  • Nonloggedininfinity icon
    Daily Quiz by specialty
  • Nonloggedinlock icon
    Paid Market Research Surveys
  • Case discussions, News & Journals' summaries
Sign-up / Log In
x
M3 app logo
Choose easy access to M3 India from your mobile!


M3 instruc arrow
Add M3 India to your Home screen
Tap  Chrome menu  and select "Add to Home screen" to pin the M3 India App to your Home screen
Okay