SUPPLEMENTARY MATERIAL.docx

A concise statement of the major
contents

The study developed and validated a nomogram combining
BMUS radiomics and the ACR TI-RADS.
The
predictive performance and stability of the nomogram was assessed with respect
to discrimination, calibration and clinical application in the validation and
entire cohort. The nomogram yielded an AUC of 0.889 and 0.849 in the training
and validation cohort, and the calibration curve were better. Higher
interobserver agreement and a significantly improved AUC, NRI and IDI were
found. Used the nomogram cutoff, radiologists showed significantly decreased
unnecessary FNA rate. The nomogram is an intuitive and convenient tool which
could considerably improve the predictive performance of radiologists with
different levels of experience and reduce the unnecessary FNA rate during the
treatment of thyroid nodules.

Keywords Thyroid nodule; Radiomics; Nomogram; Ultrasound; Prediction

Abstract

Context: Visual interpretation and radiomics
of B-mode ultrasound (BMUS) images both show good performance in predicting the
malignancy of
thyroid nodules.

Objective: Develop and validate
a nomogram combining BMUS radiomics and
the American College of Radiology (ACR) Thyroid Imaging
Reporting and Data System (TI-RADS).

Design: Retrospective cohort study

Methods: A total of 451 pathologically proven thyroid nodules at our
hospital (January 2019 to September 2020) were randomly assigned to training
and validation cohorts (7:3 ratio). Combining the BMUS radiomics score (Rad-Score) with the average ACR
TI-RADS score (ACR
score) from a senior and junior
radiologist, a nomogram was developed from the
training group. The predictive performance and stability
of the nomogram was assessed with respect to discrimination, calibration and
clinical application in the validation and entire cohort.

Results The nomogram
yielded an AUC of 0.889 in the training cohort and 0.849 in the validation
cohort, which were significantly better than the average ACR
score alone (p=0.002
and <0.001 respectively). The goodness of fit and calibration curve of the
nomogram were both better than the ACR
score. Higher interobserver agreement and a significantly improved
AUC, net reclassification index (NRI) and integrated discriminatory improvement
(IDI) of the nomogram were found compared with the
corresponding
ACR score, as independently scored by a senior and junior radiologist
(all p <0.001).

Conclusion The
nomogram is an intuitive and convenient tool that combines radiomics with the ACR TI-RADS, which could considerably
and stably improve the
predictive performance of radiologists with different levels of experience.