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Updated: Mar 19, 2026
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
Predicting malignancy in thyroid nodules: feasibility of a predictive model integrating clinical, biochemical, and
Justyna Witczak1,2, Peter Taylor1,2, Jason Chai2
1Centre for Endocrine and Diabetes Science, Institute of Molecular and Experimental Medicine, Cardiff University School of Medicine, University Hospital Wales, Cardiff, CF14 4XN UK.
Background:
Although the majority of thyroid nodules are benign the process of excluding malignancy is challenging and sometimes involves unnecessary surgical procedures. We explored the development of a predictive model for malignancy in thyroid nodules by integrating a combination of simple demographic, biochemical, and ultrasound characteristics.
Methods:
Retrospective case-record review. We reviewed records of patients with thyroid nodules referred to our institution from 2004 to 2011 (n = 536; female 84 %, mean age 51 years). All malignancy was proven histologically while benign disease was either confirmed histologically, or on cytology with minimum 36-month observation period. We focused on the following predictors: age, sex, smoking status, thyroid hormones (FT4 and TSH) and nodule characteristics on ultrasound. Variables were included in a multivariate logistic regression and bootstrap analyses were used to confirm results.
Results:
Independent predictors of malignancy in the fully adjusted model were TSH (OR 1.53, 95 % CI 1.10, 2.12, p = 0.01), male gender (OR 3.45, 95 % CI 1.33, 8.92, p = 0.01), microcalcifications (OR 6.32, 95 % CI 2.82, 14.1, p < 0.001), and irregular nodule margins (OR 5.45, 95 % CI 1.61, 18.6, p = 0.006) Bootstrap analyses strengthened these associations and a parsimonious analysis consisting of these variables and age-group demonstrated an area under the curve of 0.77. A predictive score was sensitive (86.9 %) at low scores and highly specific (94.87 %) at higher scores for distinguishing benign from malignant disease.
Conclusions:
A predictive model for malignancy using a combination of clinical, biochemical, and radiological characteristics may support clinicians in reducing unnecessary invasive procedures in patients with thyroid nodules.
