Thyroid cancer polygenic risk score combined with deep learning analysis of ultrasound images improves the classification of thyroid nodules as benign or malignant

Evaluating thyroid nodules to rule out malignancy is a very common clinical task. Image-based clinical and machine learning risk stratification schemas rely on the presence of thyroid nodule high-risk sonographic features. However, this approach is less suitable for diagnosing malignant thyroid nodules with a benign appearance on ultrasound. In this study, we developed thyroid cancer polygenic risk scoring (PRS) to complement deep learning analysis of ultrasound images. When the output of the deep learning model was combined with thyroid cancer PRS and genetic ancestry estimates, the area under the receiver operating characteristic curve (AUROC) of the benign vs. malignant thyroid nodule classifier increased from 0.83 to 0.89 (DeLong, p-value = 0.007). The combined deep learning and genetic classifier achieved a clinically relevant sensitivity of 0.95, 95 CI [0.88-0.99], specificity of 0.63 [0.55-0.70], and positive and negative predictive values of 0.47 [0.41-0.58] and 0.97 [0.92-0.99], respectively. An improved AUROC was consistent in ancestry-stratified analysis in Europeans (0.83 and 0.87 for deep-learning and deep learning combined with PRS classifiers, respectively). An elevated PRS was associated with a greater risk of thyroid cancer structural disease recurrence (ordinal logistic regression, p-value = 0.002). This study demonstrates that augmenting ultrasound image analysis with PRS improves diagnostic accuracy, paving the way for developing the next generation of clinical risk stratification algorithms incorporating inherited risk for developing thyroid malignancy. ### Competing Interest Statement Martin Barrio was supported by the Cancer League of Colorado fellowship WD#222494-MB. Nikita Pozdeyev was supported by a research grant from the University of Colorado Cancer. Bryan R. Haugen receives research support from Eisai and Merck unrelated to this research study. Bryan Haugen served on an Advisory Board at Eisai and is currently a member of the finance committee for the International Thyroid Oncology Group and Endocrine Society. Regeneron Genetics Center is a subsidiary of Regeneron Pharmaceuticals. All other authors have completed the ICMJE uniform disclosure form and declare: no support from any organization for the submitted work. ### Funding Statement This work was funded by the grant from the University of Colorado Cancer Center to NP and Colorado Cancer League fellowship AWD#222494-MB to MB. Genotyping data was provided by the Colorado Center for Personalized Medicine. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: IRB of the University of Washington gave ethical approval for this work. Colorado Multiple Institutional Review Board gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are either contained in the manuscript or available upon reasonable request to the authors, with the exception of the individual-level genetic data. [https://github.com/npozdey/thyroid\_nodule\_PRS][1] [1]: https://github.com/npozdey/thyroid_nodule_PRS