Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Care and AI Laboratory, Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA.
Citations 4
What Happens after an Incidental Thyroid Nodule? Patterns of Thyroid Ultrasound Use and Downstream Evaluation
Thyroid® | September 30, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available
Background: Incidental thyroid nodules (ITNs) detected on nonthyroid imaging contribute to thyroid cancer overdiagnosis, largely through downstream evaluation initiated by thyroid ultrasound (TUS). However, TUS follow-up rates for ITNs and their drivers in routine practice remain unclear. We quantified TUS utilization after ITN detection and identified patient, imaging, nodule, and reporting factors associated with this first step in the diagnostic cascade. Methods: We conducted a retrospective cohort study of adults without prior thyroid disease who underwent imaging that incidentally captured the thyroid at Mayo Clinic sites (2017–2023). A validated natural language processing pipeline identified ITNs and extracted nodule characteristics from radiology reports across multiple imaging modalities. The main outcome was the rate of TUS within 180 days after ITN detection. Clinical outcomes, including thyroid biopsy, thyroidectomy, and thyroid cancer diagnosis, were compared between patients who underwent TUS and those who did not. Factors associated with TUS utilization were assessed using multivariable logistic regression with penalized variable selection. Results: Among 115,683 patients who underwent thyroid-capturing imaging, 8426 (7.3%) had an ITN. These patients were predominantly female (64.6%) and White (89.7%), with a mean age of 61.7 years (standard deviation 15.2). Most nodules were detected on computed tomography (80.8%), most commonly from chest imaging (52.3%). Overall, 1677 patients with ITNs (19.9%) underwent TUS. In multivariable analysis, TUS use was independently associated with higher body mass index (odds ratio [OR], 1.20 per 10-unit increase; confidence interval [CI] [1.08–1.33]), nodule size ≥1.5 cm (OR, 1.79; CI [1.52–2.10]), and a radiologist recommendation (OR, 2.51; CI [2.12–2.98]), whereas older age was associated with lower odds of TUS (OR, 0.89 per 10-year increase; CI [0.84–0.93]). Patients undergoing TUS had higher rates of thyroid biopsy, partial thyroidectomy, and total thyroidectomy compared with those without it. All detected thyroid cancers (103 cases) occurred in the TUS group, representing 6.1% of that cohort. Conclusions: One in five patients with ITNs underwent TUS, representing a critical gateway to downstream diagnostic procedures and thyroid cancer detection. Factors associated with TUS utilization highlight opportunities to better define appropriateness of ultrasound after incidental nodule detection and to reduce unnecessary testing and treatment.
A Decade of Interventional Radiotherapy (Brachytherapy): Progress, Challenges, and Future Prospects – A Bibliometric Analysis
Technology in Cancer Research & Treatment | July 21, 2026 | Volume: 25 | Issue: No issue available | Pages: No page available
Background Interventional radiotherapy (IRT), also known as brachytherapy, has become a cornerstone of radiation oncology due to its ability to maximize therapeutic efficacy while minimizing side effects to surrounding tissues. This bibliometric analysis aims to examine the evolution of IRT over the past decade. Material and Methods A string comprising IRT-related keywords was developed, and data were extracted from the Scopus database for English-language documents published between January 2014 and December 2024. The analysis was performed using Bibliometrix package Results A total of 15 755 documents from 2150 sources were analyzed, revealing an average annual growth rate of 1.03%. Publication trends were stable from 2014 to 2018, surged from 2019, and peaked in 2021, with subsequent levels remaining above pre-2019 figures. Original articles accounted for 72.7% of the literature, with key contributions from journals such as “Brachytherapy” and the “Journal of Contemporary Brachytherapy”. The analysis highlighted strong collaborative networks, with significant input from North American and European institutions, and identified focal research themes including uterine cervical cancer and prostate brachytherapy. Emerging topics, such as deep learning, artificial intelligence, and personalized dosimetry, underscore the field's shift towards precision medicine. Conclusions The findings reflect IRT's dynamic research landscape and its growing integration into modern oncologic practice, emphasizing the need for continued interdisciplinary efforts and clinical trials to advance this minimally invasive treatment modality further. Highlights • A decade-long bibliometric analysis of 15 755 publications on interventional radiotherapy (IRT) reveals stable growth, with a notable surge in research activity post-2019. • Uterine, cervical, and prostate cancers remain the most studied clinical indications for IRT globally. • North American and European institutions dominate collaborative networks, reflecting the strength of transatlantic research partnerships. • Emerging research themes include artificial intelligence, deep learning, and personalized dosimetry—marking a transition toward precision oncology. • The field's evolving landscape highlights the increasing clinical and scientific significance of IRT in contemporary cancer care.
Artificial intelligence-enabled analysis of radiology reports: epidemiology and outcomes of incidental thyroid findings
The Journal of Clinical Endocrinology & Metabolism | April 23, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Context Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, and consequences remain undefined. Objective To develop, validate, and deploy a natural language processing (NLP) pipeline to identify ITFs in radiology reports and assess their prevalence, features, and clinical outcomes. Design Retrospective cohort study. Setting Mayo Clinic sites (Rochester, Arizona, Florida, Mayo Clinic Health System). Participants Adults without prior thyroid disease undergoing thyroid-capturing imaging from July 1, 2017, to September 30, 2023. A transformer-based NLP pipeline identified ITFs and extracted nodule characteristics from image reports from multiple modalities and body regions. Outcomes ITF prevalence, downstream thyroid ultrasound, biopsy, thyroidectomy, and cancer diagnosis. Logistic regression identified demographic and imaging-related factors. Results Among 115 683 patients (mean age, 56.8 [SD 17.2]; 52.9% women), 9077 (7.8%) had an ITF (92.9% nodular). ITFs were more likely in women, older adults, higher BMI, and in imaging ordered by specialties different from Emergency Medicine. Compared with chest CT, ITFs were more likely via neck CT, PET, and nuclear medicine scans. Nodule characteristics were poorly documented, with size reported in 44% and other features in fewer than 15%. Compared with patients without ITFs, those with ITFs had higher odds of thyroid nodule diagnosis (OR 45, 95%CI 41.1-49.3), biopsy (OR 46.8, 95%CI 39.0-56.2) thyroidectomy (OR 55.8, 95%CI 31.3-99.3), and thyroid cancer diagnosis (OR 61.7, 95%CI 38.6-98.5). Most cancers were papillary (88.5%) and larger when detected after ITFs (2 cm SD 1.4) vs no ITF (1.3 cm SD 0.8). Conclusion ITFs were common and strongly associated with cascades leading to the detection of small, low-risk cancers, highlighting their role in overdiagnosis and the need for standardized reporting and more selective follow-up.
Large Language Model and Natural Language Processing Approach to Identify Cancer Recurrence From Pathology Reports
JCO Clinical Cancer Informatics | March 25, 2026 | Volume: 10 | Issue: 1 | Pages: No page available
PURPOSE Cancer recurrence is a critical outcome for patients and physicians. Retrospective cancer recurrence data can evaluate recurrence-directed treatment and generate novel interventions targeting recurrent cancers. However, large cancer databases do not provide recurrence-related information, stymying study at scale, and consequently require significant manual record review. Automated evaluation of records may allow for the rapid generation of easily analyzed data sets, accelerating the evaluation of recurrence altogether. METHODS Patients treated with radiation therapy at one tertiary referral center from 2010 to 2018 with a verified cancer status (cancer recurrence v no cancer recurrence) were identified. Patients with recurrent disease were initially identified through manual record review, and the associated pathology report was collected. Google Automated Machine Learning with Natural Language Processing (AutoNLP) and Google Gemini 1.5 Pro were used to generate a model for binary classification, with comparison to the gold-standard manually developed data set. RESULTS A total of 7,054 patients were identified. 3,431 (48.6%) were female, with a median age of 64 years. Head and neck (1,482, 21%), breast (1,480, 21%), upper GI (1,307, 18.5%), and lung/thorax (1,107, 15.7%) were the most common disease sites. Recurrence was verified for 1,546 patients (21.9%) using pathology reports, of which 1,249 positive cases were paired with 651 negative pathology reports for model development. Google Gemini 1.5 Pro consistently outperformed AutoNLP across all measurements of accuracy, generating a greater absolute difference in precision, recall, negative predictive value, and specificity, and a higher likelihood of correct classification at the individual level, rendering Gemini superior in recurrence status extraction. CONCLUSION AutoNLP and Google Gemini 1.5 Pro are promising tools for identifying recurrence from pathology reports, with the latter demonstrating superior overall performance, making it particularly suitable for clinical translation.