Is visual assessment of thyroid attenuation on unenhanced CT of the chest useful for detecting hypothyroidism?

Relationship between Thyroid CT Density, Volume, and Future TSH Elevation: A 5-Year Follow-Up Study

This study aimed to explore the relationship between thyroid-stimulating hormone (TSH) elevation and the baseline computed tomography (CT) density and volume of the thyroid. We examined 86 cases with new-onset hypothyroidism (TSH > 4.5 IU/mL) and 1071 controls from a medical check-up database over 5 years. A deep learning-based thyroid segmentation method was used to assess CT density and volume. Statistical tests and logistic regression were employed to determine differences and odds ratios. Initially, the case group showed a higher CT density (89.8 vs. 81.7 Hounsfield units (HUs)) and smaller volume (13.0 vs. 15.3 mL) than those in the control group. For every +10 HU in CT density and -3 mL in volume, the odds of developing hypothyroidism increased by 1.40 and 1.35, respectively. Over the course of the study, the case group showed a notable CT density reduction (median: -8.9 HU), whereas the control group had a minor decrease (-2.9 HU). Thyroid volume remained relatively stable for both groups. Higher CT density and smaller thyroid volume at baseline are correlated with future TSH elevation. Over time, there was a substantial and minor decrease in CT density in the case and control groups, respectively. Thyroid volumes remained consistent in both cohorts.

Prediction of Radiation-Induced Hypothyroidism Using Radiomic Data Analysis Does Not Show Superiority over Standard Normal Tissue Complication Models

Simple Summary

Radiation-induced hypothyroidism (RIHT) commonly develops in cancer survivors that receive radiation therapy for cancers in the head and neck region. The state-of-art normal tissue complication probability (NTCP) models perform satisfactorily; however, they do not use the whole spectrum of information that can be obtained from imaging techniques. The radiomic approach offers the ability to efficiently mine features, which are imperceptible to the human eye, but may provide crucial data about the patient’s condition. We gathered CT images and clinical data from 98 patients undergoing radiotherapy for head and neck cancers, 27 of whom later developed RIHT. For them, we created machine-learning models to predict RIHT using automatically extracted radiomic features and appropriate clinical and dosimetric parameters. We also validated the well-established external state-of-art NTCP models on our datasets and observed that our radiomic-based models performed very similarly to them. This shows that automated tools may perform as well as the current standard but can be theoretically applied faster and be implemented into existing imaging software used when planning radiotherapy.

Abstract

State-of-art normal tissue complication probability (NTCP) models do not take into account more complex individual anatomical variations, which can be objectively quantitated and compared in radiomic analysis. The goal of this project was development of radiomic NTCP model for radiation-induced hypothyroidism (RIHT) using imaging biomarkers (radiomics). We gathered CT images and clinical data from 98 patients, who underwent intensity-modulated radiation therapy (IMRT) for head and neck cancers with a planned total dose of 70.0 Gy (33–35 fractions). During the 28-month (median) follow-up 27 patients (28%) developed RIHT. For each patient, we extracted 1316 radiomic features from original and transformed images using manually contoured thyroid masks. Creating models based on clinical, radiomic features or a combination thereof, we considered 3 variants of data preprocessing. Based on their performance metrics (sensitivity, specificity), we picked best models for each variant ((0.8, 0.96), (0.9, 0.93), (0.9, 0.89) variant-wise) and compared them with external NTCP models ((0.82, 0.88), (0.82, 0.88), (0.76, 0.91)). We showed that radiomic-based models did not outperform state-of-art NTCP models (p > 0.05). The potential benefit of radiomic-based approach is that it is dose-independent, and models can be used prior to treatment planning allowing faster selection of susceptible population.

Pre-contrast CT attenuation of the thyroid gland is lower in brachycephalic dogs versus non-brachycephalic dogs

Computed tomography has been used in human medicine to evaluate the thyroid gland functional status by means of Hounsfield units (HU). Studies describing attenuation value abnormalities, other than those in thyroid neoplasia, lack in veterinary medicine. The authors have observed a subjective reduction in thyroid attenuation in some patients undergoing CT for reasons other than thyroid disease. This finding has been identified more frequently in brachycephalic breeds compared to non-brachycephalic breeds. In order to determine the thyroid gland attenuation variability on CT, a retrospective and prospective, analytical, cross-sectional study was performed. The thyroid attenuation values of 65 client-owned dogs were assessed using a 16-slice helical CT scanner. Differences in attenuation between brachycephalic and non-brachycephalic dogs were estimated by Welch's t-test. Serum TT4 and TSH levels were available in 26 patients. Statistically significant differences were observed in the pre-contrast attenuation value ranges between brachycephalic and non-brachycephalic dogs (P = .04). The pre-contrast attenuation value range for the brachycephalic group was 69.1-108 HU while being 75.8-121 HU for the non-brachycephalic group. No significant correlation was found between thyroid attenuation and serum thyroid hormone levels in our population (P > .6). All patients with hypoattenuating thyroid were brachycephalic and reported euthyroid. In conclusion, brachycephalic dogs seem to have a pre-contrast attenuation thyroid gland range lower than non-brachycephalic dogs. The present study contributes to the veterinary literature by providing a new thyroid attenuation value range for brachycephalic breeds. Additionally, hypoattenuating thyroid glands may be found in dogs with normal TT4 and TSH values.