Background: To determine the predictive capability of MRI-based radiomics for extrathyroidal extension detection in papillary thyroid cancer (PTC) pre-surgically. Methods: The present retrospective trial assessed individuals with thyroid nodules examined by multiparametric MRI and subsequently administered thyroid surgery. Diagnosis and extrathyroidal extension (ETE) feature of PTC were based on pathological assessment. The thyroid tumors underwent manual segmentation, for radiomic feature extraction. Participants were randomized to the training and testing cohorts, at a ratio of 7:3. The mRMR (maximum correlation minimum redundancy) algorithm and the least absolute shrinkage and selection operator were utilized for radiomics feature selection. Then, a radiomics predictive model was generated via a linear combination of the features. The model’s performance in distinguishing the ETE feature of PTC was assessed by analyzing the receiver operating characteristic curve. Results: Totally 132 patients were assessed in this study, including 92 and 40 in the training and test cohorts, respectively). Next, the 16 top-performing features, including 4, 7 and 5 from diffusion weighted (DWI), T2-weighted (T2 WI), and contrast-enhanced T1-weighted (CE-T1WI) images, respectively, were finally retained to construct the radiomics signature. There were 8 RLM, 5 CM, 2 shape, and 1 SZM features. The radiomics prediction model achieved AUCs of 0.96 and 0.87 in the training and testing sets, respectively. Conclusions: Our study indicated that MRI radiomics approach had the potential to stratify patients based on ETE in PTCs preoperatively.

Objective: To investigate the ability of a multimodality MRI-based radiomics model in predicting the aggressiveness of papillary thyroid carcinoma (PTC). Methods: This study included consecutive patients who underwent neck magnetic resonance (MR) scans and subsequent thyroidectomy during the study period. The pathological diagnosis of thyroidectomy specimens was the gold standard to determine the aggressiveness. Thyroid nodules were manually segmented on three modal MR images, and then radiomics features were extracted. A machine learning model was established to evaluate the prediction of PTC aggressiveness. Results: The study cohort included 107 patients with PTC confirmed by pathology (cross-validation cohort: n = 71; test cohort: n = 36). A total of 1584 features were extracted from contrast-enhanced T1-weighted (CE-T1 WI), T2-weighted (T2 WI) and diffusion weighted (DWI) images of each patient. Sparse representation method is used for radiation feature selection and classification model establishment. The accuracy of the independent test set that using only one modality, like CE-T1WI, T2WI or DWI was not particularly satisfactory. In contrast, the result of these three modalities combined achieved 0.917. Conclusion: Our study shows that multimodality MR image based on radiomics model can accurately distinguish aggressiveness in PTC from non-aggressiveness PTC before operation. This method may be helpful to inform the treatment strategy and prognosis of patients with aggressiveness PTC.

Background: Photothermal therapy has the potential to enhance the precision and safety of oncological treatments. However, applicable photothermal agents associated with its photothermal activated immunogenic cell death remain exploiting. Methods: This study evaluates the effectiveness of IR813, a photothermal agent, combined with near-infrared (NIR) light for cancer treatment. In vitro, 4T1 cancer cells were treated with IR813 (5 μg/mL) and exposed to NIR irradiation (1 W/cm²) for 5 min. In vivo, after the tumor-bearing mice administered with IR813 (1 mg/kg) and exposed to NIR irradiation (1 W/cm²) for 10 min, the tumor volume, survival and immune activation were evaluated. Results: IR813 significantly increased the cytotoxicity of 4T1 cancer cells following near-infrared irradiation, resulting in the release of damage-associated molecular patterns and immunogenic cell death. Specifically, the cell viability was reduced to 5% compared to the control group. In vivo, irradiating the accumulation of IR813 at the tumor site had the potential to mediate substantial photothermal tumor suppression, improved mouse survival, and reduced metastasis, with minimal adverse reactions. Furthermore, the immune responses stimulated by IR813-induced photothermal therapy were evidenced by increased mature dendritic cell and cytotoxic T lymphocyte counts and a decrease in regulatory T cells in the spleen, tumor, and lymph nodes. Conclusions: These findings suggest that IR813-induced photothermal therapy is a promising approach for enhancing immunotherapy, directly inhibiting tumors while boosting systemic anti-cancer immunity.