Differentiated Thyroid Carcinoma: Distant Metastasis as an Unusual Sole Initial Manifestation

Dhanani, Rahim; Faisal, Muhammad; Akram, Mahir; Shakeel, Osama; Zahid, Muhammad Toqeer; Hassan, Aamna; Hussain, Raza

doi:10.4274/tao.2021.2021-2-5

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…The mean age of our patients at the time of diagnosis was 55.8 years and only two patients were younger than 40. Similar findings were reported in the literature (Dhanani et al 2021 ; Lee and Soh 2010 ).…”

Section: Discussionsupporting

confidence: 92%

Rare sites of metastases in patients with differentiated thyroid carcinoma and added value of SPECT/CT over planar whole body radioactive iodine scan

Bashank

Farghaly

Hassanein

et al. 2022

European J Hybrid Imaging

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Background Being aware of the unusual or rare location of thyroid metastases helps in early diagnosis and proper patient management. Rare metastases (RM) can be missed resulting in diagnostic pitfalls and delayed treatment. The use of single-photon emission computed tomography/computed tomography (SPECT/CT) imaging in the follow-up of differentiated thyroid cancer (DTC) patients provides precise anatomical localization and characterization of RM that may be missed or misinterpreted in planar whole body iodine-131 (WBI) scan. There is a lack of knowledge about dealing with such patients, the treatment they should receive, and therapy response due to the rarity of such cases. In this work, we reported these rare cases increasing awareness about them and their methods of treatment with response to therapy and evaluated the added value of SPECT/CT imaging in changing patients’ management. Materials and methods In this study we reviewed all patients with DTC referred to our unit either for initial radioactive iodine-131 therapy (RAIT) or under follow-up from January 2019 to January 2022. When a suspected lesion was detected in a conventional planar WBI scan whether follow-up scan or post-therapeutic scan, SPECT/CT was acquired immediately in the same session for that region. Additional imaging modalities were performed for confirmation. Response to the given treatment either disease progression (DP) or favorable response which include complete response (CR), partial regression (PR) and stable disease (SD) recorded for each patient. Results Two hundred and forty patients with DTC referred to our unit over a three-year period (from January 2019 to January 2022) were reviewed. Forty patients developed lung and bone distant metastases. Twenty-one patients were thought to have metastases at unusual sites. Due to incomplete data (no SPECT/CT pictures or confirmatory imaging), 6/21 patients were eliminated. We studied 15 patients with RM (9 females, 6 males) with a median age of 52 years (range 27–79). All patients received the initial RAIT after thyroidectomy in addition to other therapeutic modalities, e.g., radiotherapy (RTH), chemotherapy (CTH) or surgical tumor excision after detection of RM. Ten out of 15 patients (66.67%) showed favorable response to therapy (2 patients had CR, 6 patients had PR and 2 patients had SD), whereas only 5 patients had DP. Additional SPECT/CT changed management in 10/15 patients (66, 67%) of patients. Conclusion RM identification is mandatory to avoid misdiagnosis and delayed therapy. Increasing the awareness about such rare cases allows for better management. SPECT/CT could significantly impact patients' management through its precise anatomic localization and lesion characterization.

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Section: Discussionsupporting

confidence: 92%

Rare sites of metastases in patients with differentiated thyroid carcinoma and added value of SPECT/CT over planar whole body radioactive iodine scan

Bashank

Farghaly

Hassanein

et al. 2022

European J Hybrid Imaging

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“…Overall, the presence of distant metastases is an important factor suggesting poor disease prognosis in a small percentage of patients (approximately 3-15%) [19][20][21][22]. Patients with thyroid cancer with distant metastases may present with clinical symptoms at the appropriate site [23]. However, some patients who present with distant metastases at the rst visit may have no clinical symptoms or may even have insidious distant metastases [24].…”

Section: Discussionmentioning

confidence: 99%

Machine learning based on SEER database to predict distant metastasis of thyroid cancer

Qiao,

Li,

Wang

et al. 2023

Endocrine

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Distant metastasis of thyroid cancer often indicates poor prognosis, and it is important to identify patients who have developed distant metastasis or are at high risk as early as possible. This paper aims to predict distant metastasis of thyroid cancer through the construction of machine learning models to provide a reference for clinical diagnosis and treatment. Materials & MethodsData on demographic and clinicopathological characteristics of thyroid cancer patients between 2010 and 2015 were extracted from the National Institutes of Health (NIH) Surveillance, Epidemiology, and End Results (SEER) database. Our research used univariate and multivariate logistic models to screen independent risk factors, respectively. Decision Trees (DT), ElasticNet (ENET), Logistic Regression (LR), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Multilayer Perceptron (MLP), Radial Basis Function Support Vector Machine (RBFSVM) and other seven machine learning models were compared and evaluated by the following metrics: The area under receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), sensitivity(also called recall), speci city, precision, accuracy, F1 score. Interpretable machine learning was used to identify possible correlation between variables and distant metastasis. ResultsIndependent risk factors for distant metastasis, including age, gender, race, marital status, histological type, capsular invasion, and number of lymph nodes metastases were screened by multifactorial regression analysis. Among the seven machine learning algorithms, RF was the best algorithm, with an AUC of 0.948, sensitivity of 0.919, accuracy of 0.845, and F1 score of 0.886 in the training set, and an AUC of 0.960, sensitivity of 0.929, accuracy of 0.906, and F1 score of 0.908 in the test set. ConclusionsThe machine learning model constructed in this study helps in the early diagnosis of distant thyroid metastases and helps physicians to make better decisions and medical interventions.

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Machine learning based on SEER database to predict distant metastasis of thyroid cancer

Qiao,

Li,

Wang

et al. 2023

Preprint

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Objective Distant metastasis of thyroid cancer often indicates poor prognosis, and it is important to identify patients who have developed distant metastasis or are at high risk as early as possible. This paper aims to predict distant metastasis of thyroid cancer through the construction of machine learning models to provide a reference for clinical diagnosis and treatment. Materials & Methods Data on demographic and clinicopathological characteristics of thyroid cancer patients between 2010 and 2015 were extracted from the National Institutes of Health (NIH) Surveillance, Epidemiology, and End Results (SEER) database. Our research used univariate and multivariate logistic models to screen independent risk factors, respectively. Decision Trees (DT), ElasticNet (ENET), Logistic Regression (LR), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Multilayer Perceptron (MLP), Radial Basis Function Support Vector Machine (RBFSVM) and other seven machine learning models were compared and evaluated by the following metrics: The area under receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), sensitivity(also called recall), specificity, precision, accuracy, F1 score. Interpretable machine learning was used to identify possible correlation between variables and distant metastasis. Results Independent risk factors for distant metastasis, including age, gender, race, marital status, histological type, capsular invasion, and number of lymph nodes metastases were screened by multifactorial regression analysis. Among the seven machine learning algorithms, RF was the best algorithm, with an AUC of 0.948, sensitivity of 0.919, accuracy of 0.845, and F1 score of 0.886 in the training set, and an AUC of 0.960, sensitivity of 0.929, accuracy of 0.906, and F1 score of 0.908 in the test set. Conclusions The machine learning model constructed in this study helps in the early diagnosis of distant thyroid metastases and helps physicians to make better decisions and medical interventions.

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Differentiated Thyroid Carcinoma: Distant Metastasis as an Unusual Sole Initial Manifestation

Cited by 3 publications

References 17 publications

Rare sites of metastases in patients with differentiated thyroid carcinoma and added value of SPECT/CT over planar whole body radioactive iodine scan

Rare sites of metastases in patients with differentiated thyroid carcinoma and added value of SPECT/CT over planar whole body radioactive iodine scan

Machine learning based on SEER database to predict distant metastasis of thyroid cancer

Machine learning based on SEER database to predict distant metastasis of thyroid cancer

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