Temporal Evolution and Prognostic Role of Indeterminate Response Sub-Groups in Patients with Differentiated Thyroid Cancer after Initial Therapy with Radioiodine

Prognostic role and characteristics of the indeterminate response in differentiated thyroid cancer: a systematic review

PURPOSE

The management of differentiated thyroid cancer (DTC) is actually based on a dynamic risk stratification based on classes of response to the therapy. Indeterminate response (IR) includes a heterogeneous group of patients with different characteristics, particularly different Tg and AbTg levels and/or imaging findings. The aim of systematic review (SR) is to evaluate the prognosis, diagnostic findings and other characteristics of patients in the IR class.

METHODS

A wide literature search in the Scopus, PubMed/MEDLINE and Web of Science databases was performed to find published articles on patients with DTC and IR after treatment. The quality assessment of studies was carried out using QUADAS-2 evaluation.

RESULTS

Eight articles were included in the systematic review. Six studies evaluated the prognosis and the prognostic factor in patients with IR, one study evaluated the role of 2-[18F]FDG PET-CT in the management of patients with IR and biochemical incomplete response and one study the risk factors for IR.

CONCLUSION

Patients with DTC and IR to therapy have a probability of disease relapse < 15%. Tg value could be a predictor of disease progression. The role of 2-[18F]FDG PET-CT needs to be further investigated.

Application of radiomics and machine learning to thyroid diseases in nuclear medicine: a systematic review

BACKGROUND

In the last years growing evidences on the role of radiomics and machine learning (ML) applied to different nuclear medicine imaging modalities for the assessment of thyroid diseases are starting to emerge. The aim of this systematic review was therefore to analyze the diagnostic performances of these technologies in this setting.

METHODS

A wide literature search of the PubMed/MEDLINE, Scopus and Web of Science databases was made in order to find relevant published articles about the role of radiomics or ML on nuclear medicine imaging for the evaluation of different thyroid diseases.

RESULTS

Seventeen studies were included in the systematic review. Radiomics and ML were applied for assessment of thyroid incidentalomas at 18 F-FDG PET, evaluation of cytologically indeterminate thyroid nodules, assessment of thyroid cancer and classification of thyroid diseases using nuclear medicine techniques.

CONCLUSION

Despite some intrinsic limitations of radiomics and ML may have affect the results of this review, these technologies seem to have a promising role in the assessment of thyroid diseases. Validation of preliminary findings in multicentric studies is needed to translate radiomics and ML approaches in the clinical setting.