Integrated Diagnostics of Thyroid Nodules Thyroid nodules are common in clinical practice, and their diagnosis and treatment involve multiple specialists and various methods. Proper diagnosis requires integrating laboratory, imaging, and pathology exams to avoid unnecessary procedures and identify patients needing specific therapies. Bioinformatics may improve personalized diagnosis, but the clinical impact of AI needs further study, especially in indeterminate cytology cases requiring diagnostic surgery. Thyroid nodules are more common in iodine-deficient regions and in women. Most are benign, but risk factors include ionizing radiation, rapid growth, hoarseness, and family history. US is crucial for risk stratification, with scoring systems helping differentiate benign and malignant nodules. FNAC is recommended for suspicious cases, but hyperfunctioning nodules are usually benign. Thyroid scintigraphy is essential for detecting hyperfunctioning nodules. Molecular imaging with Tc-MIBI and FDG can avoid unnecessary surgeries. AI's role in thyroid nodule evaluation needs further study. Thyroid US is the first-line imaging method, with scoring systems like TI-RADS for risk stratification. Different systems are used globally, with variations in risk categories. Nuclear medicine, including scintigraphy, helps assess thyroid function. Molecular imaging with Tc-MIBI and FDG can improve diagnostic accuracy. FNAC is used for non-autonomous nodules, but indeterminate cases may benefit from molecular imaging to avoid surgery. Fine-needle aspiration cytology (FNAC) is a key diagnostic tool, with guidelines recommending biopsy based on ultrasound findings. The Bethesda System classifies cytology results, with indeterminate cases requiring further testing. Molecular markers, such as BRAF and RAS mutations, help differentiate benign and malignant nodules. These markers are used in indeterminate cases to rule in or out cancer. Integrated diagnostics combine imaging, laboratory tests, and molecular markers to improve thyroid nodule management. This approach helps avoid unnecessary procedures, improves patient outcomes, and reduces healthcare costs. Future research should focus on AI and molecular markers to enhance diagnostic accuracy and personalized treatment.Integrated Diagnostics of Thyroid Nodules Thyroid nodules are common in clinical practice, and their diagnosis and treatment involve multiple specialists and various methods. Proper diagnosis requires integrating laboratory, imaging, and pathology exams to avoid unnecessary procedures and identify patients needing specific therapies. Bioinformatics may improve personalized diagnosis, but the clinical impact of AI needs further study, especially in indeterminate cytology cases requiring diagnostic surgery. Thyroid nodules are more common in iodine-deficient regions and in women. Most are benign, but risk factors include ionizing radiation, rapid growth, hoarseness, and family history. US is crucial for risk stratification, with scoring systems helping differentiate benign and malignant nodules. FNAC is recommended for suspicious cases, but hyperfunctioning nodules are usually benign. Thyroid scintigraphy is essential for detecting hyperfunctioning nodules. Molecular imaging with Tc-MIBI and FDG can avoid unnecessary surgeries. AI's role in thyroid nodule evaluation needs further study. Thyroid US is the first-line imaging method, with scoring systems like TI-RADS for risk stratification. Different systems are used globally, with variations in risk categories. Nuclear medicine, including scintigraphy, helps assess thyroid function. Molecular imaging with Tc-MIBI and FDG can improve diagnostic accuracy. FNAC is used for non-autonomous nodules, but indeterminate cases may benefit from molecular imaging to avoid surgery. Fine-needle aspiration cytology (FNAC) is a key diagnostic tool, with guidelines recommending biopsy based on ultrasound findings. The Bethesda System classifies cytology results, with indeterminate cases requiring further testing. Molecular markers, such as BRAF and RAS mutations, help differentiate benign and malignant nodules. These markers are used in indeterminate cases to rule in or out cancer. Integrated diagnostics combine imaging, laboratory tests, and molecular markers to improve thyroid nodule management. This approach helps avoid unnecessary procedures, improves patient outcomes, and reduces healthcare costs. Future research should focus on AI and molecular markers to enhance diagnostic accuracy and personalized treatment.