AI-Assisted Ultrasound Review Before Thyroid Surgery

Clinical Application of AI-assisted Ultrasound Technology in the Preoperative Evaluation of Thyroid Cancer

This prospective, single-center, single-arm study evaluates a locked artificial intelligence (AI) system as a surgeon-led second-read tool before thyroid surgery. Eligible participants scheduled for thyroid surgery undergo standard ultrasonography followed by a standardized AI-assisted repeat examination. The AI system evaluates thyroid nodules only; cervical lymph nodes are assessed by clinicians. The study assesses participant-level supplementary pathological examinations and treatment-decision changes and evaluates nodule-level diagnostic performance against final surgical histopathology.

This prospective, single-center, single-arm study evaluates a locked AI-assisted ultrasound system used during surgeon-led preoperative review in participants scheduled for thyroid surgery. Each participant undergoes standard preoperative ultrasonography followed by a standardized AI-assisted repeat examination. The locked system provides thyroid-nodule malignancy scores and classifications; it was not retrained or recalibrated during the study and did not assess cervical lymph nodes. Clinicians integrate standard ultrasound, cytology, clinical findings, and other information and retain responsibility for all supplementary examinations and final management decisions. The two primary outcomes are participant-level: (1) whether a participant undergoes an additional cytologic or pathologic examination and (2) whether a participant has at least one change in planned surgical management. Participants are counted once within each outcome, while event counts may be summarized separately. The embedded diagnostic analysis is nodule-level and uses unambiguously pathology-matched surgical histopathology as the reference standard. Only nodules with a definitive benign or malignant surgical histopathological diagnosis are included in binary diagnostic-performance calculations. Low-risk or borderline thyroid neoplasms, including follicular tumors of uncertain malignant potential (FT-UMP), well-differentiated tumors of uncertain malignant potential (WDT-UMP), and non-invasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP), and nodules without unambiguous lesion-level linkage are excluded from binary reference-standard analyses. These post-enrollment analysis exclusions do not alter the 515-participant actual enrollment or the participant-level workflow cohort. A participant may contribute another eligible nodule if that lesion has an unambiguous definitive diagnosis. Cervical lymph-node pathology is described only for nodes actually removed or sampled; no reference diagnosis is assigned to unsampled nodes.

Inclusion Criteria:

• Patients with preoperative pathological confirmation of thyroid malignant tumors undergoing surgical treatment.
• Patients with benign thyroid tumors, such as thyroid adenomas causing compressive symptoms, undergoing surgical treatment.
• Patients with complete and high-quality traditional two-dimensional color ultrasound images.
• Complete postoperative pathology reports.
• Willingness to participate in this clinical trial and signing of informed consent.

Exclusion Criteria:

• Patients with a history of neck surgery or radiotherapy.
• Patients with a history of malignant tumors in other parts of the body.
• Patients with thyroid dysfunction.
• Incomplete or poor-quality traditional two-dimensional color ultrasound images.
• Incomplete postoperative pathology reports.
• Refusal to participate in this clinical trial.