Thyroid Cancer, Thyroid Nodule
Conditions
Keywords
Thyroid Cancer, Artificial Intelligence, Ultrasound, Preoperative Assessment
Brief summary
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.
Detailed description
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.
Interventions
DIAGNOSTIC_TESTLocked AI-Assisted Thyroid Ultrasound Repeat Examination and Review
After standard preoperative ultrasonography, the same participant underwent a standardized AI-assisted repeat examination. The locked system identified and classified thyroid nodules and provided malignancy-score information for surgeon-led review. It did not assess cervical lymph nodes and was not retrained or recalibrated during the study. Additional fine-needle aspiration, intraoperative pathologic examination, and surgical management were determined by clinicians using the complete clinical assessment.
Sponsors
Fujian Medical University
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Intervention model description
All enrolled participants underwent the same surgeon-led workflow: standard preoperative ultrasound followed by review of a locked AI nodule-assessment output. Concordant and discordant findings were workflow strata, not assigned study arms. Additional pathological examination and management changes were clinician directed.
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Proportion of Participants Undergoing Supplementary Cytologic or Pathologic Examination | From completion of the AI-assisted repeat examination through completion of surgery | Number and proportion of enrolled participants who underwent at least one additional cytologic or pathologic examination, such as fine-needle aspiration or intraoperative frozen-section examination, after completion of conventional ultrasonography and AI-assisted review and before completion of surgery. Each participant is counted once regardless of the number of examinations. The decision remained clinician led; cervical lymph-node examinations were outside the AI system's task. |
| Proportion of Participants With a Change in Planned Surgical Management | From completion of the AI-assisted review through surgery | Number and proportion of enrolled participants with at least one documented change in the surgeon-led planned surgical approach or extent after conventional ultrasonography, AI-assisted review, and any supplementary pathological examination, when performed. Changes may involve thyroid resection or cervical lymph-node management. Each participant is counted once regardless of the number of changes. The AI system provided thyroid-nodule information only and did not assess cervical lymph nodes. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Distribution of C-TIRADS Categories Among Evaluated Thyroid Nodules | During standard preoperative ultrasonography, before the AI-assisted repeat examination | Number and percentage of evaluated thyroid nodules in each clinician-assigned C-TIRADS category during conventional ultrasonography. Nodule size, composition, echogenicity, margins, calcifications, and clinician-assessed cervical lymph-node findings were recorded as descriptive covariates and were not treated as separate outcome measures. |
| Proportion of Evaluated Thyroid Nodules Classified as AI-Positive | During the preoperative AI-assisted repeat examination, before surgery | Number and percentage of evaluated thyroid nodules with a locked AI malignancy score \>0.5. The AI system evaluated thyroid nodules only and did not assess cervical lymph nodes. |
| Results of Supplementary Cytologic or Pathologic Examinations | From supplementary sampling to availability of the corresponding result, before or during surgery | Among participants who underwent at least one additional cytologic or pathologic examination, record the cytologic or histopathologic result for each sampled thyroid nodule or cervical lymph node. Results are summarized at the examination level as nonmalignant, indeterminate, malignant, or metastatic, as applicable. |
| Final Histopathological Diagnosis of Resected Thyroid Nodules | From surgery until the final postoperative histopathology report became available; assessed through October 15, 2025, over the approximately 14-month study period. | For each resected thyroid nodule linked unambiguously to the evaluated lesion, record the final diagnosis as benign, malignant, follicular tumor of uncertain malignant potential (FT-UMP), well-differentiated tumor of uncertain malignant potential (WDT-UMP), non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), or another borderline diagnosis. |
| Nodule-Level Sensitivity of AI and C-TIRADS | From the preoperative examinations until the final postoperative histopathology report became available; assessed through October 15, 2025, over the approximately 14-month study period. | Using definitive postoperative histopathology as the reference standard, sensitivity is TP/(TP + FN), expressed as a percentage, for the locked AI classification (positive if score \>0.5) and conventional C-TIRADS (positive if category 4a or higher). Include only pathology-matched nodules with an unambiguous lesion-level link and a definitive benign or malignant diagnosis. Exclude FT-UMP, WDT-UMP, NIFTP, other borderline diagnoses, and nodules without unambiguous lesion-level linkage. These lesion-level exclusions do not alter the 515-participant workflow cohort. |
| Nodule-Level False-Negative Rate of AI and C-TIRADS | From the preoperative examinations until the final postoperative histopathology report became available; assessed through October 15, 2025, over the approximately 14-month study period. | For each method, the false-negative rate is FN/(TP + FN), expressed as a percentage, among definitively malignant thyroid nodules. AI positivity is defined as score \>0.5; conventional ultrasound positivity is C-TIRADS category 4a or higher. Include only pathology-matched nodules with an unambiguous lesion-level link and a definitive benign or malignant diagnosis. Exclude FT-UMP, WDT-UMP, NIFTP, other borderline diagnoses, and nodules without unambiguous lesion-level linkage. |
| Nodule-Level Positive Predictive Value of AI and C-TIRADS | From the preoperative examinations until the final postoperative histopathology report became available; assessed through October 15, 2025, over the approximately 14-month study period. | For each method, positive predictive value is TP/(TP + FP), expressed as a percentage, among thyroid nodules classified as positive. AI positivity is defined as score \>0.5; conventional ultrasound positivity is C-TIRADS category 4a or higher. Include only pathology-matched nodules with an unambiguous lesion-level link and a definitive benign or malignant diagnosis. Exclude FT-UMP, WDT-UMP, NIFTP, other borderline diagnoses, and nodules without unambiguous lesion-level linkage. |
| Nodule-Level Youden Index of AI and C-TIRADS | From the preoperative examinations until the final postoperative histopathology report became available; assessed through October 15, 2025, over the approximately 14-month study period. | For each method, the Youden index is sensitivity + specificity - 1 using fixed binary thresholds. AI positivity is defined as score \>0.5; conventional ultrasound positivity is C-TIRADS category 4a or higher. Include only pathology-matched nodules with an unambiguous lesion-level link and a definitive benign or malignant diagnosis. Exclude FT-UMP, WDT-UMP, NIFTP, other borderline diagnoses, and nodules without unambiguous lesion-level linkage. |
| Distribution of Cervical Lymph-Node Metastasis Status Among Pathologically Examined Nodes | From surgery or supplementary sampling until the corresponding pathology result became available; assessed through October 15, 2025, over the approximately 14-month study period. | Among cervical lymph nodes actually removed or sampled and pathologically examined, record the number and percentage with and without metastasis. No pathologic reference diagnosis is assigned to unsampled lymph nodes. |
| Nodule-Level Specificity of AI and C-TIRADS | From the preoperative examinations until the final postoperative histopathology report became available; assessed through October 15, 2025, over the approximately 14-month study period. | Using definitive postoperative histopathology as the reference standard, specificity is TN/(TN + FP), expressed as a percentage, for the locked AI classification (positive if score \>0.5) and conventional C-TIRADS (positive if category 4a or higher). Include only pathology-matched nodules with an unambiguous lesion-level link and a definitive benign or malignant diagnosis. Exclude FT-UMP, WDT-UMP, NIFTP, other borderline diagnoses, and nodules without unambiguous lesion-level linkage. |
| Nodule-Level Negative Predictive Value of AI and C-TIRADS | From the preoperative examinations until the final postoperative histopathology report became available; assessed through October 15, 2025, over the approximately 14-month study period. | Using definitive postoperative histopathology as the reference standard, negative predictive value is TN/(TN + FN), expressed as a percentage, for the locked AI classification (positive if score \>0.5) and conventional C-TIRADS (positive if category 4a or higher). Include only pathology-matched nodules with an unambiguous lesion-level link and a definitive benign or malignant diagnosis. Exclude FT-UMP, WDT-UMP, NIFTP, other borderline diagnoses, and nodules without unambiguous lesion-level linkage. |
| Nodule-Level Accuracy of AI and C-TIRADS | From the preoperative examinations until the final postoperative histopathology report became available; assessed through October 15, 2025, over the approximately 14-month study period. | Using definitive postoperative histopathology as the reference standard, accuracy is (TP + TN)/(TP + TN + FP + FN), expressed as a percentage, for the locked AI classification (positive if score \>0.5) and conventional C-TIRADS (positive if category 4a or higher). Include only pathology-matched nodules with an unambiguous lesion-level link and a definitive benign or malignant diagnosis. Exclude FT-UMP, WDT-UMP, NIFTP, other borderline diagnoses, and nodules without unambiguous lesion-level linkage. |
| Area Under the ROC Curve for the Continuous AI Malignancy Score | From the preoperative examinations until the final postoperative histopathology report became available; assessed through October 15, 2025, over the approximately 14-month study period. | Using definitive postoperative histopathology as the reference standard, calculate the area under the receiver operating characteristic curve for the continuous locked AI malignancy score. Include only pathology-matched nodules with an unambiguous lesion-level link and a definitive benign or malignant diagnosis. Exclude FT-UMP, WDT-UMP, NIFTP, other borderline diagnoses, and nodules without unambiguous lesion-level linkage. No AUC is calculated for the single-threshold C-TIRADS classification. |
Countries
China
Outcome results
None listed