Lei Zhang

Rationale: Persistent midline radioiodine uptake after thyroid remnant ablation can mimic metastatic disease and lead to unnecessary re-treatment. We report a case of persistent iodine-131 ( ¹³¹ I) uptake in the thyroglossal duct region with undetectable thyroglobulin (Tg). Patient concerns: A 45-year-old woman was found to have thyroid nodules on routine ultrasound, and further evaluation supported papillary thyroid carcinoma. Diagnoses: After total thyroidectomy and central neck dissection, post-ablation and follow-up ¹³¹ I imaging demonstrated persistent focal uptake in the midline neck. Single photon emission computed tomography, computed tomography (SPECT/CT) localized the activity to the thyroglossal duct tract, while repeated serum Tg remained undetectable and no structural lesion was identified, supporting a benign thyroglossal duct remnant. Interventions: The patient underwent total thyroidectomy with central neck dissection, followed by 100 mCi ¹³¹ I remnant ablation after thyroid hormone withdrawal. She then received levothyroxine for thyroid-stimulating hormone suppression. Six months later, levothyroxine was withdrawn again for 4 weeks, and a low-dose diagnostic ¹³¹ I scan (3 mCi) with SPECT/CT was performed. Outcomes: Diagnostic ¹³¹ I imaging at 6 months again demonstrated persistent uptake at the same thyroglossal duct site, with no uptake in the thyroid bed, undetectable Tg, and no structural evidence of recurrent disease. The patient was managed conservatively with thyroid-stimulating hormone suppression and periodic biochemical and ultrasound follow-up. Lessons: For isolated midline ¹³¹ I uptake after ablation, SPECT/CT localization along the thyroglossal duct tract combined with undetectable Tg supports a benign thyroglossal duct remnant and favors observation with structured follow-up over empiric repeat ablation.

Background: This study evaluates the effectiveness of radiomics based on 18F-fluorodeoxyglucose positron emission tomography/computed tomography ( ¹⁸ F-FDG PET/CT) in distinguishing lung adenocarcinoma from squamous cell carcinoma, the 2 major subtypes of non-small cell lung cancer (NSCLC). Methods: We extracted radiomic features from both the intratumoral and peritumoral areas in NSCLC patients’ PET/CT scans. The intratumoral volume of interest (VOI_I) was manually outlined on PET/CT images. Additionally, 4 peritumoral VOIs (VOI_P) were automatically generated by expanding VOI_I by 1, 2, 3, and 4 mm. A total of 107 radiomic features were extracted from each VOI. Feature selection was conducted using the t test, Spearman correlation analysis, and the least absolute shrinkage and selection operator. Subsequently, radiomics models (VOI_I model, VOI_P model, and a combined model) were constructed. The models’ performance was assessed by the area under the curve (AUC). Results: In the training set, the intratumoral (VOI_PET_I) model achieved the highest AUC (0.973), followed by the peritumoral 1 mm (VOI_PET_P1) model (AUC = 0.952). However, in the independent testing set, the VOI_PET_P1 model outperformed the VOI_PET_I model, achieving the highest AUC of 0.931 versus 0.920, respectively. This suggests that the peritumoral 1 mm region may provide superior generalizability for subtype classification in unseen data. Conclusion: In this study, radiomics features extracted from both intratumoral and peritumoral regions on 18F-FDG PET/CT demonstrated high predictive value for classifying NSCLC pathological subtypes. Notably, the 1 mm peritumoral region exhibited the best performance for differentiating lung adenocarcinomas, especially in the independent testing cohort. However, these findings are based on a single-center cohort with a limited sample size and require further validation in larger, multicenter studies to confirm their clinical utility and generalizability.

Positron emission tomography/computed tomography (PET/CT) has emerged as a crucial tool in neuroimaging, offering valuable insights into the diagnosis and management of neurological disorders. This chapter explores the clinical applications of PET/CT through a series of case studies, highlighting its role in identifying metabolic and functional alterations in the brain. By analyzing diagnostic images, key imaging features and signal abnormalities that contribute to accurate disease characterization are discussed. Special emphasis is placed on the interpretation of PET/CT findings in conditions such as neurodegenerative diseases, epilepsy, and brain tumors, demonstrating its advantages over conventional imaging techniques. The integration of PET and CT modalities enhances anatomical localization and functional assessment, providing clinicians with critical information for treatment planning. Additionally, emerging advances in radiotracers and quantitative analysis techniques are addressed, underscoring the expanding potential of PET/CT in neuroimaging. This chapter aims to enhance the understanding of PET/CT’s diagnostic value, offering insights that bridge research findings with real-world clinical practice.

Purpose Accurate diagnosis and staging of lung cancer are critical for optimal clinical management. Fibroblast activation protein inhibitor (FAPI) imaging has emerged as a promising modality with superior detection capabilities for lung cancer. We hypothesized that [¹⁸F]FAPI-42 PET/CT would enhance diagnosis, TNM staging, and influence oncologic management in patients with suspected or confirmed lung cancer. Methods In this retrospective study, 155 patients with clinically suspected or confirmed lung cancer underwent both conventional imaging and [¹⁸F]FAPI-42 PET/CT scans within a one-week interval, without any intervening treatment. Lesions were visually assessed and categorized to evaluate the diagnostic capability of [¹⁸F]FAPI-42 PET/CT. Tracer activity was quantified using maximum standardized uptake values (SUV_max) and tumor-to-background ratios. TNM staging was independently determined by a board-certified radiologist or nuclear medicine physician using both imaging modalities, and discrepancies were assessed. Changes in TNM staging were documented and evaluated for their impact on clinical management. Results Of the 155 patients, 99 were evaluated for primary lesion diagnosis and staging. Pathological examination confirmed malignant tumors in 87 patients and benign tumors in 12. The diagnostic sensitivity and positive predictive value of [¹⁸F]FAPI-42 PET/CT for detecting primary lung tumors were 96.77% and 92.78%, respectively. Malignant lesions exhibited significantly higher SUV_max compared to benign lesions (5.2 vs. 1.5, P = 0.0002), with an area under the ROC curve of 0.87. In total, 1,556 malignant lesions were identified among patients with lung cancer, and [¹⁸F]FAPI-42 PET/CT demonstrated a diagnostic accuracy of 95.50%. However, its sensitivity for detecting adrenal metastases was lower at 33.33%, with a specificity of 100% and an accuracy of 53.85%. The use of [¹⁸F]FAPI-42 PET/CT resulted in changes in TNM staging for 46% of patients, leading to upstaging in 58 patients and downstaging in 5. These staging adjustments directly impacted clinical management in 34 patients, prompting modifications in treatment plans. Conclusion [¹⁸F]FAPI-42 PET/CT is a promising modality for lung cancer diagnosis and staging, demonstrating high sensitivity and specificity. Its use significantly altered TNM staging in nearly half of the patients, directly impacting oncologic management and treatment planning. However, its limited sensitivity for detecting adrenal metastases underscores the need for additional imaging techniques.