The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter has emerged as a favorable independent prognostic and predictive biomarker in glioma. This study aimed to build a radiomics signature based on 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) for noninvasive measurement of the MGMT promoter methylation status in glioma. One hundred and seven pathology-confirmed primary diffuse glioma patients were retrospectively included and randomly assigned to the primary (n = 71) or validation cohort (n = 36). The MGMT promoter methylation status was measured by pyrosequencing. A total of 1561 radiomics features were extracted from the three-dimensional region of interest (ROI) on the standard uptake value (SUV) maps that were generated from the original 18F-FDG PET data. A radiomics signature, a clinical signature and a fusion signature that combined the clinical and radiomics features together were generated. The performance of the three signatures was evaluated by receiver operating characteristic (ROC) curve analysis, and the patient prognosis was stratified based on the MGMT promoter methylation status and the signature with the best performance. Five radiomics features were selected to construct the radiomics signature, and displayed the best performance with area under the receiver operating characteristic (ROC) curve (AUC) reaching 0.94 and 0.86 in the primary and validation cohorts, respectively, which outweigh the performances of clinical signature and fusion signature. With a median follow-up time of 32.4 months, the radiomics signature stratified the glioma patients into two risk groups with significantly different prognoses (p = 0.04). 18F-FDG-PET-based radiomics is a promising approach for preoperatively evaluating the MGMT promoter methylation status in glioma and predicting the prognosis of glioma patients noninvasively.

Medullary thyroid carcinoma (MTC) can only be cured through the excision of all metastatic lesions, but current clinical practice fails to localize the disease in 29% to 60% of patients. Previously, we developed a fibroblast activation protein inhibitor (FAPI)-based covalent targeted radioligand (CTR) for improved detection sensitivity and accuracy. In this first-in-class clinical trial, we head-to-head compared [68Ga]Ga-CTR-FAPI PET-CT and [18F]fluorodeoxyglucose ([18F]FDG) PET-CT in 50 patients with MTC. The primary endpoint was the patient-based detection rate, with [68Ga]Ga-CTR-FAPI exhibiting higher detection than [18F]FDG (98% vs. 66%, P = 0.0002). This improved detection was attributed to increased tumor uptake (maximum standardized uptake value = 11.71 ± 9.16 vs. 2.55 ± 1.73, P < 0.0001). Diagnostic accuracy, validated on lesions with gold-standard pathology, was greater for [68Ga]Ga-CTR-FAPI compared with [18F]FDG (96.7% vs. 43.3%, P < 0.0001). Notably, the management of 32% of patients was altered following [68Ga]Ga-CTR-FAPI PET-CT, and the surgical plan was changed for 66.7% of patients. Overall, [68Ga]Ga-CTR-FAPI PET-CT provided superior detection and diagnostic accuracy compared with [18F]FDG PET-CT, enabling precision management of patients with MTC. Significance: In this first-in-class clinical trial of CTR, [68Ga]Ga-CTR-FAPI demonstrated an improved patient-based detection rate (98%), tumor uptake (maximum standardized uptake value = 11.71 ± 9.16), and pathology-validated diagnostic accuracy (96.7%) compared with the currently approved method in MTC treatment. It directly altered management in 32% of patients, enabling precision diagnosis and management of MTC. See related commentary by Witney, p. 264

Currently, glioblastoma (GBM) is the most common malignant tumor of the central nervous system in adults. Fibroblast activation protein (FAP) is a member of the dipeptidyl peptidase family, which has catalytic activity and is engaged in protein recruitment and scaffolds. Recent studies have found that FAP expression in different types of cells within the GBM microenvironment is typically upregulated compared with that in lower grade glioma and is most pronounced in the mesenchymal subtype of GBM. As a marker of cancer-associated fibroblasts (CAFs) with tumorigenic activity, FAP has been proven to promote tumor growth and invasion via hydrolysis of molecules such as brevican in the extracellular matrix and targeting of downstream pathways and substrates, such as fibroblast growth factor 21 (FGF21). In addition, based on its ability to suppress antitumor immunity in GBM and induce temozolomide resistance, FAP may be a potential target for immunotherapy and reversing temozolomide resistance; however, current studies on therapies targeting FAP are still limited. In this review, we summarized recent progress in FAP expression profiling and the understanding of the biological function of FAP in GBM and raised the possibility of FAP as an imaging biomarker and therapeutic target.

Background: To explore the feasibility of diffusion-weighted imaging (DWI) metrics to predict the histologic subtypes and genetic status of gliomas (e.g., IDH, MGMT, and TERT) noninvasively. Methods: One hundred and eleven patients with pathologically confirmed WHO grade II-IV gliomas were recruited retrospectively. Apparent diffusion coefficient (ADC) values were measured in solid parts of gliomas on co-registered T2-weighted images and were compared with each other in terms of WHO grading and genotypes using t-tests. Receiver operating characteristic analysis was performed to assess the diagnostic performances of ADC. Subsequently, multiple linear regression was used to find independent variables, which can directly affect ADC values. Results: The values of overall mean ADC (omADC) and normalized ADC (nADC) of high grade gliomas and IDH wildtype gliomas were lower than low grade gliomas and IDH mutated gliomas (P < 0.05). nADC values showed better diagnostic performance than omADC in identifying tumor grade (AUC: 0.787 vs. 0.750) and IDH status (AUC: 0.836 vs. 0.777). ADC values had limited abilities in distinguishing TERT status (AUC = 0.607 for nADC and 0.617 for omADC) and MGMT status (AUC = 0.651 for nADC). Only tumor grade and IDH status were tightly associated with ADC values. Conclusion: DWI metrics can predict glioma grading and IDH mutation noninvasively, but have limited use in detecting TERT mutation and MGMT methylation.