Differentiation of low- and high-grade pediatric gliomas with amide proton transfer imaging: added value beyond quantitative relaxation times.

To evaluate whether amide proton transfer (APT) MRI can be used to characterize gliomas in pediatric patients and whether it provides added value beyond relaxation times. In this prospective study, APT imaging and relaxation time mapping were performed in 203 pediatric patients suspected of gliomas from February 2018 to December 2019. The region of interest (ROI) in the tumor was automatically generated with artifact detection and ROI-shrinking algorithms. Several APT-related metrics (CESTR, CESTRnr, MTRRex, AREX, and APT#) and quantitative T1 and T2 were compared between low-grade and high-grade gliomas using the student's t-test or Mann-Whitney U-test. The performance of these parameters was assessed using the receiver operating characteristic (ROC) analysis. A stepwise multivariate logistic regression model was used to combine the imaging parameters. Forty-eight patients (mean age: 6 ± 4 years; 23 males and 25 females) were included in the final analysis. All the APT-related metrics except APT# had significantly (p < 0.05) higher values in the high-grade group than the low-grade group. Under different ROI-shrinking cutoffs, the quantitative T1 (p = 0.045-0.200) and T2 (p = 0.037-0.171) values of high-grade gliomas were typically lower than those of low-grade ones. The stepwise multivariate logistic regression revealed that CESTRnr and APT# were combined significant predictors of glioma grades (p < 0.05), with an area under the ROC curve (AUC) of 0.86 substantially larger than those of T1 (AUC = 0.69) and T2 (AUC = 0.68). APT imaging can be used to differentiate high-grade and low-grade gliomas in pediatric patients and provide added value beyond quantitative relaxation times. • Amide proton transfer (APT) MRI showed significantly (p < 0.05) higher values in pediatric patients with high-grade gliomas than those with low-grade ones. • The area under the curve was 0.86 for APT MRI to differentiate low-grade and high-grade gliomas in pediatric patients, which was substantially higher than that for quantitative T1 (0.69) and T2 (0.68). • APT MRI demonstrated added value beyond quantitative T1 and T2 mapping in characterizing pediatric gliomas.

Zhang H ，Yong X ，Ma X ，Zhao J ，Shen Z ，Chen X ，Tian F ，Chen W ，Wu D ，Zhang Y ... -  《-》

Amide proton transfer-weighted imaging and derived radiomics in the classification of adult-type diffuse gliomas.

To evaluate the utility of amide proton transfer-weighted (APTw) MRI imaging and its derived radiomics in classifying adult-type diffuse glioma. In this prospective study, APTw imaging was performed on 129 patients with adult-type diffuse gliomas. The mean APTw-related metrics (chemical exchange saturation transfer ratio (CESTR), CESTR normalized with the reference value (CESTRnr), and relaxation-compensated inverse magnetization transfer ratio (MTRRex)) and radiomic features within 3D tumor masks were extracted. APTw-radiomics models were developed using a support vector machine (SVM) classifier. Sensitivity analysis with tumor area of interest, different histogram cutoff values, and other classifiers were conducted. CESTR, CESTRnr, and MTRRex in glioblastomas were all significantly higher (p < 0.0003) than those of oligodendrogliomas and astrocytomas, with no significant difference between oligodendrogliomas and astrocytomas. The APTw-related metrics for IDH-wildtype and high-grade gliomas were significantly higher (p < 0.001) than those for the IDH-mutant and low-grade gliomas, with area under the curve (AUCs) of 0.88 for CESTR. The CESTR-radiomics models demonstrated accuracies of 84% (AUC 0.87), 83% (AUC 0.83), 90% (AUC 0.95), and 84% (AUC 0.86) in predicting the IDH mutation status, differentiating glioblastomas from astrocytomas, distinguishing glioblastomas from oligodendrogliomas, and determining high/low grade prediction, respectively, but showed poor performance in distinguishing oligodendrogliomas from astrocytomas (accuracy 63%, AUC 0.63). The sensitivity analysis affirmed the robustness of the APTw signal and APTw-derived radiomics prediction models. APTw imaging, along with its derived radiomics, presents a promising quantitative approach for prediction IDH mutation and grading adult-type diffuse glioma. Amide proton transfer-weighted imaging, a quantitative imaging biomarker, coupled with its derived radiomics, offers a promising non-invasive approach for predicting IDH mutation status and grading adult-type diffuse gliomas, thereby informing individualized clinical diagnostics and treatment strategies. • This study evaluates the differences of different amide proton transfer-weighted metrics across three molecular subtypes and their efficacy in classifying adult-type diffuse glioma. • Chemical exchange saturation transfer ratio normalized with the reference value and relaxation-compensated inverse magnetization transfer ratio effectively predicts IDH mutation/grading, notably the first one. • Amide proton transfer-weighted imaging and its derived radiomics holds potential to be used as a diagnostic tool in routine clinical characterizing adult-type diffuse glioma.

Wu M ，Jiang T ，Guo M ，Duan Y ，Zhuo Z ，Weng J ，Xie C ，Sun J ，Li J ，Cheng D ，Liu X ，Du J ，Zhang X ，Zhang Y ，Liu Y ... -  《-》

Risk stratification of abdominal tumors in children with amide proton transfer imaging.

To evaluate the potential of molecular amide proton transfer (APT) MRI for predicting the risk group of abdominal tumors in children, and compare it with quantitative T1 and T2 mapping. This prospective study enrolled 133 untreated pediatric patients with suspected abdominal tumors from February 2019 to September 2020. APT-weighted (APTw) imaging and quantitative relaxation time mapping sequences were executed for each subject. The region of interest (ROI) was generated with automatic artifact detection and ROI-shrinking algorithms, within which the APTw, T1, and T2 indices were calculated and compared between different risk groups. The prediction performance of different imaging parameters was assessed with the receiver operating characteristics (ROC) analysis and Student's t-test. Fifty-seven patients were included in the final analysis, including 24 neuroblastomas (NB), 18 Wilms' tumors (WT), and 15 hepatoblastomas (HB). The APTw signal was significantly (p < .001) higher in patients with high-risk NB than those with low-risk NB, while the difference between patients with low-risk and high-risk WT (p = .69) or HB (p = .35) was not statistically significant. The associated areas under the curve (AUC) for APT to differentiate low-risk and high-risk NB, WT, and HB were 0.93, 0.58, and 0.71, respectively. The quantitative T1 and T2 values generated AUCs of 0.61-0.70 for the risk stratification of abdominal tumors. APT MRI is a potential imaging biomarker for stratifying the risk group of pediatric neuroblastoma in the abdomen preoperatively and provides added value to structural MRI. • Amide proton transfer (APT) imaging showed significantly (p < .001) higher values in pediatric patients with high-risk neuroblastoma than those with low-risk neuroblastoma, but did not demonstrate a significant difference in patients with Wilms' tumor (p = .69) or hepatoblastoma (p = .35). • The associated areas under the curve (AUC) for APT to differentiate low-risk and high-risk neuroblastoma, Wilms' tumor, and hepatoblastoma were 0.93, 0.58, and 0.71, respectively. • The quantitative T1 and T2 indices generated AUCs of 0.61-0.70 for dichotomizing the risk group of abdominal tumors.

Jia X ，Wang W ，Liang J ，Ma X ，Chen W ，Wu D ，Lai C ，Zhang Y ... -  《-》

Amide proton transfer imaging to discriminate between low- and high-grade gliomas: added value to apparent diffusion coefficient and relative cerebral blood volume.

Choi YS ，Ahn SS ，Lee SK ，Chang JH ，Kang SG ，Kim SH ，Zhou J ... -  《-》

Diagnostic performance of gliomas grading and IDH status decoding A comparison between 3D amide proton transfer APT and four diffusion-weighted MRI models.

The focus of neuro-oncology research has changed from histopathologic grading to molecular characteristics, and medical imaging routinely follows this change. To compare the diagnostic performance of amide proton transfer (APT) and four diffusion models in gliomas grading and isocitrate dehydrogenase (IDH) genotype. Prospective. A total of 62 participants (37 males, 25 females; mean age, 52 ± 13 years) whose IDH genotypes were mutant in 6 of 14 grade II gliomas, 8 of 20 of grade III gliomas, and 4 of 28 grade IV gliomas. APT imaging using sampling perfection with application optimized contrasts by using different flip angle evolutions (SPACE) and DWI with q-space Cartesian grid sampling were acquired at 3 T. The ability of diffusion kurtosis imaging, diffusion kurtosis imaging, neurite orientation dispersion and density imaging (NODDI), mean apparent propagator (MAP), and APT imaging for glioma grade and IDH status were assessed, with histopathological grade and genetic testing used as a reference standard. Regions of interest (ROIs) were drawn by two neuroradiologists after consensus. T-test and Mann-Whitney U test; one-way analysis of variance (ANOVA); receiver operating curve (ROC) and area under the curve (AUC); DeLong test. P value < 0.05 was considered statistically significant. Compared with IDH-mutant gliomas, IDH-wildtype gliomas showed a significantly higher mean, 5th-percentile (APT5 ), and 95th-percentile from APTw, the 95th-percentile value of axial, mean, and radial diffusivity from DKI, and 95th-percentile value of isotropic volume fraction from NODDI, and no significantly different parameters from DTI and MAP (P = 0.075-0.998). The combined APT model showed a significantly wider area under the curve (AUC 0.870) for IDH status, when compared with DKI and NODDI. APT5 was significantly different between two of the three groups (glioma II vs. glioma III vs. glioma IV: 1.35 ± 0.75 vs. 2.09 ± 0.93 vs. 2.71 ± 0.81). APT has higher diagnostic accuracy than DTI, DKI, MAP, and NODDI in glioma IDH genotype. APT5 can effectively identify both tumor grading and IDH genotyping, making it a promising biomarker for glioma classification. 1 TECHNICAL EFFICACY: Stage 2.

Guo H ，Liu J ，Hu J ，Zhang H ，Zhao W ，Gao M ，Zhang Y ，Yang G ，Cui Y ... -  《-》