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Purpose: To explore the value of 3D amide proton transfer weighted imaging (APTWI) in the differential diagnosis between benign and malignant bone tumors, and to compare the diagnostic performance of APTWI with traditional diffusionweighted imaging (DWI). Materials and methods: Patients with bone tumors located in the pelvis or lower limbs confirmed by puncture or surgical pathology were collected from January 2021 to July 2023 in the First Affiliated Hospital of Zhengzhou University. All patients underwent APTWI and DWI examinations. The magnetization transfer ratio with asymmetric analysis at the frequency offset of 3.5 ppm [MTRasym(3.5 ppm)] derived by APTWI and the apparent diffusion coefficient (ADC) derived by DWI for the tumors were measured. The Kolmogorou-Smirnou and Levene normality test was used to confirm the normal distribution of imaging parameters; and the independent sample t test was used to compare the differences in MTRasym(3.5 ppm) and ADC between benign and malignant bone tumors. In addition, the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of different imaging parameters in differentiation between benign and malignant bone tumors. P<0.05 means statistically significant. Results: Among 85 bone tumor patients, 33 were benign and 52 were malignant. The MTRasym(3.5 ppm) values of malignant bone tumors were significantly higher than those of benign tumors, while the ADC valueswere significantly lower in benign tumors. ROC analysis shows thatMTRasym(3.5 ppm) and ADC values perform well in the differential diagnosis of benign and malignant bone tumors, with the area under the ROC curve (AUC) of 0.798 and 0.780, respectively. Combination of MTRasym(3.5 ppm) and ADC values can further improve the diagnostic performance with the AUC of 0.849 (sensitivity = 84.9% and specificity = 73.1%). Conclusion: MTRasym(3.5 ppm) ofmalignant bone tumors was significantly higher than that of benign bone tumors, reflecting the abnormal increase of protein synthesis in malignant tumors. APTWI combined with DWI can achieve a high diagnostic efficacy in differentiation between benign and malignant bone tumors. [ABSTRACT FROM AUTHOR]

Amide proton transfer weighted (APTw) imaging enables in vivo assessment of tissue‐bound mobile proteins and peptides through the detection of chemical exchange saturation transfer. Promising applications of APTw imaging have been shown in adult brain tumors. As pediatric brain tumors differ from their adult counterparts, we investigate the radiological appearance of pediatric brain tumors on APTw imaging. APTw imaging was conducted at 3 T. APTw maps were calculated using magnetization transfer ratio asymmetry at 3.5 ppm. First, the repeatability of APTw imaging was assessed in a phantom and in five healthy volunteers by calculating the within‐subject coefficient of variation (wCV). APTw images of pediatric brain tumor patients were analyzed retrospectively. APTw levels were compared between solid tumor tissue and normal‐appearing white matter (NAWM) and between pediatric high‐grade glioma (pHGG) and pediatric low‐grade glioma (pLGG) using t‐tests. APTw maps were repeatable in supratentorial and infratentorial brain regions (wCV ranged from 11% to 39%), except those from the pontine region (wCV between 39% and 50%). APTw images of 23 children with brain tumor were analyzed (mean age 12 years ± 5, 12 male). Significantly higher APTw values are present in tumor compared with NAWM for both pHGG and pLGG (p < 0.05). APTw values were higher in pLGG subtype pilocytic astrocytoma compared with other pLGG subtypes (p < 0.05). Non‐invasive characterization of pediatric brain tumor biology with APTw imaging could aid the radiologist in clinical decision‐making. [ABSTRACT FROM AUTHOR]

Abstract Background 1p/19q co-deletion in low-grade gliomas (LGG, World Health Organization grade II and III) is of great significance in clinical decision making. We aim to use radiomics analysis to predict 1p/19q co-deletion in LGG based on amide proton transfer weighted (APTw), diffusion weighted imaging (DWI), and conventional MRI. Methods This retrospective study included 90 patients histopathologically diagnosed with LGG. We performed a radiomics analysis by extracting 8454 MRI-based features form APTw, DWI and conventional MR images and applied a least absolute shrinkage and selection operator (LASSO) algorithm to select radiomics signature. A radiomics score (Rad-score) was generated using a linear combination of the values of the selected features weighted for each of the patients. Three neuroradiologists, including one experienced neuroradiologist and two resident physicians, independently evaluated the MR features of LGG and provided predictions on whether the tumor had 1p/19q co-deletion or 1p/19q intact status. A clinical model was then constructed based on the significant variables identified in this analysis. A combined model incorporating both the Rad-score and clinical factors was also constructed. The predictive performance was validated by receiver operating characteristic curve analysis, DeLong analysis and decision curve analysis. P

Background: 1p/19q co-deletion in low-grade gliomas (LGG, World Health Organization grade II and III) is of great significance in clinical decision making. We aim to use radiomics analysis to predict 1p/19q co-deletion in LGG based on amide proton transfer weighted (APTw), diffusion weighted imaging (DWI), and conventional MRI. Methods: This retrospective study included 90 patients histopathologically diagnosed with LGG. We performed a radiomics analysis by extracting 8454 MRI-based features form APTw, DWI and conventional MR images and applied a least absolute shrinkage and selection operator (LASSO) algorithm to select radiomics signature. A radiomics score (Rad-score) was generated using a linear combination of the values of the selected features weighted for each of the patients. Three neuroradiologists, including one experienced neuroradiologist and two resident physicians, independently evaluated the MR features of LGG and provided predictions on whether the tumor had 1p/19q co-deletion or 1p/19q intact status. A clinical model was then constructed based on the significant variables identified in this analysis. A combined model incorporating both the Rad-score and clinical factors was also constructed. The predictive performance was validated by receiver operating characteristic curve analysis, DeLong analysis and decision curve analysis. P < 0.05 was statistically significant. Results: The radiomics model and the combined model both exhibited excellent performance on both the training and test sets, achieving areas under the curve (AUCs) of 0.948 and 0.966, as well as 0.909 and 0.896, respectively. These results surpassed the performance of the clinical model, which achieved AUCs of 0.760 and 0.766 on the training and test sets, respectively. After performing Delong analysis, the clinical model did not significantly differ in predictive performance from three neuroradiologists. In the training set, both the radiomic and combined models performed better than all neuroradiologists. In the test set, the models exhibited higher AUCs than the neuroradiologists, with the radiomics model significantly outperforming resident physicians B and C, but not differing significantly from experienced neuroradiologist. Conclusions: Our results suggest that our algorithm can noninvasively predict the 1p/19q co-deletion status of LGG. The predictive performance of radiomics model was comparable to that of experienced neuroradiologist, significantly outperforming the diagnostic accuracy of resident physicians, thereby offering the potential to facilitate non-invasive 1p/19q co-deletion prediction of LGG. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the difference in amide proton transfer (APT)-weighted imaging between glioblastoma and brain metastasis. Materials and Methods: Fourteen patients including eight males and six females, with age ranging between 46 and 75 years old, were included in the present study. Ten patients with glioblastomas and four patients with brain metastases underwent preoperative brain 3T-MRI with APT-weighted sequence. The magnetization transfer ratio asymmetry (MTRasym) and normalized magnetization transfer ratio asymmetry (nMTRasym) values in enhancing solid portion, peritumoral non-enhancing hyperintense FLAIR area, and contralateral normal appearing white matter (CNAWM) in glioblastomas and brain metastases were obtained and compared for statistical analyses. Final diagnosis was validated by pathological results. Results: The MTRasym and nMTRasym in enhancing solid portion and peritumoral non-enhancing hyperintense FLAIR area of glioblastomas were significantly greater than that of the brain metastases. By visual assessment, the APTw color map also showed higher signal at the perilesional edema in glioblastomas than the metastasis. Conclusion: As a non-invasive imaging method, APT-weighted MR imaging might be helpful to distinguish glioblastomas from brain metastasis. [ABSTRACT FROM AUTHOR]

Purpose: To explore the value of 3D amide proton transfer weighted imaging (APTWI) in the differential diagnosis between benign and malignant bone tumors, and to compare the diagnostic performance of APTWI with traditional diffusion-weighted imaging (DWI)., Materials and Methods: Patients with bone tumors located in the pelvis or lower limbs confirmed by puncture or surgical pathology were collected from January 2021 to July 2023 in the First Affiliated Hospital of Zhengzhou University. All patients underwent APTWI and DWI examinations. The magnetization transfer ratio with asymmetric analysis at the frequency offset of 3.5 ppm [MTRasym(3.5 ppm)] derived by APTWI and the apparent diffusion coefficient (ADC) derived by DWI for the tumors were measured. The Kolmogorou-Smirnou and Levene normality test was used to confirm the normal distribution of imaging parameters; and the independent sample t test was used to compare the differences in MTRasym(3.5 ppm) and ADC between benign and malignant bone tumors. In addition, the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of different imaging parameters in differentiation between benign and malignant bone tumors. P<0.05 means statistically significant., Results: Among 85 bone tumor patients, 33 were benign and 52 were malignant. The MTRasym(3.5 ppm) values of malignant bone tumors were significantly higher than those of benign tumors, while the ADC values were significantly lower in benign tumors. ROC analysis shows that MTRasym(3.5 ppm) and ADC values perform well in the differential diagnosis of benign and malignant bone tumors, with the area under the ROC curve (AUC) of 0.798 and 0.780, respectively. Combination of MTRasym(3.5 ppm) and ADC values can further improve the diagnostic performance with the AUC of 0.849 (sensitivity = 84.9% and specificity = 73.1%)., Conclusion: MTRasym(3.5 ppm) of malignant bone tumors was significantly higher than that of benign bone tumors, reflecting the abnormal increase of protein synthesis in malignant tumors. APTWI combined with DWI can achieve a high diagnostic efficacy in differentiation between benign and malignant bone tumors., Competing Interests: Author LL was employed by Philips Healthcare. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Li, Lin, Zhang, Ren, Zhang and Cheng.)