Correlation between amide proton transfer-related signal intensity and diffusion and perfusion magnetic resonance imaging parameters in high-grade glioma.
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ABSTRACT:
SUBMITTER: Nakajo M
PROVIDER: S-EPMC8159950 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThis study investigates the influence of diffusion-weighted Magnetic Resonance Imaging (DWI-MRI) on radiomic-based prediction of glioma types according to molecular status and assesses the impact of DWI intensity normalization on model generalizability.MethodsRadiomic features, compliant with image biomarker standardization initiative standards, were extracted from preoperative MRI of 549 patients with diffuse glioma, known IDH, and 1p19q-status. Anatomical sequences (T1, T1c, T2, FLAIR) underwent N4-Bias Field Correction (N4) and WhiteStripe normalization (N4/WS). Apparent diffusion coefficient (ADC) maps were normalized using N4 or N4/z-score. Nine machine-learning algorithms were trained for multiclass prediction of glioma types (IDH-mutant 1p/19q codeleted, IDH-mutant 1p/19q non-codeleted, IDH-wild type). Four approaches were compared: Anatomical, anatomical + ADC naive, anatomical + ADC N4, and anatomical + ADC N4/z-score. The University of California San Francisco (UCSF)-glioma dataset (n = 409) was used for external validation.ResultsNaïve-Bayes algorithms yielded overall the best performance on the internal test set. Adding ADC radiomics significantly improved AUC from 0.79 to 0.86 (P = .011) for the IDH-wild-type subgroup, but not for the other 2 glioma subgroups (P > .05). In the external UCSF dataset, the addition of ADC radiomics yielded a significantly higher AUC for the IDH-wild-type subgroup (P ≤ .001): 0.80 (N4/WS anatomical alone), 0.81 (anatomical + ADC naive), 0.81 (anatomical + ADC N4), and 0.88 (anatomical + ADC N4/z-score) as well as for the IDH-mutant 1p/19q non-codeleted subgroup (P < .012 each).ConclusionsADC radiomics can enhance the performance of conventional MRI-based radiomic models, particularly for IDH-wild-type glioma. The benefit of intensity normalization of ADC maps depends on the type and context of the used data.
| S-EPMC11003539 | biostudies-literature
Project description:BACKGROUND:To investigate the ability of amide proton transfer (APT) weighted magnetic resonance imaging (MRI), arterial spin labeling (ASL), diffusion weighted imaging (DWI) and the combination for differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs). METHODS:Twenty-seven patients including nine LGGs and eighteen HGGs underwent conventional, APT, ASL and DWI MRI with a 3.0-T MR scanner. Histogram analyses was performed and quantitative parameters including mean apparent diffusion coefficient (ADC mean), 20th-percentile ADC (ADC 20th), mean APT (APT mean), 90th-percentile APT (APT 90th), relative mean cerebral blood flow (rCBF mean) and relative 90th-percentile CBF (rCBF 90th) were compared between HGGs and LGGs. The diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis of each parameter and their combination. Correlations were analyzed among the MRI parameters and Ki-67. RESULTS:The APT values were significantly higher in the HGGs compared to the LGGs (p?<? 0.005), whereas ADC values were significantly lower in HGGs than LGGs (P?<? 0.0001). The ADC 20th and APT mean had higher discrimination abilities compared with other single parameters, with the area under the ROC curve (AUC) of 0.877 and 0.840. Adding ADC parameter, the discrimination ability of APT and rCBF significantly improved. The ADC was negatively correlated with the APT and rCBF value, respectively, while APT value was positively correlated with rCBF value. Significant correlations between ADC values and Ki-67 were also observed. CONCLUSIONS:APT and DWI are valuable in differentiating HGGs from LGGs. The combination of APT, DWI and ASL imaging could improve the ability for discriminating HGGs from LGGs.
| S-EPMC7227252 | biostudies-literature
Project description:OBJECTIVES:To evaluate the added value of amide proton transfer (APT) imaging to the apparent diffusion coefficient (ADC) from diffusion tensor imaging (DTI) and the relative cerebral blood volume (rCBV) from perfusion magnetic resonance imaging (MRI) for discriminating between high- and low-grade gliomas. METHODS:Forty-six consecutive adult patients with diffuse gliomas who underwent preoperative APT imaging, DTI and perfusion MRI were enrolled. APT signals were compared according to the World Health Organization grade. The diagnostic ability and added value of the APT signal to the ADC and rCBV for discriminating between low- and high-grade gliomas were evaluated using receiver operating characteristic (ROC) analyses and integrated discrimination improvement. RESULTS:The APT signal increased as the glioma grade increased. The discrimination abilities of the APT, ADC and rCBV values were not significantly different. Using both the APT signal and ADC significantly improved discrimination vs. the ADC alone (area under the ROC curve [AUC], 0.888?vs.?0.910; P?=?0.007), whereas using both the APT signal and rCBV did not improve discrimination vs. the rCBV alone (AUC, 0.927?vs.?0.923; P?=?0.222). CONCLUSIONS:APT imaging may be a useful imaging biomarker that adds value to the ADC for discriminating between low- and high-grade gliomas. KEY POINTS:• Higher APT values were correlated with higher glioma grades. • Adding the APT signal to the ADC improved glioma grading. • Adding the APT signal to rCBV did not improve glioma grading. • APT is a useful adjunct to the ADC for glioma grading.
| S-EPMC5746027 | biostudies-literature
Project description:Background1p/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.MethodsThis 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.ResultsThe 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.ConclusionsOur 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.
| S-EPMC11005152 | biostudies-literature
Project description:Gliomas represent a broad spectrum of disease with life-expectancy outcomes ranging from months to decades. As our understanding of the molecular profiles of gliomas expands rapidly, practitioners are now better able to identify patients with favorable versus nonfavorable prognoses. Radiation therapy plays a key role in glioma treatment, improving disease control and oftentimes survival. However, for survivors, either long-term or short-term, radiation-induced cognitive impairments may negatively impact their quality of life. For patients with both favorable and unfavorable prognoses, intensity modulated proton therapy (IMPT) may offer significant, yet unproven benefits. IMPT is the newest and most advanced proton delivery technique, one with substantial benefits compared with historical proton techniques. IMPT allows practitioners to maximize the physical benefits of protons, increasing normal tissue sparing and reducing the potential for adverse effects. For more aggressive tumors, the dose conformality and normal tissue sparing afforded by IMPT may also allow for dose escalation to target volumes. However, in order to truly maximize the clinical potential of IMPT, the field of radiation oncology must not only implement the most advanced technologies, but also understand and capitalize on the unique biologic aspects of proton therapy.
| S-EPMC5463497 | biostudies-literature
Project description:The current study aimed to test whether the ratio of T1-weighted to T2-weighted signal intensity (T1W/T2W ratio: rT1/T2) derived from conventional MRI could act as a surrogate relaxation time predictive of IDH mutation status in histologically lower-grade gliomas. Strong exponential correlations were found between rT1/T2 and each of T1- and T2-relaxation times in eight subjects (rT1/T2 = 1.63exp-0.0005T1-relax + 0.30 and rT1/T2 = 1.27exp-0.0081T2-relax + 0.48; R2 = 0.64 and 0.59, respectively). In a test cohort of 25 patients, mean rT1/T2 (mrT1/T2) was significantly higher in IDHwt tumors than in IDHmt tumors (p < 0.05) and the optimal cut-off of mrT1/T2 for discriminating IDHmt was 0.666-0.677, (AUC = 0.75, p < 0.05), which was validated in an external domestic cohort of 29 patients (AUC = 0.75, p = 0.02). However, this result was not validated in an external international cohort derived from TCIA/TCGA (AUC = 0.63, p = 0.08). The t-Distributed Stochastic Neighbor Embedding analysis revealed a greater diversity in image characteristics within the TCIA/TCGA cohort than in the two domestic cohorts. The failure of external validation in the TCIA/TCGA cohort could be attributed to its wider variety of original imaging characteristics.
| S-EPMC9637175 | biostudies-literature
Project description:Radiation therapy (RT) is a critical part of definitive therapy for pediatric high-grade glioma (pHGG). RT is designed to treat residual tumor defined on conventional MRI (cMRI), though pHGG lesions may be ill-characterized on standard imaging. Spectroscopic MRI (sMRI) measures endogenous metabolite concentrations in the brain, and Choline (Cho)/N-acetylaspartate (NAA) ratio is a highly sensitive biomarker for metabolically active tumor. We provide a preliminary report of our study introducing a novel treatment approach of whole brain sMRI-guided proton therapy for pHGG. An observational cohort (c1 = 10 patients) receives standard of care RT; a therapeutic cohort (c2 = 15 patients) receives sMRI-guided proton RT. All patients undergo cMRI and sMRI, a high-resolution 3D whole-brain echo-planar spectroscopic imaging (EPSI) sequence (interpolated resolution of 12 µL) prior to RT and at several follow-up timepoints integrated into diagnostic scans. Treatment volumes are defined by cMRI for c1 and by cMRI and Cho/NAA ≥ 2x for c2. A longitudinal imaging database is used to quantify changes in lesion and metabolite volumes. Four subjects have been enrolled (c1 = 1/c2 = 3) with sMRI imaging follow-up of 4-18 months. Preliminary data suggest sMRI improves identification of pHGG infiltration based on abnormal metabolic activity, and using proton therapy to target sMRI-defined high-risk regions is safe and feasible.
| S-EPMC10037577 | biostudies-literature
Project description:OBJECTIVE:The purpose of this study was the assessment of volumetric CT-perfusion (CTP) of the lower leg musculature in patients with symptomatic peripheral arterial disease (PAD) of the lower extremities, comparing it with established angiographic and hemodynamic parameters. MATERIALS AND METHODS:Thirty-five consecutive patients with symptomatic PAD of the lower extremities requiring interventional revascularization were assessed prospectively. All patients underwent a CTP scan of the lower leg, and hemodynamic and angiographic assessment. Hemodynamic parameters, specifically ankle-brachial pressure index (ABI), ankle blood pressure (ABP), peak systolic velocity (PSV), and segmental pulse oscillography (SPO) level, were determined. Lesion length and degree of collateralization were assessed by interventional angiography. CTP parameters were calculated with a perfusion software, acting on a no outflow assumption. A sequential two-compartment model was used. Differences in CTP parameters and correlations between CTP, hemodynamic and angiographic parameters were assessed with non-parametric tests. RESULTS:The cohort consisted of 27 subjects with an occlusion, and eight with a high-grade stenosis. The mean blood flow (BF) was 7.71 ± 2.96 ml/100ml*min-1, mean blood volume (BV) 0.71 ± 0.33 ml/100ml, and mean mean transit time (MTT) 7.22 ± 2.66 s. BF and BV were higher in subjects with longer lesions, and BV was higher in subjects with lower ABI. Significant correlations were found between lesion length and BV (r = 0.65) and BF (r = 0.52). Significant inverse correlations were found between BV and ABI and between BV and ABP (r = -0.56, for both correlations). CONCLUSIONS:In our study, we have shown the feasibility of CTP for the assessment of PAD. In the future, this quantitative method might serve as a non-invasive method, possibly complementing the diagnostic workup of patients with peripheral arterial disease.
| S-EPMC6764684 | biostudies-literature
Project description:PurposeTo assess the amide proton transfer-weighted (APTw) MRI features of isocitrate dehydrogenase (IDH)-wildtype and IDH-mutant grade II gliomas and to test the hypothesis that the APTw signal is a surrogate imaging marker for identifying IDH mutation status preoperatively.MethodsTwenty-seven patients with pathologically confirmed low-grade glioma, who were previously scanned at 3T, were retrospectively analyzed. The Mann-Whitney test was used to evaluate relationships between APTw intensities for IDH-mutant and IDH-wildtype groups, and receiver operator characteristic (ROC) analysis was used to assess the diagnostic performance of APTw.ResultsBased on histopathology and molecular analysis, seven cases were diagnosed as IDH-wildtype grade II gliomas and 20 cases as IDH-mutant grade II gliomas. The maximum and minimum APTw values, based on multiple regions of interest, as well as the whole-tumor histogram-based mean and 50th percentile APTw values, were significantly higher in the IDH-wildtype gliomas than in the IDH-mutant groups. This corresponded to the areas under the ROC curves of 0.89, 0.76, 0.75, and 0.75, respectively, for the prediction of the IDH mutation status.ConclusionIDH-wildtype lesions typically were associated with relatively high APTw signal intensities as compared with IDH-mutant lesions. The APTw signal could be a valuable imaging biomarker by which to identify IDH1 mutation status in grade II gliomas. Magn Reson Med 78:1100-1109, 2017. © 2017 International Society for Magnetic Resonance in Medicine.
| S-EPMC5561497 | biostudies-literature
Project description:Conventional diffusion imaging techniques are not sufficiently accurate for evaluating glioma grade and cellular proliferation, which are critical for guiding glioma treatment. Diffusion kurtosis imaging (DKI), an advanced non-Gaussian diffusion imaging technique, has shown potential in grading glioma; however, its applications in this tumor have not been fully elucidated. In this study, DKI and diffusion weighted imaging (DWI) were performed on 74 consecutive patients with histopathologically confirmed glioma. The kurtosis and conventional diffusion metric values of the tumor were semi-automatically obtained. The relationships of these metrics with the glioma grade and Ki-67 expression were evaluated. The diagnostic efficiency of these metrics in grading was further compared. It was demonstrated that compared with the conventional diffusion metrics, the kurtosis metrics were more promising imaging markers in distinguishing high-grade from low-grade gliomas and distinguishing among grade II, III and IV gliomas; the kurtosis metrics also showed great potential in the prediction of Ki-67 expression. To our best knowledge, we are the first to reveal the ability of DKI to assess the cellular proliferation of gliomas, and to employ the semi-automatic method for the accurate measurement of gliomas. These results could have a significant impact on the diagnosis and subsequent therapy of glioma.
| S-EPMC4747234 | biostudies-literature