Comparison of Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging and Arterial Spin Labeling MR Imaging in Gliomas. Biomed Res Int. 2015;2015:234245. [PMID: 25945328 PMCID: PMC4402183 DOI: 10.1155/2015/234245]

Possibilities of Using Multi-b-value Diffusion Magnetic Resonance Imaging for Classification of Brain Lesions

In contrast to conventional diffusion magnetic resonance imaging (MRI), multi-b-value diffusion MRI methods are able to separate the signal from free water, pseudo-diffusion, and non-Gaussian components of water molecule diffusion. These approaches can then be utilised in so-called intravoxel incoherent motion imaging and diffusion kurtosis imaging. Various parameters provided by these methods can describe additional characteristics of the tissue microstructure and potentially help in the diagnosis and classification of various pathological processes. In this review, we present the basic principles and methods of analysing multi-b-value diffusion imaging data and specifically focus on the known possibilities for its use in the diagnosis of brain lesions. We also suggest possible directions for further research.

Intravoxel Incoherent Motion Quantification Dependent on Measurement SNR and Tissue Perfusion: A Simulation Study

Background

The intravoxel incoherent motion (IVIM) model extracts both functional and structural information of a tissue using motion-sensitizing gradients.

Objective

The Objective of the present work is to investigate the impact of signal to noise ratio (SNR) and physiologic conditions on the validity of IVIM parameters.

Material and Methods

This study is a simulation study, modeling IVIM at a voxel, and also done 10,000 times for every single simulation. Complex noises with various standard deviations were added to signal in-silico to investigate SNR effects on output validity. Besides, some blood perfusion situations for different tissues were considered based on their physiological range to explore the impacts of blood fraction at each voxel on the validity of the IVIM outputs. Coefficient variation (CV) and bias of the estimations were computed to assess the validity of the IVIM parameters.

Results

This study has shown that the validity of IVIM output parameters highly depends on measurement SNR and physiologic characteristics of the studied organ.

Conclusion

IVIM imaging could be useful if imaging parameters are correctly selected for each specific organ, considering hardware limitations.

Efficacy of three-dimensional arterial spin labeling and how it compares against that of contrast enhanced magnetic resonance imaging in preoperative grading of brain gliomas

PURPOSE

To evaluate the efficacy of three-dimensional arterial spin labeling (3D-ASL) imaging in preoperative grading of brain gliomas, and compare the discrepancy between images obtained from 3D-ASL and contrast enhanced magnetic resonance imaging (CE-MRI) in grading of gliomas.

METHODS

Fifty-one patients with brain gliomas received plain MRI, CE-MRI and 3D-ASL scanning before surgery. In 3D-ASL images, the maximum tumor blood flow (TBF) of tumor parenchyma was measured, relative TBF-M and rTBF-WM were calculated. The cases were categorized into "ASL dominant" and "CE dominant" to compare the discrepancy between 3D-ASL and CE-MRI results. Independent samples t test, Mann-Whitney and U test and one-way analysis of variance (ANOVA) were performed to test the differences of TBF, rTBF-M and rTBF-WM values among brain gliomas with different grades. Spearman rank correlation analysis was performed to assess the correlation between TBF, rTBF-M, rTBF-WM and glioma grades respectively. To compare the discrepancy between 3D-ASL and CE-MRI results.

RESULTS

In high-grade gliomas (HGG) group, TBF, rTBF-M and rTBF-WM values were higher than those in low-grade gliomas (LGG) group (p < .05). Multiple comparison showed TBF and rTBF-WM values were different between grade I and IV gliomas, grade II and IV gliomas (both p < .05), the rTBF-M value was different between grade I and IV gliomas (p < .05). The values of all 3D-ASL derived parameters were positively correlated with gliomas grading (all p < .001). TBF showed highest specificity (89.3%) and rTBF-WM showed highest sensitivity (96.4%) when discriminating LGG and HGG using ROC curve. There were 29 CE dominant cases (23 cases were HGG), 9 ASL dominant cases (4 cases were HGG).  CONCLUSION: 3D-ASL is of significance to preoperative grading of brain gliomas and might be more sensitive than CE-MRI in detection of tumor perfusion.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging and 3D-ASL to Assess the Value of Ki-67 Labeling Index and Grade in Glioma

Objective

To determine the proportion of intravoxel incoherent motion diffusion-weighted images (IVIM-DWI) and three-dimensional arterial circulation markers (3D-ASL) in Ki-67 labeling index (Ki-67 LI) and glioma grading.

Methods

According to the classification of diseases of the central nervous system dealt with by WHO in 2007, patients with stage II glioma were classified as low (n = 20) and patients with stages III-IV were divided into higher levels (n = 22). Prior to surgery, brain MRI, IVIM-DWI, and 3D-ASL were performed in all patients, and the actual water molecular diffusion coefficient (D), microcirculation coefficient (D∗), blood flow fraction (f), and cerebral blood flow (CBF) were measured. A rank sum (Mann-Whitney U test) was used to compare the four upper and lower level Ki-67 LI measurements. Spearman's method is used to identify the relationship between 4 groups of quantification and Ki-67 LI. Reciprocal grafting (ROC) curves were used to measure the diagnosis of four groups of glioma grading defects.

Results

There were significant differences in D, D∗, f, and CBF between the solid region of the tumor and the normal white matter contralateral to it (P < 0.05). The significant differences of rD, rD∗, rf, and rCBF were shown between patients with low-grade glioma and high-grade glioma (P < 0.05). Ki-67 LI was found to have negative correlation with rD (r = 00.693, P < 0.001) and rf (r = 00.539, P < 0.001), but similarly correlated with rCBF (r = 0.665, P < 0.001) in patients with glioma. Recipient efficacy for predicting advanced and secondary glioma from rD, rf, rD∗, rCBF, and Ki-67 LI raises AUCs of 0.819, 0.747, 0.719, 0.836, and 0.907, respectively.

Conclusion

IVIM-DWI has good application value for preoperative grading of glioma.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading

Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.

3D pCASL-perfusion in preoperative assessment of brain gliomas in large cohort of patients

The aim of the study was to evaluate the role of pseudocontinuous arterial spin labeling perfusion (pCASL-perfusion) in preoperative assessment of cerebral glioma grades. The study group consisted of 253 patients, aged 7-78 years with supratentorial gliomas (65 low-grade gliomas (LGG), 188 high-grade gliomas (HGG)). We used 3D pCASL-perfusion for each patient in order to calculate the tumor blood flow (TBF). We obtained maximal tumor blood flow (maxTBF) in small regions of interest (30 ± 10 mm²) and then normalized absolute maximum tumor blood flow (nTBF) to that of the contralateral normal-appearing white matter of the centrum semiovale. MaxTBF and nTBF values significantly differed between HGG and LGG groups (p < 0.001), as well as between patient groups separated by the grades (grade II vs. grade III) (p < 0.001). Moreover, we performed ROC-analysis which demonstrated high sensitivity and specificity in differentiating between HGG and LGG. We found significant differences for maxTBF and nTBF between grade III and IV gliomas, however, ROC-analysis showed low sensitivity and specificity. We did not observe a significant difference in TBF for astrocytomas and oligodendrogliomas. Our study demonstrates that 3D pCASL-perfusion as an effective diagnostic tool for preoperative differentiation of glioma grades.

Monoexponential, biexponential and stretched exponential models of diffusion weighted magnetic resonance imaging in glioma in relation to histopathologic grade and Ki-67 labeling index using high B values

PURPOSE

To explore the performance of various parameters obtained from monoexponential (Gaussian), biexponential and stretched exponential (non-Gaussian) models of Diffusion Weighted Magnetic Resonance Imaging in differentiating gliomas with correlation to histopathology and Ki-67 labeling index (LI).

MATERIALS AND METHODS

This Institute Review Board approved retrospective study included 51 pathologically proven glioma patients (WHO Grade I, n = 1; Grade II, n = 19, Grade III, n = 12; Grade IV, n = 19), and immunohistochemistry for Ki-67 LI was obtained. The conventional Magnetic Resonance (MR) images and Diffusion Weighted (DW) images with 19 non-zero b values (0-4500 s/mm²) followed by contrast-enhanced MR images were obtained at 3T preoperatively. All images were processed with Advantage Workstation 4.5 (GE Medical Systems). Region of interest (ROI) in the solid part of the tumor was manually drawn along the border meticulously excluding areas of edema, cyst, hemorrhage, necrosis, and/or calcification, and the parameters: Apparent Diffusion Coefficient (ADC) of monoexponential; pure molecular diffusion coefficient (Dslow), pseudo-diffusion coefficient (Dfast), and perfusion fraction (f) of biexponential; Distributed Diffusion Coefficient (DDC), and heterogeneity index (α) of stretched exponential models were obtained. ROI of 50 mm² in the contralateral normal appearing white matter (NAWM) was drawn for the internal control either on centrum semiovale or white matter of the frontal lobe. Analysis of reliability by Intra-class Correlation Coefficient (ICC); correlation with Ki-67 LI by Spearman's rank correlation; comparison between high grade glioma (HGG) and low grade glioma (LGG) by either Mann Whitney U test or Independent t-Test; comparison among Grade II, III and IV gliomas by one-way ANOVA with Bonferroni; and diagnostic performance by analysis of Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were conducted.

RESULTS

Highly significant differences were found between HGG and LGG for all the parameters (P < 0.001 for all). In differentiating HGG from LGG, AUC values were 0.955 for Ki-67 LI; 0.926 for α; 0.903 for Dslow; 0.897 for f; 0.863 for DDC; 0.852 for ADC; 0.820 for Dfast (P < 0.001 for all). The parameters ADC, Dslow, Dfast, f, DDC, and α showed moderate to good negative correlation with Ki-67 LI (P < 0.001 for all). The ICCs of all the parameters were found greater than 0.75 (P < 0.05 for all) suggesting good reliability of measurements.

CONCLUSION

In comparison to ADC derived from monoexponential model, the parameters α and Dslow derived from stretched exponential, and biexponential models respectively can efficiently differentiate HGG from LGG with high diagnostic accuracy. Additionally, f and DDC derived from biexponential, and stretched exponential models respectively are also more useful in differentiating HGG from LGG in comparison to ADC.

Noncontrast Pediatric Brain Perfusion: Arterial Spin Labeling and Intravoxel Incoherent Motion

Noncontrast magnetic resonance imaging techniques for measuring brain perfusion include arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM). These techniques provide noninvasive and repeatable assessment of cerebral blood flow or cerebral blood volume without the need for intravenous contrast. This article discusses the technical aspects of ASL and IVIM with a focus on normal physiologic variations, technical parameters, and artifacts. Multiple pediatric clinical applications are presented, including tumors, stroke, vasculopathy, vascular malformations, epilepsy, migraine, trauma, and inflammation.

Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas

Objectives

To explore the efficacy of diffusion weighted imaging (DWI)-derived metrics under different models as surrogate indicators for molecular biomarkers and tumor microenvironment in gliomas.

Methods

A retrospective study was performed for 41 patients with gliomas. The standard apparent diffusion coefficient (ADC_st) and ADC under ultra-high b values (ADC_uh) (b values: 2500 to 5000 s/mm²) were calculated based on monoexponential model. The fraction of fast diffusion (f), pseudo ADC (ADC_fast) and true ADC (ADC_slow) were calculated by bi-exponential model (b values: 0 to 2000 s/mm²). The apparent diffusional kurtosis (K_app) was derived from the simplified diffusion kurtosis imaging (DKI) model (b values: 200 to 3000 s/mm²). Potential correlations between DWI parameters and immunohistological indices (i.e. Aquaporin (AQP)1, AQP4, AQP9 and Ki-67) were investigated and DWI parameters were compared between high- and low-grade gliomas, and between tumor center and peritumor. Receiver operator characteristic (ROC) curve and area under the curve (AUC) were calculated to determine the performance of independent or combined DWI parameters in grading gliomas.

Results

The ADC_slow and ADC_uh at tumor center showed a stronger correlation with Ki-67 than other DWI metrics. The ADC_st, ADC_slow and ADC_uh at tumor center presented correlations with AQP1 and AQP4 while AQP9 did not correlate with any DWI metric. K_app showed a correlation with Ki-67 while no significant correlation with AQPs. ADC_st (p < 0.001) and ADC_slow (p = 0.001) were significantly lower while the ADC_uh (p = 0.006) and K_app (p = 0.005) were significantly higher in the high-grade than in the low-grade gliomas. ADC_st, f, ADC_fast, ADC_slow, ADC_uh, K_app at the tumor center had significant differences with those in peritumor when the gliomas grade became high (p < 0.05). Involving ADC_uh and K_app simultaneously into an independent ADC_st model (AUC = 0.833) could further improve the grading performance (ADC_st+ADC_uh+K_app: AUC = 0.923).

Conclusion

Different DWI metrics fitted within different b-value ranges (low to ultra-high b values) have different efficacies as a surrogate indicator for molecular expression or microstructural complexity in gliomas. Further studies are needed to better explain the biological meanings of these DWI parameters in gliomas.

Prediction of Intraoperative Fluorescence of Brain Gliomas: Correlation between Tumor Blood Flow and the Fluorescence

INTRODUCTION

The prediction of the fluorescent effect of 5-aminolevulinic acid (5-ALA) in patients with diffuse gliomas can improve the selection of patients. The degree of enhancement of gliomas has been reported to predict 5-ALA fluorescence, while, at the same time, rarer cases of fluorescence have been described in non-enhancing gliomas. Perfusion studies, in particular arterial spin labeling perfusion, have demonstrated high efficiency in determining the degree of malignancy of brain gliomas and may be better for predicting fluorescence than contrast enhancement. The aim of the study was to investigate the relationship between tumor blood flow, measured by ASL, and intraoperative fluorescent glow of gliomas of different grades.

MATERIALS AND METHODS

Tumoral blood flow was assessed in 75 patients by pCASL (pseudo-continuous arterial spin labeling) within 1 week prior to surgery. In all cases of tumor removal, 5-ALA had been administered preoperatively. Maximum values of tumoral blood flow (TBF max) were measured, and normalized tumor blood flow (nTBF) was calculated.

RESULTS

A total of 76% of patients had significant contrast enhancement, while 24% were non-enhancing. The histopathology revealed 17 WHO grade II gliomas, 12 WHO grade III gliomas and 46 glioblastomas. Overall, there was a relationship between the degree of intraoperative tumor fluorescence and ASL-TBF (R_s = 0.28, p = 0.02 or the TBF; R_s = 0.34, p = 0.003 for nTBF). Non-enhancing gliomas were fluorescent in 9/18 patients, with nTBF in fluorescent gliomas being 54.58 ± 32.34 mL/100 mg/s and in non-fluorescent gliomas being 52.99 ± 53.61 mL/100 g/s (p > 0.05). Enhancing gliomas were fluorescent in 53/57 patients, with nTBF being 170.17 ± 107.65 mL/100 g/s in fluorescent and 165.52 ± 141.71 in non-fluorescent gliomas (p > 0.05).

CONCLUSION

Tumoral blood flow levels measured by non-contrast ASL perfusion method predict the fluorescence by 5-ALA; however, the additional value beyond contrast enhancement is not clear. ASL is, however, useful in cases with contraindication to contrast.

Three-dimensional pulsed continuous arterial spin labeling and intravoxel incoherent motion imaging of nasopharyngeal carcinoma: correlations with Ki-67 proliferation status

BACKGROUND

Recurrence and distant metastasis are still the main problems affecting the long-term prognosis of nasopharyngeal carcinoma (NPC) patients, and may be related to the Ki-67 proliferation status. We therefore explored the potential correlation between Ki-67 proliferation status in NPC with the parameters derived from two imaging techniques: three-dimensional pulsed continuous arterial spin labeling (3D pCASL) and intravoxel incoherent motion (IVIM).

METHODS

Thirty-six patients with pathologically confirmed NPC were included, and the Ki-67 labeling index (LI) was measured by immunohistochemistry. All patients underwent plain and contrast-enhanced magnetic resonance imaging (MRI), IVIM, and 3D pCASL examination. The mean, maximum, and minimum of blood flow (BF), minimum of apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) parameters were all measured, and Spearman's correlation analysis was performed to evaluate the relationships between these parameters and the Ki-67 LI. According to the Ki-67 values, the patients were divided into two groups: high (>50%) and low (≤50%). The rank-sum test (Mann-Whitney U test) was then used to compare the differences in quantitative parameters between the high and low Ki-67 groups.

RESULTS

Ki-67 LI was positively correlated with BFmean and BFmax (r=0.415 and 0.425). D*mean and D*min did have positive correlation with Ki-67, but this was not significant (P=0.082 and 0.072). BFmax was significantly different between the high and low Ki-67 groups (P=0.028).

CONCLUSIONS

3D pCASL and IVIM are noninvasive functional MR perfusion imaging techniques that can evaluate perfusion information and perfusion parameters. Our study suggests that 3D pCASL is more effective than IVIM for assessing the proliferation status of NPC, which is beneficial for evaluating the prognosis of patients. Furthermore, BFmax is the best biomarker for distinguishing high from low Ki-67 levels.

Diagnostic Accuracy of Machine Learning-Based Radiomics in Grading Gliomas: Systematic Review and Meta-Analysis

Purpose

This study aimed to estimate the diagnostic accuracy of machine learning- (ML-) based radiomics in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG) and to identify potential covariates that could affect the diagnostic accuracy of ML-based radiomic analysis in classifying gliomas.

Method

A primary literature search of the PubMed database was conducted to find all related literatures in English between January 1, 2009, and May 1, 2020, with combining synonyms for “machine learning,” “glioma,” and “radiomics.” Five retrospective designed original articles including LGG and HGG subjects were chosen. Pooled sensitivity, specificity, their 95% confidence interval, area under curve (AUC), and hierarchical summary receiver-operating characteristic (HSROC) models were obtained.

Result

The pooled sensitivity when diagnosing HGG was higher (96% (95% CI: 0.93, 0.98)) than the specificity when diagnosing LGG (90% (95% CI 0.85, 0.93)). Heterogeneity was observed in both sensitivity and specificity. Metaregression confirmed the heterogeneity in sample sizes (p=0.05), imaging sequence types (p=0.02), and data sources (p=0.01), but not for the inclusion of the testing set (p=0.19), feature extraction number (p=0.36), and selection of feature number (p=0.18). The results of subgroup analysis indicate that sample sizes of more than 100 and feature selection numbers less than the total sample size positively affected the diagnostic performance in differentiating HGG from LGG.

Conclusion

This study demonstrates the excellent diagnostic performance of ML-based radiomics in differentiating HGG from LGG.

Intravoxel incoherent motion (IVIM) modeling of diffusion MRI during chemoradiation predicts therapeutic response in IDH wildtype glioblastoma

Background:

Prediction of early progression in glioblastoma may provide an opportunity to personalize treatment. Simplified intravoxel incoherent motion (IVIM) MRI offers quantitative estimates of diffusion and perfusion metrics. We investigated whether these metrics, during chemoradiation, could predict treatment outcome.

Methods:

38 patients with newly diagnosed IDH-wildtype glioblastoma undergoing 6-week/30-fraction chemoradiation had standardized post-operative MRIs at baseline (radiation planning), and at the 10th and 20th fractions. Non-overlapping T1-enhancing (T1C) and non-enhancing T2-FLAIR hyperintense regions were independently segmented. Apparent diffusion coefficient (ADC_T1C, ADC_T2-FLAIR) and perfusion fraction (f_T1C, f_T2-FLAIR) maps were generated with simplified IVIM modelling. Parameters associated with progression before or after 6.9 months (early vs late progression, respectively), overall survival (OS) and progression-free survival (PFS) were investigated.

Results:

Higher ADC_T2-FLAIR at baseline [Odds Ratio (OR) = 1.06, 95% CI 1.01–1.15, p = 0.025], lower f_T2-FLAIR at fraction 10 (OR = 2.11, 95% CI 1.04–4.27, p = 0.018), and lack of increase in ADC_T2-FLAIR at fraction 20 compared to baseline (OR = 1.12, 95% CI 1.02–1.22, p = 0.02) were associated with early progression. Combining ADC_T2-FLAIR at baseline, f_T2-FLAIR at fraction 10, ECOG and MGMT promoter methylation status significantly improved AUC to 90.3% compared to a model with only ECOG and MGMT promoter methylation status (p = 0.001). Using multivariable analysis, neither IVIM metrics were associated with OS but higher f_T2-FLAIR at fraction 10 (HR = 0.72, 95% CI 0.56–0.95, p = 0.018) was associated with longer PFS.

Conclusion:

ADC_T2-FLAIR at baseline, its lack of increase from baseline to fraction 20, or f_T2-FLAIR at fraction 10 significantly predicted early progression. f_T2-FLAIR at fraction 10 was associated with PFS.

Intravoxel Incoherent Motion Magnetic Resonance Imaging for Assessing Parotid Gland Tumors: Correlation and Comparison with Arterial Spin Labeling Imaging

Objective

To compare and correlate the findings of intravoxel incoherent motion (IVIM) magnetic resonance (MR) imaging and arterial spin labeling (ASL) imaging in characterizing parotid gland tumors.

Materials and Methods

We retrospectively reviewed 56 patients with parotid gland tumors evaluated by MR imaging. The true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and fraction of perfusion (f) values of IVIM imaging and tumor-to-parotid gland signal intensity ratio (SIR) on ASL imaging were calculated. Spearman rank correlation coefficient, chi-squared, Mann-Whitney U, and Kruskal-Wallis tests with the post-hoc Dunn-Bonferroni method and receiver operating characteristic curve assessments were used for statistical analysis.

Results

Malignant parotid gland tumors showed significantly lower D than benign tumors (p = 0.019). Within subgroup analyses, pleomorphic adenomas (PAs) showed significantly higher D than malignant tumors (MTs) and Warthin's tumors (WTs) (p < 0.001). The D* of WTs was significantly higher than that of PAs (p = 0.031). The f and SIR on ASL imaging of WTs were significantly higher than those of MTs and PAs (p < 0.05). Significantly positive correlation was found between SIR on ASL imaging and f (r = 0.446, p = 0.001). In comparison with f, SIR on ASL imaging showed a higher area under curve (0.853 vs. 0.891) in discriminating MTs from WTs, although the difference was not significant (p = 0.720).

Conclusion

IVIM and ASL imaging could help differentiate parotid gland tumors. SIR on ASL imaging showed a significantly positive correlation with f. ASL imaging might hold potential to improve the ability to discriminate MTs from WTs.

Investigating the value of arterial spin labeling and intravoxel incoherent motion imaging on diagnosing nasopharyngeal carcinoma in T1 stage

BACKGROUND

To investigate the diagnostic value of arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM) imaging in distinguishing nasopharyngeal carcinoma (NPC) in T1 stage from healthy controls (HC).

METHODS

Forty-five newly diagnosed NPC patients in the T1 stage and thirty-one healthy volunteers who underwent MR examinations for both 3D pseudo-continuous ASL (pCASL) and IVIM were enrolled in this study. The Mann-Whitney test was used to compare the mean values of blood flow (BF) derived from pCASL and IVIM derived parameters, including apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f) between NPC tumor and benign nasopharyngeal mucosa of HC. Receiver Operating Characteristic (ROC) was performed to determine diagnostic cutoff and efficiency. The correlation coefficients among parameters were investigated using Spearman's test.

RESULTS

The NPC in the T1 stage showed higher mean BF, lower ADC, D, and f compared to benign nasopharyngeal mucosa (P < 0.001) with the area under curve of ROC of 0.742-0.996 (highest by BF). BF cutoff was set at > 36 mL/100 g/min; the corresponding sensitivity, specificity, and accuracy in differentiating NPC stage T1 from benign nasopharyngeal mucosa were 95.56% (43/45), 100% (31/31) and 97.37% (74/76), respectively. BF demonstrated moderate negative correlation with D* on HC (ρ [Spearman correlation coefficients] = - 0.426, P = 0.017).

CONCLUSIONS

ASL and IVIM could reflect the difference in perfusion and diffusion between tumor and benign nasopharyngeal mucosa, indicating a potential for accessing early diagnosis of NPC. Notably, BF, with a specificity of 100%, demonstrated better performance compared to IVIM in distinguishing malignant lesions from healthy tissue.

Ki-67 labeling index and the grading of cerebral gliomas by using intravoxel incoherent motion diffusion-weighted imaging and three-dimensional arterial spin labeling magnetic resonance imaging

BACKGROUND

Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and three-dimensional arterial spin labeling (3D-ASL) have been applied to brain tumors; however, the relationship between their parameters and the Ki-67 labeling index (Ki-67 LI) for the grading of gliomas have yet to be investigated.

PURPOSE

The aim of this study is to compare multiple parameters obtained from IVIM-DWI and 3D-ASL with the Ki-67 LI when grading gliomas.

MATERIAL AND METHODS

Fifty-two patients with pathologically confirmed gliomas had undergone magnetic resonance imaging (MRI), including IVIM-DWI and 3D-ASL imaging. Mann-Whitney U tests were conducted and receiver operating characteristic (ROC) curves were generated to determine parameters for distinguishing high-grade gliomas (HGGs) from low-grade gliomas (LGGs). These parameters included the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo diffusivity (D*), perfusion fraction (f), cerebral blood flow (CBF), and their relative values (rADC, rD, rD*, rf, and rCBF). Spearman correlation analysis was used to assess the correlations of the parameters of MRI with the Ki-67 LI.

RESULTS

The rADC, rD, and rf were significantly lower in HGGs than in LGGs (P < 0.005 for all). The rD had a significantly greater area under the ROC curve than that of the other parameters in the differentiation of HGGs from LGGs (P < 0.05). Both the rD and rf were moderately negatively correlated with the Ki-67 LI.

CONCLUSION

Both the rD and rf can be used for the quantitative prediction of the Ki-67 LI. Among the extracted parameters, the rD had the significantly greatest diagnostic efficacy.

Correlation and Characteristics of Intravoxel Incoherent Motion and Arterial Spin Labeling Techniques Versus Multiple Parameters Obtained on Dynamic Susceptibility Contrast Perfusion MRI for Brain Tumors

Purpose : To compare data on brain tumors derived from intravoxel incoherent motion (IVIM) and arterial spin labeling (ASL) imaging with multiple parameters obtained on dynamic susceptibility contrast (DSC) perfusion MRI and to clarify the characteristics of IVIM and ASL perfusion data from the viewpoint of cerebral blood flow (CBF) analysis. Methods : ASL-CBF and IVIM techniques as well as DSC examination were performed in 24 patients with brain tumors. The IVIM data were analyzed with the two models. The relative blood flow (rBF), relative blood volume (rBV) corrected relative blood volume (crBV), mean transit time (MTT), and leakage coefficient (K2) were obtained from the DSC MRI data. Results : The ASL-CBF had the same tendency as the perfusion parameters derived from the DSC data, but the permeability from the vessels had less of an effect on the ASL-CBF. The diffusion coefficient of the fast component on IVIM contained more information on permeability than the f value. Conclusion : ASL-CBF is more suitable for the evaluation of perfusion in brain tumors than IVIM parameters. ASL-CBF and IVIM techniques should be carefully selected and the biological significance of each parameter should be understood for the correct comprehension of the pathological status of brain tumors. J. Med. Invest. 66 : 308-313, August, 2019.

Grading of Glioma: combined diagnostic value of amide proton transfer weighted, arterial spin labeling and diffusion weighted magnetic resonance imaging

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.

Can the low and high b-value distribution influence the pseudodiffusion parameter derived from IVIM DWI in normal brain?

Background

Our study aims to reveal whether the low b-values distribution, high b-values upper limit, and the number of excitation (NEX) influence the accuracy of the intravoxel incoherent motion (IVIM) parameter derived from multi-b-value diffusion-weighted imaging (DWI) in the brain.

Methods

This prospective study was approved by the local Ethics Committee and informed consent was obtained from each participant. The five consecutive multi-b DWI with different b-value protocols (0–3500 s/mm²) were performed in 22 male healthy volunteers on a 3.0-T MRI system. The IVIM parameters from normal white matter (WM) and gray matter (GM) including slow diffusion coefficient (D), fast perfusion coefficient (D*) and perfusion fraction (f) were compared for differences among defined groups with different IVIM protocols by one-way ANOVA.

Results

The D* and f value of WM or GM in groups with less low b-values distribution (less than or equal to 5 b-values) were significantly lower than ones in any other group with more low b-values distribution (all P <  0.05), but no significant differences among groups with more low b-values distribution (P > 0.05). In addition, no significant differences in the D, D* and f value of WM or GM were found between group with one and more NEX of low b-values distribution (all P > 0.05). IVIM parameters in normal WM and GM strongly depended on the choice of the high b-value upper limit.

Conclusions

Metrics of IVIM parameters can be affected by low and high b value distribution. Eight low b-values distribution with high b-value upper limit of 800–1000 s/mm² may be the relatively proper set when performing brain IVIM studies.

Detection of Crossed Cerebellar Diaschisis by Intravoxel Incoherent Motion MR Imaging in Subacute Ischemic Stroke

Intravoxel incoherent motion has received extensive attention in brain studies for its potential as a non-invasive magnetic resonance perfusion method. However, studies on intravoxel incoherent motion imaging and crossed cerebellar diaschisis detection are relatively scarce. The aim of our study was to evaluate the feasibility of using intravoxel incoherent motion imaging in crossed cerebellar diaschisis diagnosis in subacute ischemic stroke patients by comparing results from intravoxel incoherent motion imaging, single-photon emission computed tomography, and arterial spin-labeling perfusion methods. In total, 39 patients with subacute ischemic stroke who underwent intravoxel incoherent motion, arterial spin-labeling, and single-photon emission computed tomography scanning were enrolled. Intravoxel incoherent motion-derived perfusion-related parameters including fast diffusion coefficient, vascular volume fraction, arterial spin-labeling-derived cerebral blood flow as well as single-photon emission computed tomography-derived cerebral blood flow of bilateral cerebellum were measured. A crossed cerebellar diaschisis-positive result was considered present with an asymmetry index ≥10% of single-photon emission computed tomography. In the crossed cerebellar diaschisis-positive group, fast diffusion coefficient, arterial spin-labeling-derived cerebral blood flow, and computed tomography-derived cerebral blood flow of the contralateral cerebellum decreased compared with those of the ipsilesional cerebellum; whereas vascular volume fraction significantly increased. The National Institutes of Health Stroke Scale score and infarct volume in the crossed cerebellar diaschisis-positive group were significantly higher than those in the crossed cerebellar diaschisis-negative group. A positive correlation was detected between the fast diffusion coefficient-based asymmetry index and the single-photon emission computed tomography-based asymmetry index, fast diffusion coefficient-based asymmetry, and arterial spin-labeling based asymmetry index; whereas the vascular volume fraction-based asymmetry index value had a negative correlation with the single-photon emission computed tomography-based asymmetry index and arterial spin-labeling based asymmetry index. Furthermore, the area under the receiver operating characteristic curve value of the arterial spin-labeling-based asymmetry index was 0.923. The fast diffusion coefficient derived from the intravoxel incoherent motion could be valuable for the assessment of crossed cerebellar diaschisis in supratentorial stroke patients.

The value of arterial spin labelling in adults glioma grading: systematic review and meta-analysis

This study aimed to evaluate the diagnostic performance of arterial spin labelling (ASL) in grading of adult gliomas. Eighteen studies matched the inclusion criteria and were included after systematic searches through EMBASE and MEDLINE databases. The quality of the included studies was assessed utilizing Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The quantitative values were extracted and a meta-analysis was subsequently based on a random-effect model with forest plot and joint sensitivity and specificity modelling. Hierarchical summary receiver operating characteristic (HROC) curve analysis was also conducted. The absolute tumour blood flow (TBF) values can differentiate high-grade gliomas (HGGs) from low-grade gliomas (LGGs) and grade II from grade IV tumours. However, it lacked the capacity to differentiate grade II from grade III tumours and grade III from grade IV tumours. In contrast, the relative TBF (rTBF) is effective in differentiating HGG from LGG and in glioma grading. The maximum rTBF (rTBFmax) demonstrated the best results in glioma grading. These results were also reflected in the sensitivity/specificity analysis in which the rTBFmax showed the highest discrimination performance in glioma grading. The estimated effect size for the rTBF was approximately similar between HGGs and LGGs, and grade II and grade III tumours, (-1.46 (-2.00, -0.91), p-value < 0.001), (-1.39 (-1.89, -0.89), p-value < 0.001), respectively; while it exhibited smaller effect size between grade III and grade IV (-1.05 (-1.82, -0.27)), p < 0.05). Sensitivity and specificity analysis replicate these results as well. This meta-analysis suggests that ASL is useful for glioma grading, especially when considering the rTBFmax parameter.

Survey of Image Processing Techniques for Brain Pathology Diagnosis: Challenges and Opportunities

In recent years, a number of new products introduced to the global market combine intelligent robotics, artificial intelligence and smart interfaces to provide powerful tools to support professional decision making. However, while brain disease diagnosis from the brain scan images is supported by imaging robotics, the data analysis to form a medical diagnosis is performed solely by highly trained medical professionals. Recent advances in medical imaging techniques, artificial intelligence, machine learning and computer vision present new opportunities to build intelligent decision support tools to aid the diagnostic process, increase the disease detection accuracy, reduce error, automate the monitoring of patient's recovery, and discover new knowledge about the disease cause and its treatment. This article introduces the topic of medical diagnosis of brain diseases from the MRI based images. We describe existing, multi-modal imaging techniques of the brain's soft tissue and describe in detail how are the resulting images are analyzed by a radiologist to form a diagnosis. Several comparisons between the best results of classifying natural scenes and medical image analysis illustrate the challenges of applying existing image processing techniques to the medical image analysis domain. The survey of medical image processing methods also identified several knowledge gaps, the need for automation of image processing analysis, and the identification of the brain structures in the medical images that differentiate healthy tissue from a pathology. This survey is grounded in the cases of brain tumor analysis and the traumatic brain injury diagnoses, as these two case studies illustrate the vastly different approaches needed to define, extract, and synthesize meaningful information from multiple MRI image sets for a diagnosis. Finally, the article summarizes artificial intelligence frameworks that are built as multi-stage, hybrid, hierarchical information processing work-flows and the benefits of applying these models for medical diagnosis to build intelligent physician's aids with knowledge transparency, expert knowledge embedding, and increased analytical quality.

An evidence-based approach to assess the accuracy of intravoxel incoherent motion imaging for the grading of brain tumors

BACKGROUND

Differentiation of high-grade gliomas (HGGs) and low-grade gliomas (LGGs) is an important clinical problem because treatment strategies vary greatly. This study was performed to investigate the potential diagnostic value of incoherent intravoxel motion imaging (IVIM) to distinguish HGG from LGG by meta-analysis.

METHODS

A computerized search of the literature was performed using the free-access PubMed database, Web of Science, and Chinese biomedical database, and relevant articles until September 18, 2018 that used IVIM to distinguish HGG from LGG were included. All analyses were performed using Review Manager 5.3 and Stata. Mean difference (MD) at 95% confidence interval (CI) of the apparent diffusion coefficient (ADC), diffusion coefficient value (D), perfusion fraction value (f), and perfusion coefficient value (D*) were summarized.

RESULTS

Nine studies were used for general data pooling. In the tumor parenchyma (TP) regions, subgroup analysis revealed D* in HGG is higher than in LGG (MD = 1.19, P = .002), and D in HGG is lower than in LGG (MD = -1.06, P = .001). However, no significant difference in f (MD = 0.89, P = .056) was detected between HGG and LGG. In the white matter regions, HGG had higher D* (MD = 0.76, P = .04) compared with LGG, while no marked differences between the D value (P = .07) and f (P = .09) values.

CONCLUSION

The present meta-analysis shows that the ADC, D, and D* values derived from IVIM may be useful in differentiating HGG from LGG. Considering the small sample of this study, we need to be cautious when interpreting the results of this study. Other prospective and large-sample randomized controlled trials were needed to establish the value of IVIM in differentiating HGG from LGG.

Water Diffusion in the Brain of Chronic Hypoperfusion Model Mice: A Study Considering the Effect of Blood Flow

Purpose:

Chronic cerebral hypoperfusion model mice were created by unilateral common carotid artery occlusion (UCCAO) surgery, which does not cause cerebral infarction, but which does cause long-term reduction in cerebral blood flow (CBF) to the occluded side. Cognitive dysfunction in this mouse model has been demonstrated in behavioral experiments, but neuron density change was not found in a previous positron emission tomography (PET) study. As a next step, in this study we investigated the injury of neuronal fibers in chronic cerebral hypoperfusion model mice using diffusion tensor imaging (DTI).

Methods:

In diffusion-weighted imaging (DWI), not only the diffusion of water but also the capillary flow in the voxel, i.e., intravoxel incoherent motion (IVIM), contributes to the signal. Thus, we used DTI to evaluate DWI signal changes in the brains of chronic hypoperfusion model mice at 4 weeks after UCCAO while monitoring the possible influence of CBF change using arterial spin-labeling (ASL) MRI.

Results:

Simple t-tests indicated that there were significant differences in CBF between the control and occluded sides of the brain, but there was no significant difference for the mean diffusivity (MD) or fractional anisotropy (FA). However, as Pearson correlation analysis showed that MD was strongly correlated with CBF, analysis-of-covariance (ANCOVA) was then performed using CBF as a covariate and a significant difference in MD between the contra- and ipsilateral sides was found. Performing a similar procedure for the FA found no significant differences.

Conclusion:

The results suggest the injury of neuronal fibers due to chronic hypoperfusion. It is also suggested that CBF-related signal changes should be considered when DWI-based information is used for pathological diagnosis.

Intravoxel incoherent motion MRI for differentiating sinonasal small round cell malignant tumours (SRCMTs) from Non-SRCMTs: comparison and correlation with dynamic contrast-enhanced MRI

AIM

To investigate the value of intravoxel incoherent motion (IVIM) in the differentiation of sinonasal small round cell malignant tumours (SRCMTs) from non-SRCMTs and to compare and correlate these results with those of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Ninety patients with histologically confirmed sinonasal malignant tumours (53 SRCMTs and 37 non-SRCMTs) who underwent conventional MRI, IVIM, and DCE-MRI before treatment were enrolled. The IVIM and DCE-MRI parameters were measured. Statistical analyses were performed using Student's t-tests, receiver operating characteristic (ROC) curve analyses, and Spearman's correlation coefficients.

RESULTS

A lower pure diffusion coefficient (D) value and a higher pseudo-diffusion coefficient (D*) value were found in the sinonasal SRCMTs than in the non-SRCMTs (p<0.001 and p=0.011, respectively). Moreover, the mean extravascular extracellular space volume ratio (V_e) of the SRCMTs was significantly lower than that of the non-SRCMTs (p=0.020). ROC curve analysis showed that the diagnostic performance of D outperformed those of the other perfusion and diffusion parameters. A cut-off D value of 0.56 ×10^-3 mm²/s yielded a sensitivity of 80.4%, a specificity of 75%, and an accuracy of 78.2%, with an AUC of 0.825. Significant but poor-to-fair correlations were found between the parameters from IVIM and DCE-MRI.

CONCLUSIONS

The D and D* values of IVIM and the V_e value of DCE-MRI are helpful in distinguishing sinonasal SRCMTs from non-SRCMTs, with the D values having the best diagnostic efficiency.

Radiomics strategy for glioma grading using texture features from multiparametric MRI

BACKGROUND

Accurate glioma grading plays an important role in the clinical management of patients and is also the basis of molecular stratification nowadays.

PURPOSE/HYPOTHESIS

To verify the superiority of radiomics features extracted from multiparametric MRI to glioma grading and evaluate the grading potential of different MRI sequences or parametric maps.

STUDY TYPE

Retrospective; radiomics.

POPULATION

A total of 153 patients including 42, 33, and 78 patients with Grades II, III, and IV gliomas, respectively.

FIELD STRENGTH/SEQUENCE

3.0T MRI/T₁ -weighted images before and after contrast-enhanced, T₂ -weighted, multi-b-value diffusion-weighted and 3D arterial spin labeling images.

ASSESSMENT

After multiparametric MRI preprocessing, high-throughput features were derived from patients' volumes of interests (VOIs). The support vector machine-based recursive feature elimination was adopted to find the optimal features for low-grade glioma (LGG) vs. high-grade glioma (HGG), and Grade III vs. IV glioma classification tasks. Then support vector machine (SVM) classifiers were established using the optimal features. The accuracy and area under the curve (AUC) was used to assess the grading efficiency.

STATISTICAL TESTS

Student's t-test or a chi-square test were applied on different clinical characteristics to confirm whether intergroup significant differences exist.

RESULTS

Patients' ages between LGG and HGG groups were significantly different (P < 0.01). For each patient, 420 texture and 90 histogram parameters were derived from 10 VOIs of multiparametric MRI. SVM models were established using 30 and 28 optimal features for classifying LGGs from HGGs and grades III from IV, respectively. The accuracies/AUCs were 96.8%/0.987 for classifying LGGs from HGGs, and 98.1%/0.992 for classifying grades III from IV, which were more promising than using histogram parameters or using the single sequence MRI.

DATA CONCLUSION

Texture features were more effective for noninvasively grading gliomas than histogram parameters. The combined application of multiparametric MRI provided a higher grading efficiency. The proposed radiomic strategy could facilitate clinical decision-making for patients with varied glioma grades.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1518-1528.

A Modified Tri-Exponential Model for Multi-b-value Diffusion-Weighted Imaging: A Method to Detect the Strictly Diffusion-Limited Compartment in Brain

Purpose: To present a new modified tri-exponential model for diffusion-weighted imaging (DWI) to detect the strictly diffusion-limited compartment, and to compare it with the conventional bi- and tri-exponential models.

Methods: Multi-b-value diffusion-weighted imaging (DWI) with 17 b-values up to 8,000 s/mm² were performed on six volunteers. The corrected Akaike information criterions (AICc) and squared predicted errors (SPE) were calculated to compare these three models.

Results: The mean f₀ values were ranging 11.9–18.7% in white matter ROIs and 1.2–2.7% in gray matter ROIs. In all white matter ROIs: the AICcs of the modified tri-exponential model were the lowest (p < 0.05 for five ROIs), indicating the new model has the best fit among these models; the SPEs of the bi-exponential model were the highest (p < 0.05), suggesting the bi-exponential model is unable to predict the signal intensity at ultra-high b-value. The mean ADC_very−slow values were extremely low in white matter (1–7 × 10⁻⁶ mm²/s), but not in gray matter (251–445 × 10⁻⁶ mm²/s), indicating that the conventional tri-exponential model fails to represent a special compartment.

Conclusions: The strictly diffusion-limited compartment may be an important component in white matter. The new model fits better than the other two models, and may provide additional information.

Differentiating the histologic grades of gliomas preoperatively using amide proton transfer-weighted (APTW) and intravoxel incoherent motion MRI

The purpose of this work was to investigate the diagnostic performance of amide proton transfer-weighted (APTW) and intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in the preoperative grading of gliomas. Fifty-one patients with suspected gliomas were recruited and underwent a preoperative MRI examination that included APTW and IVIM sequences. All cases were confirmed by postsurgical histopathology. APTW signal intensity, true diffusion coefficient (D), perfusion fraction (f) and pseudo-diffusion coefficient (D*) were applied to assess the solid tumor component and contralateral normal-appearing white matter. The relative APTW signal intensity (rAPTW) was also used. Independent-sample and paired-sample t-tests were used to compare differences in MRI parameters between low-grade glioma (LGG) and high-grade glioma (HGG) groups. The diagnostic performance was assessed with the receiver operating characteristic curve. Twenty-six patients were pathologically diagnosed with LGG and 25 were diagnosed with HGG. APTW, rAPTW and f values were significantly higher (all p < 0.001), whereas D values were significantly lower (p < 0.001) in the HGG group than in the LGG group. There was no significant difference between D* values for the two groups. rAPTW had an area under the curve (AUC) of 0.957, with a sensitivity of 100% and a specificity of 84.6%, followed by APTW, f, D and D*. The combined use of APTW and IVIM showed the best diagnostic performance, with an AUC of 0.986. In conclusion, APTW and IVIM, as two promising supplementary sequences for routine MRI, could be valuable in differentiating LGGs from HGGs.

[Non-contrast ASL perfusion in preoperative diagnosis of supratentorial gliomas]

The purpose of this study was to investigate the potential of pseudocontinuous arterial spin labeling perfusion (pCASL) in assessing the degree of malignancy of brain gliomas at the preoperative stage. MATERIAL AND METHODS: The study included 126 patients aged 12-75 years with supratentorial gliomas of different malignancy (35 low-grade gliomas and 91 high-grade gliomas). The maximum tumor blood flow (TBF) was measured, and the normalized tumor blood flow (nTBF) was calculated relative to the intact semiovale white matter of the contralateral hemisphere. The TBF and nTBF indicators differed significantly between low-grade and high-grade glioma groups (p<0.001). When using TBF and nTBF in the differential diagnosis of low-grade and high-grade gliomas, the area under the ROC curve was 0.96 in both cases. Our findings suggest that 3D pCASL perfusion is an effective technique for preoperative differential diagnosis of low-grade and high-grade gliomas. The study was supported by the Russian Foundation for Basic Research (grant #18-315-00384).

Rapid measurement of intravoxel incoherent motion (IVIM) derived perfusion fraction for clinical magnetic resonance imaging

OBJECTIVE

This study aimed to investigate the reliability of intravoxel incoherent motion (IVIM) model derived parameters D and f and their dependence on b value distributions with a rapid three b value acquisition protocol.

MATERIALS AND METHODS

Diffusion models for brain, kidney, and liver were assessed for bias, error, and reproducibility for the estimated IVIM parameters using b values 0 and 1000, and a b value between 200 and 900, at signal-to-noise ratios (SNR) 40, 55, and 80. Relative errors were used to estimate optimal b value distributions for each tissue scenario. Sixteen volunteers underwent brain DW-MRI, for which bias and coefficient of variation were determined in the grey matter.

RESULTS

Bias had a large influence in the estimation of D and f for the low-perfused brain model, particularly at lower b values, with the same trends being confirmed by in vivo imaging. Significant differences were demonstrated in vivo for estimation of D (P = 0.029) and f (P < 0.001) with [300,1000] and [500,1000] distributions. The effect of bias was considerably lower for the high-perfused models. The optimal b value distributions were estimated to be brain_500,1000, kidney_300,1000, and liver_200,1000.

CONCLUSION

IVIM parameters can be estimated using a rapid DW-MRI protocol, where the optimal b value distribution depends on tissue characteristics and compromise between bias and variability.

Temporal evolution of perfusion parameters in brain metastases treated with stereotactic radiosurgery: comparison of intravoxel incoherent motion and dynamic contrast enhanced MRI

Intravoxel incoherent motion (IVIM) is a magnetic resonance imaging (MRI) technique that is seeing increasing use in neuro-oncology and offers an alternative to contrast-enhanced perfusion techniques for evaluation of tumor blood volume after stereotactic radiosurgery (SRS). To date, IVIM has not been validated against contrast enhanced techniques for brain metastases after SRS. In the present study, we measure blood volume for 20 brain metastases (15 patients) at baseline, 1 week and 1 month after SRS using IVIM and dynamic contrast enhanced (DCE)-MRI. Correlation between blood volume measurements made with IVIM and DCE-MRI show poor correlation at baseline, 1 week, and 1 month post SRS (r = 0.33, 0.14 and 0.30 respectively). At 1 week after treatment, no significant change in tumor blood volume was found using IVIM or DCE-MRI (p = 0.81 and 0.41 respectively). At 1 month, DCE-MRI showed a significant decrease in blood volume (p = 0.0002). IVIM, on the other hand, demonstrated the opposite effect and showed a significant increase in blood volume at 1 month (p = 0.03). The results of this study indicate that blood volume measured with IVIM and DCE-MRI are not equivalent. While this may relate to differences in the type of perfusion information each technique is providing, it could also reflect a limitation of tumor blood volume measurements made with IVIM after SRS. IVIM measurements of tumor blood volume in the month after SRS should therefore be interpreted with caution.

Diffusion magnetic resonance imaging: A molecular imaging tool caught between hope, hype and the real world of “personalized oncology”

“Personalized oncology” is a multi-disciplinary science, which requires inputs from various streams for optimal patient management. Humongous progress in the treatment modalities available and the increasing need to provide functional information in addition to the morphological data; has led to leaping progress in the field of imaging. Magnetic resonance imaging has undergone tremendous progress with various newer MR techniques providing vital functional information and is becoming the cornerstone of “radiomics/radiogenomics”. Diffusion-weighted imaging is one such technique which capitalizes on the tendency of water protons to diffuse randomly in a given system. This technique has revolutionized oncological imaging, by giving vital qualitative and quantitative information regarding tumor biology which helps in detection, characterization and post treatment surveillance of the lesions and challenging the notion that “one size fits all”. It has been applied at various sites with different clinical experience. We hereby present a brief review of this novel functional imaging tool, with its application in “personalized oncology”.

Non-parametric intravoxel incoherent motion analysis in patients with intracranial lesions: Test-retest reliability and correlation with arterial spin labeling

Intravoxel incoherent motion (IVIM) analysis of diffusion imaging data provides biomarkers of true passive water diffusion and perfusion properties. A new IVIM algorithm with variable adjustment of the b-value threshold separating diffusion and perfusion effects was applied for cerebral tissue characterization in healthy volunteers, computation of test-retest reliability, correlation with arterial spin labeling, and assessment of applicability in a small cohort of patients with malignant intracranial masses. The main results of this study are threefold: (i) accounting for regional differences in the separation of the perfusion and the diffusion components improves the reliability of the model parameters; (ii) if differences in the b-value threshold are not accounted for, a significant tissue-dependent systematic bias of the IVIM parameters occurs; (iii) accounting for voxel-wise differences in the b-value threshold improves the correlation with CBF measurements in healthy volunteers and patients. The proposed algorithm provides a robust characterization of regional micro-vascularization and cellularity without a priori assumptions on tissue diffusion properties. The glioblastoma multiforme with its inherently high variability of tumor vascularization and tumor cell density may benefit from a non-invasive clinical characterization of diffusion and perfusion properties.

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The novel IVIM algorithm accounts for regional differences in the separation of the perfusion and the diffusion components.

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The algorithm improves the reliability of IVIM parameters.

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The algorithm improves the correlation with CBF in healthy volunteers and patients.

Bench to bedside molecular functional imaging in translational cancer medicine: to image or to imagine?

Ongoing research on malignant and normal cell biology has substantially enhanced the understanding of the biology of cancer and carcinogenesis. This has led to the development of methods to image the evolution of cancer, target specific biological molecules, and study the anti-tumour effects of novel therapeutic agents. At the same time, there has been a paradigm shift in the field of oncological imaging from purely structural or functional imaging to combined multimodal structure-function approaches that enable the assessment of malignancy from all aspects (including molecular and functional level) in a single examination. The evolving molecular functional imaging using specific molecular targets (especially with combined positron-emission tomography [PET] computed tomography [CT] using 2- [(18)F]-fluoro-2-deoxy-D-glucose [FDG] and other novel PET tracers) has great potential in translational research, giving specific quantitative information with regard to tumour activity, and has been of pivotal importance in diagnoses and therapy tailoring. Furthermore, molecular functional imaging has taken a key place in the present era of translational cancer research, producing an important tool to study and evolve newer receptor-targeted therapies, gene therapies, and in cancer stem cell research, which could form the basis to translate these agents into clinical practice, popularly termed "theranostics". Targeted molecular imaging needs to be developed in close association with biotechnology, information technology, and basic translational scientists for its best utility. This article reviews the current role of molecular functional imaging as one of the main pillars of translational research.