Associations among q-space MRI, diffusion-weighted MRI and histopathological parameters in meningiomas

Association of apparent diffusion coefficient with Ki-67 proliferation index, progesterone-receptor status and various histopathological parameters, and its utility in predicting the high grade in meningiomas

BACKGROUND

Accurate preoperative determination of the histological grade and cellular proliferative potential of meningioma by non-invasive imaging is of paramount importance.

PURPOSE

To evaluate the utility of apparent diffusion coefficient (ADC) in determining the histological grade of meningioma, and to investigate the correlation of ADC with Ki-67 proliferation index (PI), progesterone receptor (PR) status, and a number of other histopathological parameters.

MATERIAL AND METHODS

Histopathologically confirmed 94 meningioma patients (72 low-grade, 22 high-grade) who had undergone preoperative diffusion-weighted imaging were retrospectively evaluated. ADC values were obtained by manually drawing the regions of interest (ROIs) within the solid components of the tumor. The relationship between ADC and Ki-67 values, PR status, and multiple histopathological parameters were investigated, and the ADC values of high-grade and low-grade meningiomas were compared. Independent sample t-test, Mann-Whitney U test, receiver operating characteristic, Pearson correlation, and multiple logistic regression analysis were used for statistical assessment.

RESULTS

All ADC and rADC values were significantly lower in high-grade meningiomas than in low-grade meningiomas (all P < 0.05). ADC values showed significantly negative correlations with Ki-67 and mitotic index (P < 0.001 for each). Numerous ADC parameters were significantly lower in meningiomas demonstrating hypercellularity and necrosis features (P < 0.05). ADC values did not show a significant correlation with PR score (all P > 0.05).

CONCLUSION

ADC can be utilized as a reliable imaging biomarker for predicting the proliferative potential and histological grade in meningiomas.

ADC values of benign and high grade meningiomas and associations with tumor cellularity and proliferation - A systematic review and meta-analysis

INTRODUCTION

The aim of the present systematic review and meta-analysis was to compare the reported ADC values in different meningiomas and to analyze associations between ADC and cell count and proliferation activity in this tumor entity.

METHOD

MEDLINE library and SCOPUS database were screened for papers investigating ADC values of meningiomas up November 2019. The first primary endpoint of the systematic review was the reported ADC mean value of the meningioma groups. The second primary endpoint was the correlation coefficient between ADC values and proliferation index Ki 67 and cellularity.

RESULTS

For the discrimination analysis between benign and high grade meningioma 17 studies were suitable. There were 766 grade I tumors and 289 high grade meningiomas. The calculated mean ADC value of the benign grade I tumors was 0.93 × 10^-3mm²/s [95%-Confidence interval 0.84;1.03] and the mean value of the high-grade tumors was 0.77 × 10^-3mm²/s [95%-Confidence interval 0.73-0.80]. The pooled correlation coefficient between ADC and the proliferation index Ki 67 was r = -0.36 [95% CI -0.43; -0.28]. The pooled correlation coefficient between ADC and cellularity was r = -0.43 [95% CI -0.61; - 0.26].

CONCLUSION

No validated ADC threshold can be recommended for distinguishing benign from high grade meningiomas. Only a moderate inverse correlation was identified between ADC values and tumor microstructure in meningiomas and, therefore, ADC might not accurately enough to predict proliferation potential and cellularity in this entity.

Atypical meningiomas

Meningiomas are the most common primary CNS tumor in adults, representing a third of brain lesions. Their clinical presentation varies greatly, ranging from asymptomatic incidental tumor to fatal tumor. The majority of meningiomas are benign, and gross total resection can achieve very low recurrence rates, with radiation therapy or radiosurgery reserved for recurrences or residual tumor that grows during serial imaging. At the other end of the spectrum, malignant meningiomas, although comprising just 1% of meningiomas, have been recognized to exhibit aggressive behavior that ultimately proves lethal regardless of the extent of resection or whether adjuvant radiation and chemotherapy are utilized. Over the past 2 decades, there has been pathologic recognition of a third type of meningioma known as "atypical," with borderline histologic and clinical features between benign and malignant meningioma. Here we review the clinical features, treatment, and outcomes of atypical meningiomas, with a focus on the impact of extent of resection and radiation therapy on the long-term recurrence rate of completely and incompletely resected atypical meningiomas.

q-Space Imaging Yields a Higher Effect Gradient to Assess Cellularity than Conventional Diffusion-weighted Imaging Methods at 3.0 T: A Pilot Study with Freshly Excised Whole-Breast Tumors

Purpose

To determine whether q-space imaging (QSI), an advanced diffusion-weighted MRI method, provides a higher effect gradient to assess tumor cellularity than existing diffusion imaging methods, and fidelity to cellularity obtained from histologic analysis.

Materials and Methods

In this prospective study, diffusion-weighted images were acquired from 20 whole-breast tumors freshly excised from participants (age range, 35-78 years) by using a clinical 3.0-T MRI unit. Median and skewness values were extracted from the histogram distributions obtained from QSI, monoexponential model, diffusion kurtosis imaging (DKI), and stretched exponential model (SEM). The skewness from QSI and other diffusion models was compared by using paired t tests and relative effect gradient obtained from correlating skewness values.

Results

The skewness obtained from QSI (mean, 1.34 ± 0.77 [standard deviation]) was significantly higher than the skewness from monoexponential fitting approach (mean, 1.09 ± 0.67; P = .015), SEM (mean, 1.07 ± 0.70; P = .014), and DKI (mean, 0.97 ± 0.63; P = .004). QSI yielded a higher effect gradient in skewness (percentage increase) compared with monoexponential fitting approach (0.26 of 0.74; 35.1%), SEM (0.26 of 0.74; 35.1%), and DKI (0.37 of 0.63; 58.7%). The skewness and median from QSI were significantly correlated with the skewness (ρ = -0.468; P = .038) and median (ρ = -0.513; P = .021) of cellularity from histologic analysis.

Conclusion

QSI yields a higher effect gradient in assessing breast tumor cellularity than existing diffusion methods, and fidelity to underlying histologic structure.Keywords: Breast, MR-Diffusion Weighted Imaging, MR-Imaging, Pathology, Tissue Characterization, Tumor ResponseOnline supplemental material is available for this article.Published under a CC BY 4.0 license.

Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 1: ADCmean

Diffusion weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion in tissues. This diffusion can be quantified by apparent diffusion coefficient (ADC). Some reports indicated that ADC can reflect tumor proliferation potential. The purpose of this meta-analysis was to provide evident data regarding associations between ADC and KI 67 in different tumors. Studies investigating the relationship between ADC and KI 67 in different tumors were identified. MEDLINE library was screened for associations between ADC and KI 67 in different tumors up to April 2017. Overall, 42 studies with 2026 patients were identified. The following data were extracted from the literature: authors, year of publication, number of patients, tumor type, and correlation coefficients. Associations between ADC and KI 67 were analyzed by Spearman's correlation coefficient. The reported Pearson correlation coefficients in some studies were converted into Spearman correlation coefficients. The pooled correlation coefficient between ADC_mean and KI 67 for all included tumors was ρ = -0.44. Furthermore, correlation coefficient for every tumor entity was calculated. The calculated correlation coefficients were as follows: ovarian cancer: ρ = -0.62, urothelial carcinomas: ρ = -0.56, cerebral lymphoma: ρ = -0.55, neuroendocrine tumors: ρ = -0.52, glioma: ρ = -0.51, lung cancer: ρ = -0.50, prostatic cancer: ρ = -0.43, rectal cancer: ρ = -0.42, pituitary adenoma:ρ = -0.44, meningioma, ρ = -0.43, hepatocellular carcinoma: ρ = -0.37, breast cancer: ρ = -0.22.

Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis

The purpose of this meta-analysis was to provide clinical evidence regarding relationship between ADC and cellularity in different tumors based on large patient data.

Medline library was screened for associations between ADC and cell count in different tumors up to September 2016. Only publications in English were extracted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA) was used for the research.

Overall, 39 publications with 1530 patients were included into the analysis. The following data were extracted from the literature: authors, year of publication, number of patients, tumor type, and correlation coefficients.

The pooled correlation coefficient for all studies was ρ = -0.56 (95 % CI = [−0.62; −0.50]),. Correlation coefficients ranged from ρ =−0.25 (95 % CI = [−0.63; 0.12]) in lymphoma to ρ=−0.66 (95 % CI = [−0.85; −0.47]) in glioma. Other coefficients were as follows: ovarian cancer, ρ = −0.64 (95% CI = [−0.76; −0.52]); lung cancer, ρ = −0.63 (95 % CI = [−0.78; −0.48]); uterine cervical cancer, ρ = −0.57 (95 % CI = [−0.80; −0.34]); prostatic cancer, ρ = −0.56 (95 % CI = [−0.69; −0.42]); renal cell carcinoma, ρ = −0.53 (95 % CI = [−0.93; −0.13]); head and neck squamous cell carcinoma, ρ = −0.53 (95 % CI = [-0.74; −0.32]); breast cancer, ρ = −0.48 (95 % CI = [−0.74; −0.23]); and meningioma, ρ = -0.45 (95 % CI = [−0.73; −0.17]).

Microvascularization of Grade I meningiomas: effect on tumor volume, blood loss, and patient outcome

OBJECTIVE Quantitative assessment of tumor microvascularity has the potential to improve prognostication, advance understanding of tumor biology, and help narrow potential molecular therapies. While the role of tumor microvascularity has been widely studied in meningiomas, this study examines both the role of automated measurements and the impact on surgical outcome. METHODS Two hundred seven patients with Grade I meningiomas underwent surgery between 1996 and 2011. Tissue samples from each patient were retrospectively evaluated for histopathological measures of microvascularity, including staining for von Willebrand factor (vWF), CD31, CD105, hypoxia-inducible factor 1 (HIF-1), vascular endothelial growth factor, glucose transporter 1, and carbonic anhydrase IX. Manual methods of assessing microvascularity were supplemented by a computational analysis of the microvascular patterns by means of fractal analysis. MIB-1 proliferation staining was also performed on the same tumors. These measures were compared with various patient characteristics, tumor volume, estimated blood loss (EBL) during surgery, progression-free survival (PFS), and overall survival (OS). RESULTS The mean patient age was 55.4 ± 14.8 years, and 63 (30.4%) patients were male. Patients harboring tumors ≥ 3 cm were significantly older (56.9 ± 15.2 years vs 53.1 ± 13.6 years; p = 0.07), more frequently male (40.8% vs 14.6%; p = 0.0001), and had greater EBL (446.5 ± 532.2 ml vs 185.4 ± 197.2 ml; p = 0.0001), greater tumor volume (33.9 ± 38.1 ml vs 29.4 ± 23.5 ml; p = 0.0001), higher MIB-1 index values (3.0% ± 5.4% vs 1.7% ± 1.7%; p = 0.03), higher vWF levels (85.6% ± 76.9% vs 54.1% ± 52.4%; p = 0.001), lower HIF-1 expression (1.4 ± 1.3 vs 2.2 ± 1.4; p = 0.004), and worse OS (199.9 ± 7.6 months vs 180.8 ± 8.1 months; p = 0.05) than patients with tumors < 3 cm. In the multivariate logistic regression, MIB-1 (OR 1.14; p = 0.05), vWF (OR 1.01; p = 0.01), and HIF-1 (OR 1.54; p = 0.0001) significantly predicted tumor size. Although multiple factors were predictive of EBL in the univariate linear regression, only vWF remained significant in the multivariate analysis (β = 0.39; p = 0.004). Lastly, MIB-1 was useful via Kaplan-Meier survival analysis for predicting patients with disease progression, whereby an MIB-1 cutoff value of ≥ 3% conferred a 36% sensitivity and 82.5% specificity in predicting disease progression; an MIB-1 value ≥ 3% showed significantly shorter mean PFS (140.1 ± 11.7 months vs 179.5 ± 7.0 months; log-rank test, p = 0.05). The Cox proportional hazards model showed a trend for MIB-1 in predicting disease progression in a hazards model (OR 1.08; 95% CI 0.99-1.19; p = 0.08). CONCLUSIONS These results support the importance of various microvascularity measures in predicting preoperative (e.g., tumor size), intraoperative (e.g., EBL), and postoperative (e.g., PFS and OS) outcomes in patients with Grade I meningiomas. An MIB-1 cutoff value of 3% showed good specificity for predicting tumor progression. The predictive ability of various measures to detect aberrant tumor microvasculature differed, possibly reflecting the heterogeneous underlying biology of meningiomas. It may be necessary to combine assays to understand angiogenesis in meningiomas.

Diffusion MRI of the spinal cord: from structural studies to pathology

Diffusion MRI is extensively used to study brain microarchitecture and pathologies, and water diffusion appears highly anisotropic in the white matter (WM) of the spinal cord (SC). Despite these facts, the use of diffusion MRI to study the SC, which has increased in recent years, is much less common than that in the brain. In the present review, after a brief outline of early studies of diffusion MRI (DWI) and diffusion tensor MRI (DTI) of the SC, we provide a short survey on DTI and on diffusion MRI methods beyond the tensor that have been used to study SC microstructure and pathologies. After introducing the porous view of WM and describing the q-space approach and q-space diffusion MRI (QSI), we describe other methodologies that can be applied to study the SC. Selected applications of the use of DTI, QSI, and other more advanced diffusion MRI methods to study SC microstructure and pathologies are presented, with some emphasis on the use of less conventional diffusion methodologies. Because of length constraints, we concentrate on structural studies and on a few selected pathologies. Examples of the use of diffusion MRI to study dysmyelination, demyelination as in experimental autoimmune encephalomyelitis and multiple sclerosis, amyotrophic lateral sclerosis, and traumatic SC injury are presented. We conclude with a brief summary and a discussion of challenges and future directions for diffusion MRI of the SC. Copyright © 2016 John Wiley & Sons, Ltd.

Diffusion-Weighted Imaging in Meningioma: Prediction of Tumor Grade and Association with Histopathological Parameters

OBJECTIVES

To analyze diffusion-weighted imaging (DWI) findings of meningiomas and to compare them with tumor grade, cell count, and proliferation index and to test a possibility of use of apparent diffusion coefficient (ADC) to differentiate benign from atypical/malignant tumors.

METHODS

Forty-nine meningiomas were analyzed. DWI was done using a multislice single-shot echo-planar imaging sequence. A polygonal region of interest was drawn on ADC maps around the margin of the lesion. In all lesions, minimal ADC values (ADCmin) and mean ADC values (ADCmean) were estimated. Normalized ADC (NADC) was calculated in every case as a ratio ADCmean meningioma/ADCmean white matter. All meningiomas were surgically resected and analyzed histopathologically. The tumor proliferation index was estimated on Ki-67 antigen-stained specimens. Cell density was calculated. Collected data were evaluated by means of descriptive statistics. Analyses of ADC/NADC values were performed by means of two-sided t tests.

RESULTS

The mean ADCmean value was higher in grade I meningiomas in comparison to grade II/III tumors (0.96 vs 0.80 × 10(-3) mm(2)s(-1), P = .006). Grade II/III meningiomas showed lower NADC values in comparison to grade I tumors (1.05 vs 1.26, P = .015). There was no significant difference in ADCmin values between grade I and II/III tumors (0.69 vs 0.63 × 10(-3) mm(2)s(-1), P = .539). The estimated cell count varied from 486 to 2091 (mean value, 1158.20 ± 333.74; median value, 1108). There were no significant differences in cell count between grade I and grade II/III tumors (1163.93 vs 1123.86 cells, P = .77). The mean level of the proliferation index was 4.78 ± 5.08%, the range was 1% to 18%, and the median value was 2%. The proliferation index was statistically significant higher in grade II/III meningiomas in comparison to grade I tumors (15.43% vs 3.00%, P = .001). Ki-67 was negatively associated with ADCmean (r = -0.61, P < .001) and NADC (r = -0.60, P < .001). No significant correlations between cell count and ADCmean (r = -0.20, P = .164) or NADC (r = -0.25, P = .079) were found. ADCmin correlated statistically significant with cell count (r = -0.44, P = .002) but not with Ki-67 (r = -0.22, P = .129). Furthermore, the association between ADCmin and cell count was stronger in grade II/III tumors (r = -0.79, P = .036) versus grade I meningiomas (r = -0.41, P = .008). An ADCmean value of less than 0.85 × 10(-3) mm(2)s(-1) was determined as the threshold in differentiating between grade I and grade II/III meningiomas (sensitivity 72.9%, specificity 73.1%, accuracy 73.0%). The positive and negative predictive values were 33.3% and 96.8%, respectively. The same threshold ADCmean value was used in differentiating between tumors with Ki-67 level ≥5% and meningiomas with low proliferation index (Ki-67 <5%). This threshold yielded a sensitivity of 70.6%, a specificity of 81.2%, and an accuracy of 77.6%. The positive and negative predictive values were 66.6% and 83.9%, respectively.

CONCLUSIONS

Grade II/III tumors had lower ADCmean values than grade I meningiomas. ADCmean correlated negatively with tumor proliferation index and ADCmin with tumor cell count. These associations were different in several meningiomas. ADCmean can be used for distinguishing between benign and atypical/malignant tumors.

Prospective estimation of mean axon diameter and extra-axonal space of the posterior limb of the internal capsule in patients with idiopathic normal pressure hydrocephalus before and after a lumboperitoneal shunt by using q-space diffusion MRI

Objectives

To prospectively estimate the mean axon diameter (MAD) and extracellular space of the posterior limb of the internal capsule (PLIC) in patients with idiopathic normal pressure hydrocephalus (iNPH) before and after a lumboperitoneal (LP) shunting operation using q-space diffusion MRI analysis.

Methods

We studied 12 consecutive patients with iNPH and 12 controls at our institution. After conventional magnetic resonance imaging (MRI), q-space image (QSI) data were acquired with a 3-T MRI scanner. The MAD and extra-axonal space of the PLIC before and after LP shunting were calculated using two-component q-space imaging analyses; the before and after values were compared.

Results

After LP shunt surgery, the extracellular space of the PLIC was significantly higher than that of the same patients before the operation (one-way analysis of variance (ANOVA) with Scheffé’s post-hoc test, P = 0.024). No significant differences were observed in the PLIC axon diameters among normal controls or in patients before and after surgery.

Conclusion

Increases in the root mean square displacement in the extra-axonal space of the PLIC in patients with iNPH after an LP shunt procedure are associated with the microstructural changes of white matter and subsequent abatement of patient symptoms.

Key Points

• Q-space diffusion MRI provides information on microstructural changes in the corticospinal tract

• Lumboperitoneal (LP) shunting operation is useful for idiopathic normal pressure hydrocephalus

• Q-space measurement may be a biomarker for the effect of the LP shunt procedure

Primary intracranial mucosa-associated lymphoid tissue lymphoma. A report of two cases and literature review

Low-grade B cell non-Hodgkin lymphomas typically arise from the marginal zone of the secondary lymphatic follicles. Their intracranial expression is very rare, most frequently affecting the dura mater and the choroid plexus glomi in the lateral ventricles. Their initial evaluation requires the exclusion of more common extra-axial lesions, such as meningiomas, dural metastasis, granulomatous lesions or secondary lymphoproliferative dural extension from body lymphomas. Whenever a ventricular lesion is present, the patient's age and lesion location help narrow the differential diagnosis. Dural-based lymphomas and ventricular/choroid plexus lymphomas are slow-growing lesions with imaging features similar to meningiomas, which is typically their main differential consideration. Diffusion-weighted images frequently show restricted diffusion behaviour on lymphomas, helping to differentiate them from the typical meningiomas.