True progression versus pseudoprogression in the treatment of glioblastomas: a comparison study of normalized cerebral blood volume and apparent diffusion coefficient by histogram analysis

Repeatability of derived parameters from histograms following non-Gaussian diffusion modelling of diffusion-weighted imaging in a paediatric oncological cohort

OBJECTIVES

To examine repeatability of parameters derived from non-Gaussian diffusion models in data acquired in children with solid tumours.

METHODS

Paediatric patients (<16 years, n = 17) were scanned twice, 24 h apart, using DWI (6 b-values, 0-1000 mm-2 s) at 1.5 T in a prospective study. Tumour ROIs were drawn (3 slices) and all data fitted using IVIM, stretched exponential, and kurtosis models; percentage coefficients of variation (CV) calculated for each parameter at all ROI histogram centiles, including the medians.

RESULTS

The values for ADC, D, DDCα, α, and DDCK gave CV < 10 % down to the 5th centile, with sharp CV increases below 5th and above 95th centile. K, f, and D* showed increased CV (>30 %) over the histogram. ADC, D, DDCα, and DDCK were strongly correlated (ρ > 0.9), DDCα and α were not correlated (ρ = 0.083).

CONCLUSION

Perfusion- and kurtosis-related parameters displayed larger, more variable CV across the histogram, indicating observed clinical changes outside of D/DDC in these models should be interpreted with caution. Centiles below 5th for all parameters show high CV and are unreliable as diffusion metrics. The stretched exponential model behaved well for both DDCα and α, making it a strong candidate for modelling multiple-b-value diffusion imaging data.

KEY POINTS

• ADC has good repeatability as low 5th centile of the histogram distribution. • High CV was observed for all parameters at extremes of histogram. • Parameters from the stretched exponential model showed low coefficients of variation. • The median ADC, D, DDC α , and DDC K are highly correlated and repeatable. • Perfusion/kurtosis parameters showed high CV variations across their histogram distributions.

Extended T2-IVIM model for correction of TE dependence of pseudo-diffusion volume fraction in clinical diffusion-weighted magnetic resonance imaging

The bi-exponential intravoxel-incoherent-motion (IVIM) model for diffusion-weighted MRI (DWI) fails to account for differential T 2 s in the model compartments, resulting in overestimation of pseudodiffusion fraction f. An extended model, T2-IVIM, allows removal of the confounding echo-time (TE) dependence of f, and provides direct compartment T 2 estimates. Two consented healthy volunteer cohorts (n  =  5, 6) underwent DWI comprising multiple TE/b-value combinations (Protocol 1: TE  =  62-102 ms, b  =  0-250 mm-2s, 30 combinations. Protocol 2: 8 b-values 0-800 mm-2s at TE  =  62 ms, with 3 additional b-values 0-50 mm-2s at TE  =  80, 100 ms; scanned twice). Data from liver ROIs were fitted with IVIM at individual TEs, and with the T2-IVIM model using all data. Repeat-measures coefficients of variation were assessed for Protocol 2. Conventional IVIM modelling at individual TEs (Protocol 1) demonstrated apparent f increasing with longer TE: 22.4  ±  7% (TE  =  62 ms) to 30.7  ±  11% (TE  =  102 ms); T2-IVIM model fitting accounted for all data variation. Fitting of Protocol 2 data using T2-IVIM yielded reduced f estimates (IVIM: 27.9  ±  6%, T2-IVIM: 18.3  ±  7%), as well as T 2  =  42.1  ±  7 ms, 77.6  ±  30 ms for true and pseudodiffusion compartments, respectively. A reduced Protocol 2 dataset yielded comparable results in a clinical time frame (11 min). The confounding dependence of IVIM f on TE can be accounted for using additional b/TE images and the extended T2-IVIM model.

Evaluation of pseudoprogression in patients with glioblastoma

Background

Management of glioblastoma is complicated by pseudoprogression, a radiological phenomenon mimicking progression. This retrospective cohort study investigated the incidence, prognostic implications, and most clinically appropriate definition of pseudoprogression.

Methods

Consecutive glioblastoma patients treated at the Juravinski Hospital and Cancer Centre, Hamilton, Ontario between 2004 and 2012 with temozolomide chemoradiotherapy and with contrast-enhanced MRI at standard imaging intervals were included. At each imaging interval, patient responses as per the RECIST (Response Evaluation Criteria in Solid Tumors), MacDonald, and RANO (Response Assessment in Neuro-Oncology) criteria were reported. Based on each set of criteria, subjects were classified as having disease response, stable disease, pseudoprogression, or true progression. The primary outcome was overall survival.

Results

The incidence of pseudoprogression among 130 glioblastoma patients treated with chemoradiotherapy was 15%, 19%, and 23% as defined by RANO, MacDonald, and RECIST criteria, respectively. Using the RANO definition, median survival for patients with pseudoprogression was 13.0 months compared with 12.5 months for patients with stable disease (hazard ratio [HR]=0.70; 95% confidence interval [CI], 0.35-1.42). Similarly, using the MacDonald definition, median survival for the pseudoprogression group was 11.8 months compared with 12.0 months for the stable disease group (HR=0.86; 95% CI, 0.47-1.58). Furthermore, disease response compared with stable disease was also similar using the RANO (HR=0.52; 95% CI, 0.20-1.35) and MacDonald (HR=0.51: 95% CI, 0.20-1.31) definitions.

Conclusions

Of all conventional glioblastoma response criteria, the RANO criteria gave the lowest incidence of pseudoprogression. Regardless of criteria, patients with pseudoprogression did not have statistically significant difference in survival compared with patients with stable disease.

Does the Reporting Quality of Diagnostic Test Accuracy Studies, as Defined by STARD 2015, Affect Citation?

Objective

To determine the rate with which diagnostic test accuracy studies that are published in a general radiology journal adhere to the Standards for Reporting of Diagnostic Accuracy Studies (STARD) 2015, and to explore the relationship between adherence rate and citation rate while avoiding confounding by journal factors.

Materials and Methods

All eligible diagnostic test accuracy studies that were published in the Korean Journal of Radiology in 2011–2015 were identified. Five reviewers assessed each article for yes/no compliance with 27 of the 30 STARD 2015 checklist items (items 28, 29, and 30 were excluded). The total STARD score (number of fulfilled STARD items) was calculated. The score of the 15 STARD items that related directly to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 was also calculated. The number of times each article was cited (as indicated by the Web of Science) after publication until March 2016 and the article exposure time (time in months between publication and March 2016) were extracted.

Results

Sixty-three articles were analyzed. The mean (range) total and QUADAS-2-related STARD scores were 20.0 (14.5–25) and 11.4 (7–15), respectively. The mean citation number was 4 (0–21). Citation number did not associate significantly with either STARD score after accounting for exposure time (total score: correlation coefficient = 0.154, p = 0.232; QUADAS-2-related score: correlation coefficient = 0.143, p = 0.266).

Conclusion

The degree of adherence to STARD 2015 was moderate for this journal, indicating that there is room for improvement. When adjusted for exposure time, the degree of adherence did not affect the citation rate.

MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: a systematic review and meta-analysis

BACKGROUND

Distinction between tumor and treatment related changes is crucial for clinical management of patients with high-grade gliomas. Our purpose was to evaluate whether dynamic susceptibility contrast-enhanced (DSC) and dynamic contrast enhanced (DCE) perfusion-weighted imaging (PWI) metrics can effectively differentiate between recurrent tumor and posttreatment changes within the enhancing signal abnormality on conventional MRI.

METHODS

A comprehensive literature search was performed for studies evaluating PWI-based differentiation of recurrent tumor and posttreatment changes in patients with high-grade gliomas (World Health Organization grades III and IV). Only studies published in the "temozolomide era" beginning in 2005 were included. Summary estimates of diagnostic accuracy were obtained by using a random-effects model.

RESULTS

Of 1581 abstracts screened, 28 articles were included. The pooled sensitivities and specificities of each study's best performing parameter were 90% and 88% (95% CI: 0.85-0.94; 0.83-0.92) and 89% and 85% (95% CI: 0.78-0.96; 0.77-0.91) for DSC and DCE, respectively. The pooled sensitivities and specificities for detecting tumor recurrence using the 2 most commonly evaluated parameters, mean relative cerebral blood volume (rCBV) (threshold range, 0.9-2.15) and maximum rCBV (threshold range, 1.49-3.1), were 88% and 88% (95% CI: 0.81-0.94; 0.78-0.95) and 93% and 76% (95% CI: 0.86-0.98; 0.66-0.85), respectively.

CONCLUSIONS

PWI-derived thresholds separating viable tumor from treatment changes demonstrate relatively good accuracy in individual studies. However, because of significant variability in optimal reported thresholds and other limitations in the existing body of literature, further investigation and standardization is needed before implementing any particular quantitative PWI strategy across institutions.

DEMARCATE: Density-based magnetic resonance image clustering for assessing tumor heterogeneity in cancer

Tumor heterogeneity is a crucial area of cancer research wherein inter- and intra-tumor differences are investigated to assess and monitor disease development and progression, especially in cancer. The proliferation of imaging and linked genomic data has enabled us to evaluate tumor heterogeneity on multiple levels. In this work, we examine magnetic resonance imaging (MRI) in patients with brain cancer to assess image-based tumor heterogeneity. Standard approaches to this problem use scalar summary measures (e.g., intensity-based histogram statistics) that do not adequately capture the complete and finer scale information in the voxel-level data. In this paper, we introduce a novel technique, DEMARCATE (DEnsity-based MAgnetic Resonance image Clustering for Assessing Tumor hEterogeneity) to explore the entire tumor heterogeneity density profiles (THDPs) obtained from the full tumor voxel space. THDPs are smoothed representations of the probability density function of the tumor images. We develop tools for analyzing such objects under the Fisher-Rao Riemannian framework that allows us to construct metrics for THDP comparisons across patients, which can be used in conjunction with standard clustering approaches. Our analyses of The Cancer Genome Atlas (TCGA) based Glioblastoma dataset reveal two significant clusters of patients with marked differences in tumor morphology, genomic characteristics and prognostic clinical outcomes. In addition, we see enrichment of image-based clusters with known molecular subtypes of glioblastoma multiforme, which further validates our representation of tumor heterogeneity and subsequent clustering techniques.

Imaging of the Posttherapeutic Brain

This review covers important topics relating to the imaging evaluation of glioblastoma multiforme after therapy. An overview of the Macdonald and Response Assessment in Neuro-Oncology criteria as well as important questions and limitations regarding their use are provided. Pseudoprogression and pseudoresponse as well as the use of advanced magnetic resonance imaging techniques such as perfusion, diffusion, and spectroscopy in the evaluation of the posttherapeutic brain are also reviewed.

Small increases in enhancement on MRI may predict survival post radiotherapy in patients with glioblastoma

To assess impact of volumetric changes in tumour volume post chemoradiotherapy in glioblastoma. Patients managed with chemoradiotherapy between 2008 and 2011 were included. Patients with incomplete MRI sets were excluded. Analyses were performed on post-operative MRI, and MRIs at 1 month (M+1), 3 months (M+3), 5 months (M+5), 7 months (M+7), and 12 months (M+12) post completion of RT. RANO definitions of response were used for all techniques. Modified RANO criteria and two volumetric analysis techniques were used. The two volumetric analysis techniques involved utility of the Eclipse treatment planning software to calculate the volume of delineated tissue: surgical cavity plus all surrounding enhancement (Volumetric) versus surrounding enhancement only (Rim). Retrospective analysis of 49 patients with median survival of 18.4 months. Using Volumetric analysis the difference in MS for patients who had a <5 % increase versus ≥5 % at M+3 was 23.1 versus 15.1 months (p = 0.006), and M+5 was 26.3 versus 15.1 months (p = 0.006). For patients who were classified as progressive disease using modified RANO criteria at M+1 and M+3 there was a difference in MS compared with those who were not (M+1: 13.1 vs. 19.4 months, p = 0.017, M+3: 13.2 vs. 20.1 months, p = 0.096). An increase in the volume of cavity and enhancement of ≥5 % at M+3 and M+5 post RT was associated with reduced survival, suggesting that increases in radiological abnormality of <25 % may predict survival.

Identification of a candidate biomarker from perfusion MRI to anticipate glioblastoma progression after chemoradiation

OBJECTIVE

To identify relevant relative cerebral blood volume biomarkers from T2* dynamic-susceptibility contrast magnetic resonance imaging to anticipate glioblastoma progression after chemoradiation.

METHODS

Twenty-five patients from a prospective study with glioblastoma, primarily treated by chemoradiation, were included. According to the last follow-up MRI confirmed status, patients were divided into: relapse group (n = 13) and control group (n = 12). The time of last MR acquisition was t_end; MR acquisitions performed at t_end-2M, t_end-4M and t_end-6M (respectively 2, 4 and 6 months before t_end) were analyzed to extract relevant variations among eleven perfusion biomarkers (B). These variations were assessed through R(B), as the absolute value of the ratio between ∆B from t_end-4M to t_end-2M and ∆B from t_end-6M to t_end-4M. The optimal cut-off for R(B) was determined using receiver-operating-characteristic curve analysis.

RESULTS

The fraction of hypoperfused tumor volume (F_hP_g) was a relevant biomarker. A ratio R(F_hP_g) ≥ 0.61 would have been able to anticipate relapse at the next follow-up with a sensitivity/specificity/accuracy of 92.3 %/63.6 %/79.2 %. High R(F_hPg) (≥0.61) was associated with more relapse at t_end compared to low R(F_hPg) (75 % vs 12.5 %, p = 0.008).

CONCLUSION

Iterative analysis of F_hP_g from consecutive examinations could provide surrogate markers to predict progression at the next follow-up.

KEY POINTS

• Related rCBV biomarkers from DSC were assessed to anticipate GBM progression. • Biomarkers were assessed through their patterns of variation during the follow-up. • The fraction of hypoperfused tumour volume (F_hP _g ) seemed to be a relevant biomarker. • An innovative ratio R(F_hP _g ) could be an early surrogate marker of relapse. • A significant time gain could be achieved in the management of GBM patients.

Recent Application of Advanced MR Imaging to Predict Pseudoprogression in High-grade Glioma Patients

Pseudoprogression is regarded as a subacute form of treatment-related change with a reported incidence of 20-30%, occurring predominantly within the first three months after the completion of concurrent chemoradiotherapy (CCRT) in glioblastoma multiforme (GBM) patients. Occurrence of progressive lesions on conventional contrast-enhanced MR imaging may also accompany clinical deterioration, posing considerable diagnostic challenges to clinicians and radiologists. False interpretation of treatment-related change as true progression may lead to the cessation of effective first-line therapy (i.e., adjuvant temozolomide) and unnecessary surgery. Increasing awareness of the diagnostic challenge of the phenomenon has underscored the need for better imaging techniques that may aid in differentiating the treatment-related change from true progression. In this review, we discuss the recent applications of advanced MR imaging such as diffusion-weighted and perfusion-weighted imaging in the evaluation of treatment response in high-grade glioma patients and highlight their potential role in differentiating pseudoprogression from true progression.

Prediction of Response to Concurrent Chemoradiotherapy with Temozolomide in Glioblastoma: Application of Immediate Post-Operative Dynamic Susceptibility Contrast and Diffusion-Weighted MR Imaging

Objective

To determine whether histogram values of the normalized apparent diffusion coefficient (nADC) and normalized cerebral blood volume (nCBV) maps obtained in contrast-enhancing lesions detected on immediate post-operative MR imaging can be used to predict the patient response to concurrent chemoradiotherapy (CCRT) with temozolomide (TMZ).

Materials and Methods

Twenty-four patients with GBM who had shown measurable contrast enhancement on immediate post-operative MR imaging and had subsequently undergone CCRT with TMZ were retrospectively analyzed. The corresponding histogram parameters of nCBV and nADC maps for measurable contrast-enhancing lesions were calculated. Patient groups with progression (n = 11) and non-progression (n = 13) at one year after the operation were identified, and the histogram parameters were compared between the two groups. Receiver operating characteristic (ROC) analysis was used to determine the best cutoff value for predicting progression. Progression-free survival (PFS) was determined with the Kaplan-Meier method and the log-rank test.

Results

The 99th percentile of the cumulative nCBV histogram (nCBV C99) on immediate post-operative MR imaging was a significant predictor of one-year progression (p = 0.033). ROC analysis showed that the best cutoff value for predicting progression after CCRT was 5.537 (sensitivity and specificity were 72.7% and 76.9%, respectively). The patients with an nCBV C99 of < 5.537 had a significantly longer PFS than those with an nCBV C99 of ≥ 5.537 (p = 0.026).

Conclusion

The nCBV C99 from the cumulative histogram analysis of the nCBV from immediate post-operative MR imaging may be feasible for predicting glioblastoma response to CCRT with TMZ.

Independent Poor Prognostic Factors for True Progression after Radiation Therapy and Concomitant Temozolomide in Patients with Glioblastoma: Subependymal Enhancement and Low ADC Value

BACKGROUND AND PURPOSE

Subependymal enhancement and DWI have been reported to be useful MR imaging markers for identifying true progression. Our aim was to determine whether the subependymal enhancement pattern and ADC can differentiate true progression from pseudoprogression in patients with glioblastoma multiforme treated with concurrent chemoradiotherapy by using temozolomide.

MATERIALS AND METHODS

Forty-two patients with glioblastoma multiforme with newly developed or enlarged enhancing lesions on the first follow-up MR images obtained within 2 months of concurrent chemoradiotherapy completion were included. Subependymal enhancement was analyzed for the presence, location, and pattern (local or distant relative to enhancing lesions). The mean ADC value and the fifth percentile of the cumulative ADC histogram were determined. A multiple logistic regression analysis was performed to identify independent factors associated with true progression.

RESULTS

Distant subependymal enhancement (ie, extending >1 cm or isolated from the enhancing lesion) was significantly more common in true progression (n = 24) than in pseudoprogression (n = 18) (P = .042). The fifth percentile of the cumulative ADC histogram was significantly lower in true progression than in pseudoprogression (P = .014). Both the distant subependymal enhancement and the fifth percentile of the cumulative ADC histogram were independent factors associated with true progression (P = .041 and P = .033, respectively). Sensitivity and specificity for the diagnosis of true progression were 83% and 67%, respectively, by using both factors.

CONCLUSIONS

Both the distant subependymal enhancement and the fifth percentile of the cumulative ADC histogram were significant independent factors predictive of true progression.

Physiologic MRI for assessment of response to therapy and prognosis in glioblastoma

Aside from bidimensional measurements from conventional contrast-enhanced MRI, there are no validated or FDA-qualified imaging biomarkers for high-grade gliomas. However, advanced functional MRI techniques, including perfusion- and diffusion-weighted MRI, have demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response. They may also prove useful for differentiating pseudoprogression from true progression after temozolomide chemoradiation and pseudoresponse from true response after anti-angiogenic therapy. This review will highlight recent developments using these techniques and emphasize the need for technical standardization and validation in prospective studies in order for these methods to become incorporated into standard-of-care imaging for brain tumor patients.

Dynamic contrast enhanced T1 MRI perfusion differentiates pseudoprogression from recurrent glioblastoma

Pseudoprogression may present as transient new or increasing enhancing lesions that mimic recurrent tumors in treated glioblastoma. The purpose of this study was to examine the utility of dynamic contrast enhanced T1 magnetic resonance imaging (DCE MRI) in differentiating between pseudoprogression and tumor progression and devise a cut-off value sensitive for pseudoprogression. We retrospectively examined 37 patients with glioblastoma treated with radiation and temozolomide after surgical resection that then developed new or increasing enhancing lesion(s) indeterminate for pseudoprogression versus progression. Volumetric plasma volume (Vp) and time-dependent leakage constant (Ktrans) maps were measured for the enhancing lesion and the mean and ninetieth percentile histogram values recorded. Lesion outcome was determined by clinical follow up with pseudoprogression defined as stable disease not requiring new treatment. Statistical analysis was performed with Wilcoxon rank-sum tests. Patients with pseudoprogression (n = 13) had Vp (mean) = 2.4 and Vp (90 %tile) = 3.2; and Ktrans (mean) = 3.5 and Ktrans (90 %tile) = 4.2. Patients with tumor progression (n = 24) had Vp (mean) = 5.3 and Vp (90 %tile) = 6.6; and Ktrans (mean) = 7.4 and Ktrans (90 %tile) = 9.1. Compared with tumor progression, pseudoprogression demonstrated lower Vp perfusion values (p = 0.0002) with a Vp (mean) cutoff <3.7 yielding 85% sensitivity and 79% specificity for pseudoprogression. Ktrans (mean) of >3.6 had a 69% sensitivity and 79% specificity for disease progression. DCE MRI shows lower plasma volume and time dependent leakage constant values in pseudoprogression than in tumor progression. A cut-off value with high sensitivity for pseudoprogression can be applied to aid in interpretation of DCE MRI.

Relative cerebral blood volume is a potential predictive imaging biomarker of bevacizumab efficacy in recurrent glioblastoma

BACKGROUND

To analyze the relevance of dynamic susceptibility-weighted contrast-enhanced MRI (DSC-MRI) derived relative cerebral blood volume (rCBV) analysis for predicting response to bevacizumab (BEV) in patients with recurrent glioblastoma (rGB).

METHODS

A total of 127 patients diagnosed with rGB receiving either bevacizumab (71 patients, BEV cohort) or alkylating chemotherapy (56 patients, non-BEV cohort) underwent conventional anatomic MRI and DSC-MRI at baseline and at first follow-up after treatment initiation. The mean rCBV of the contrast-enhancing tumor (cT1) as well as cT1 and fluid-attenuated inversion recovery (FLAIR) volumes at both time points were correlated with progression-free survival (PFS) and overall survival (OS) using Cox proportional hazard models, logistic regression, and the log-rank test.

RESULTS

Baseline rCBV was associated with both PFS (hazard ratio [HR] = 1.3; P < .01) and OS (HR = 1.3; P < .01) in the BEV cohort and predicted 6-month PFS in 82% and 12-month OS in 79% of patients, whereas it was not associated with PFS (HR = 1.0; P = .70) or OS (HR = 1.0; P = .47) in the non-BEV cohort. Corresponding median OS and PFS rates in the BEV cohort for patients with rCBV-values less than 3.92 (optimal threshold from receiver operating characteristic [ROC] analysis of 12-month OS data) were 14.2 and 6.0 months, as compared to 6.6 and 2.8 months for patients with rCBV-values greater than 3.92 (P < .01, respectively). cT1 and FLAIR volumes at first follow-up were significant predictors of 6-month PFS and 12-month OS in the BEV cohort but not in the non-BEV cohort. Corresponding volumes at baseline were not significant in any cohort.

CONCLUSIONS

Pretreatment rCBV is a potential predictive imaging biomarker in BEV-treated rGB but not alkylating chemotherapy-treated rGB, which is superior to volumetric analysis of conventional anatomic MRI and predicts 6-month PFS and 12-month OS in 80% of BEV-treated patients.

Prognosis prediction of measurable enhancing lesion after completion of standard concomitant chemoradiotherapy and adjuvant temozolomide in glioblastoma patients: application of dynamic susceptibility contrast perfusion and diffusion-weighted imaging

Purpose

To assess the prognosis predictability of a measurable enhancing lesion using histogram parameters produced by the normalized cerebral blood volume (nCBV) and normalized apparent diffusion coefficient (nADC) after completion of standard concomitant chemoradiotherapy (CCRT) and adjuvant temozolomide (TMZ) medication in glioblastoma multiforme (GBM) patients.

Materials and Methods

This study was approved by the institutional review board (IRB), and the requirement for informed consent was waived. A total of 59 patients with newly diagnosed GBM who received standard CCRT with TMZ and adjuvant TMZ for six cycles underwent perfusion-weighted and diffusion-weighted imaging. Twenty-seven patients had a measurable enhancing lesion and 32 patients lacked a measurable enhancing lesion based on the Response Assessment in Neuro-Oncology (RANO) criteria in the follow-up MRI, which was performed within 3 months after adjuvant TMZ therapy was completed. We measured the nCBV and nADC histogram parameters based on the measurable enhancing lesion. The progression free survival (PFS) was analyzed by the Kaplan-Meier method with the use of the log-rank test.

Results

The median PFS of patients lacking measurable enhancing lesion was longer than for those with measurable enhancing lesions (17.6 vs 3.3 months, P<.0001). There was a significant, positive correlation between the 99^th percentile nCBV value of a measurable enhancing lesion and the PFS (P = .044, R² = .152). In addition, the median PFS was longer in patients with a 99^th percentile nCBV value ≧4.5 than it was in those with a value <4.5 (4.4 vs 3.1 months, P = .036).

Conclusion

We found that the nCBV value can be used for the prognosis prediction of a measurable enhancing lesion after the completion of standard treatment for GBM, wherein a high 99^th percentile nCBV value (≧4.5) suggests a better PFS for GBM patients.

Glioblastoma treated with concurrent radiation therapy and temozolomide chemotherapy: differentiation of true progression from pseudoprogression with quantitative dynamic contrast-enhanced MR imaging

PURPOSE

To explore the role of dynamic contrast material-enhanced magnetic resonance (MR) imaging in the differentiation of true progression from pseudoprogression in patients with glioblastoma on the basis of findings in entirely newly developed or enlarged enhancing lesions after concurrent radiation therapy and chemotherapy with temozolomide and to evaluate the diagnostic performance of the quantitative pharmacokinetic parameters obtained at dynamic contrast-enhanced MR imaging, such as the volume transfer constant (K(trans)), the extravascular extracellular space per unit volume of tissue(ve), and the blood plasma volume per unit volume of tissue(vp).

MATERIALS AND METHODS

This prospective study had institutional review board approval; written informed consent was obtained from all patients. Thirty-three patients with histopathologically proven glioblastoma who had undergone concurrent radiation therapy and chemotherapy with temozolomide were included. Dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters, including K(trans), ve, and vp, were calculated for newly developed or enlarged enhancing lesions. Pharmacokinetic parameters were compared between the true progression (n = 17) and pseudoprogression (n = 16) groups by using unpaired t tests and then multivariable analysis.

RESULTS

The mean K(trans) and ve were higher in the true progression group than in the pseudoprogression group (mean K(trans), 0.44 min(-1) ± 0.25 [standard deviation] and 0.23 min(-1) ± 0.10 for true progression and pseudoprogression groups, respectively, P = .004; and mean ve, 1.26 ± 0.78 and 0.75 ± 0.49 for true progression and pseudoprogression groups, respectively, P = .034). Multivariable analysis showed that mean K(trans) was the only independently differentiating variable (P = .004).

CONCLUSION

Dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters, including K(trans) and ve, in the entire newly developed or enlarged enhancing lesion may be useful objective diagnostic tools in the differentiation of true progression from pseudoprogression in patients with glioblastoma who have undergone concurrent radiation therapy and chemotherapy with temozolomide.

Use of high-resolution volumetric MR spectroscopic imaging in assessing treatment response of glioblastoma to an HDAC inhibitor

OBJECTIVE

Improved predictive imaging would enable personalization and adjustment of treatment, which are critical for patients with glioblastomain whom therapy is likely to fail. This article describes the use of MR spectroscopic imaging (MRSI) to predict early clinical and behavioral response to a therapy and an effort to develop high-resolution, volumetric MRSI to improve its clinical application.

CONCLUSION

MRSI may enable quantitative analysis of brain tumor response, offering a precise tool for monitoring of patients in clinical trials.

Improving tumour heterogeneity MRI assessment with histograms

By definition, tumours are heterogeneous. They are defined by marked differences in cells, microenvironmental factors (oxygenation levels, pH, VEGF, VPF and TGF-α) metabolism, vasculature, structure and function that in turn translate into heterogeneous drug delivery and therapeutic outcome. Ways to estimate quantitatively tumour heterogeneity can improve drug discovery, treatment planning and therapeutic responses. It is therefore of paramount importance to have reliable and reproducible biomarkers of cancerous lesions' heterogeneity. During the past decade, the number of studies using histogram approaches increased drastically with various magnetic resonance imaging (MRI) techniques (DCE-MRI, DWI, SWI etc.) although information on tumour heterogeneity remains poorly exploited. This fact can be attributed to a poor knowledge of the available metrics and of their specific meaning as well as to the lack of literature references to standardised histogram methods with which surrogate markers of heterogeneity can be compared. This review highlights the current knowledge and critical advances needed to investigate and quantify tumour heterogeneity. The key role of imaging techniques and in particular the key role of MRI for an accurate investigation of tumour heterogeneity is reviewed with a particular emphasis on histogram approaches and derived methods.

Perfusion magnetic resonance imaging: a comprehensive update on principles and techniques

Perfusion is a fundamental biological function that refers to the delivery of oxygen and nutrients to tissue by means of blood flow. Perfusion MRI is sensitive to microvasculature and has been applied in a wide variety of clinical applications, including the classification of tumors, identification of stroke regions, and characterization of other diseases. Perfusion MRI techniques are classified with or without using an exogenous contrast agent. Bolus methods, with injections of a contrast agent, provide better sensitivity with higher spatial resolution, and are therefore more widely used in clinical applications. However, arterial spin-labeling methods provide a unique opportunity to measure cerebral blood flow without requiring an exogenous contrast agent and have better accuracy for quantification. Importantly, MRI-based perfusion measurements are minimally invasive overall, and do not use any radiation and radioisotopes. In this review, we describe the principles and techniques of perfusion MRI. This review summarizes comprehensive updated knowledge on the physical principles and techniques of perfusion MRI.