Functional diffusion map: a noninvasive MRI biomarker for early stratification of clinical brain tumor response

Multimodal imaging of gliomas in the context of evolving cellular and molecular therapies

The vast majority of malignant gliomas relapse after surgery and standard radio-chemotherapy. Novel molecular and cellular therapies are thus being developed, targeting specific aspects of tumor growth. While histopathology remains the gold standard for tumor classification, neuroimaging has over the years taken a central role in the diagnosis and treatment follow up of brain tumors. It is used to detect and localize lesions, define the target area for biopsies, plan surgical and radiation interventions and assess tumor progression and treatment outcome. In recent years the application of novel drugs including anti-angiogenic agents that affect the tumor vasculature, has drastically modulated the outcome of brain tumor imaging. To properly evaluate the effects of emerging experimental therapies and successfully support treatment decisions, neuroimaging will have to evolve. Multi-modal imaging systems with existing and new contrast agents, molecular tracers, technological advances and advanced data analysis can all contribute to the establishment of disease relevant biomarkers that will improve disease management and patient care. In this review, we address the challenges of glioma imaging in the context of novel molecular and cellular therapies, and take a prospective look at emerging experimental and pre-clinical imaging techniques that bear the promise of meeting these challenges.

Assessing tumor cytoarchitecture using multiecho DSC-MRI derived measures of the transverse relaxivity at tracer equilibrium (TRATE)

PURPOSE

In brain tumor dynamic susceptibility contrast (DSC)-MRI studies, multiecho acquisition methods are used to quantify the dynamic changes in T1 and T2 * that occur when contrast agent (CA) extravasates. Such methods also enable the estimation of the effective tissue CA transverse relaxivity. The goal of this study was to evaluate the sensitivity of the transverse relaxivity at tracer equilibrium (TRATE) to tumor cytoarchitecture.

METHODS

Computational and in vitro studies were used to evaluate the biophysical basis of TRATE. In 9L, C6, and human brain tumors, TRATE, the apparent diffusion coefficient (ADC), the CA transfer constant (K(trans) ), the extravascular extracellular volume fraction (ve ), and histological data were compared.

RESULTS

Simulations and in vitro results indicate that TRATE is highly sensitive to variations in cellular properties such as cell size and density. The histologic cell density and TRATE values were significantly higher in 9L tumors as compared to C6 tumors. In animal and human tumors, a voxel-wise comparison of TRATE with ADC, ve , and K(trans) maps showed low spatial correlation.

CONCLUSION

The assessment of TRATE is clinically feasible and its sensitivity to tissue cytoarchitectural features not present in other imaging methods indicate that it could potentially serve as a unique structural signature or "trait" of cancer.

Serial Diffusion-Weighted and Conventional MR Imaging in Primary Cerebral Neuroblastoma Treated with Radiotherapy and Chemotherapy. A Case Report and Literature Review

Primary cerebral neuroblastoma is a rare malignant tumor encountered most commonly in children. The radiological features of this entity are variable and rarely reported. The diffusion-weighted imaging (DWI) findings have not previously reported. We describe serial DWI and conventional MRI in a case of primary cerebral neuroblastoma to assess the imaging features and the role of DWI for monitoring chemoradiotherapy response.

The comprehensive neuro-oncology data repository (CONDR): a research infrastructure to develop and validate imaging biomarkers

BACKGROUND

Advanced imaging methods have the potential to serve as quantitative biomarkers in neuro-oncology research. However, a lack of standardization of image acquisition, processing, and analysis limits their application in clinical research. Standardization of these methods and an organized archival platform are required to better validate and apply these markers in research settings and, ultimately, in clinical practice.

OBJECTIVE

The primary objective of the Comprehensive Neuro-oncology Data Repository (CONDR) is to develop a data set for assessing and validating advanced imaging methods in patients diagnosed with brain tumors. As a secondary objective, informatics resources will be developed to facilitate the integrated collection, processing, and analysis of imaging, tissue, and clinical data in multicenter clinical trials. Finally, CONDR data and informatics resources will be shared with the research community for further analysis.

METHODS

CONDR will enroll 200 patients diagnosed with primary brain tumors. Clinical, imaging, and tissue-based data are obtained from patients serially, beginning with diagnosis and continuing over the course of their treatment. The CONDR imaging protocol includes structural and functional sequences, including diffusion- and perfusion-weighted imaging. All data are managed within an XNAT-based informatics platform. Imaging markers are assessed by correlating image and spatially aligned pathological markers and a variety of clinical markers.

EXPECTED OUTCOMES

CONDR will generate data for developing and validating imaging markers of primary brain tumors, including multispectral and probabilistic maps.

DISCUSSION

CONDR implements a novel, open-research model that will provide the research community with both open-access data and open-source informatics resources.

Perfusion parameters of dynamic contrast-enhanced magnetic resonance imaging predict outcomes of hepatocellular carcinoma receiving radiotherapy with or without thalidomide

BACKGROUND

To correlate between signal parameters using dynamic contrast-enhanced magnetic resonance imaging (DCEMRI) and outcomes of hepatocellular carcinoma (HCC) receiving radiotherapy with or without concomitant thalidomide.

METHODS

DCEMRI was performed in advanced HCC patients undergoing radiotherapy with or without concomitant thalidomide. Initial first-pass enhancement slopes (slope) and peak enhancement ratios (peak) were measured over an operator-defined region of interest over tumor and non-tumor liver parenchyma. The perfusion parameters were correlated with clinical outcomes. The study was registered with ClinicalTrials.gov. (identifier NCT00155272).

RESULTS

Forty-three patients were evaluable. There were 18 partial responses (PRs), 5 minimal responses (MRs), 17 stable diseases (SDs), and 3 progressive diseases (PDs). Baseline perfusion parameters as well as slope at 14 days of radiotherapy were higher in patients with PR or MR compared to SD or PD (0.81 ± 0.29 vs. 0.49 ± 0.34, p < 0.01; 0.39 ± 0.15 vs. 0.28 ± 0.16, p = 0.02; 0.97 ± 0.38 vs. 0.46 ± 0.26, p < 0.01; respectively). Multivariate analysis revealed perfusion parameters over liver parenchyma, but not over tumor, and independently predicted progression-free and overall survival (182 ± 33 vs. 105 ± 26 days, p = 0.01; 397 ± 111 vs. 233 ± 19 days, p = 0.001 respectively). For 22 patients receiving concomitant thalidomide, the perfusion parameters were not significantly different from those receiving radiotherapy alone.

CONCLUSIONS

Signal parameters of DCEMRI over tumor and liver parenchyma correlated with tumor response and survival, respectively, in HCC patients receiving radiotherapy.

Review of treatment assessment using DCE-MRI in breast cancer radiation therapy

As a noninvasive functional imaging technique, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is being used in oncology to measure properties of tumor microvascular structure and permeability. Studies have shown that parameters derived from certain pharmacokinetic models can be used as imaging biomarkers for tumor treatment response. The use of DCE-MRI for quantitative and objective assessment of radiation therapy has been explored in a variety of methods and tumor types. However, due to the complexity in imaging technology and divergent outcomes from different pharmacokinetic approaches, the method of using DCE-MRI in treatment assessment has yet to be standardized, especially for breast cancer. This article reviews the basic principles of breast DCE-MRI and recent studies using DCE-MRI in treatment assessment. Technical and clinical considerations are emphasized with specific attention to assessment of radiation treatment response.

Ocular adnexal lymphoma: monitoring response to therapy with diffusion-weighted imaging

PURPOSE

Outcome evaluation in ocular adnexal lymphoma (OAL) is based on clinical assessment and conventional volumetric changes in tumor size. The purpose of this retrospective study was to compare if changes in apparent diffusion coefficient (ADC) tumor values obtained by diffusion-weighted MRI corresponded to changes in enhancing tumor volume in the evaluation of early treatment response or failure in patients with OAL.

METHODS

A retrospective case series analysis of conventional contrast-enhanced orbital MRI and diffusion-weighted sequences was performed on 8 pathologically confirmed OAL tumors before and after therapy. Mean ADC values and normalized ADC ratios were obtained using a region-of-interest analysis method on enhancing OAL lesions; tumor volumes were calculated using a manual segmentation method. Changes in tumor volume, mean ADC tumor values, and normalized ADC ratios were compared before and after therapy using a Wilcoxon rank-sum test.

RESULTS

Overall, a significant difference was found in mean ADC values and normalized ADC ratios within OAL tumors before and after therapy (p < 0.05), irrespective of the type of therapy administered. There was a trend toward decreased mean enhancing tumor volume after therapy (p = 0.161). An increase in ADC values and a decrease in enhancing tumor volume after therapy correlated with a positive treatment response in 7 of 8 tumors; a decrease in ADC values and an increase in enhancing tumor volume after therapy correlated with a negative treatment response in 1 of 8 tumors.

CONCLUSIONS

Tracking changes in tumor ADC values after various treatment regimens for OAL may be useful in predicting early treatment response or failure and can provide complementary information that corresponds to conventional volume changes in tumor size. Further validation of these preliminary results in larger prospective randomized trials is needed.

The role of imaging in radiation therapy planning: past, present, and future

The use of ionizing radiation for cancer treatment has undergone extraordinary development during the past hundred years. The advancement of medical imaging has been critical in helping to achieve this change. The invention of computed tomography (CT) was pivotal in the development of treatment planning. Despite some disadvantages, CT remains the only three-dimensional imaging modality used for dose calculation. Newer image modalities, such as magnetic resonance (MR) imaging and positron emission tomography (PET), are also used secondarily in the treatment-planning process. MR, with its better tissue contrast and resolution than those of CT, improves tumor definition compared with CT planning alone. PET also provides metabolic information to supplement the CT and MR anatomical information. With emerging molecular imaging techniques, the ability to visualize and characterize tumors with regard to their metabolic profile, active pathways, and genetic markers, both across different tumors and within individual, heterogeneous tumors, will inform clinicians regarding the treatment options most likely to benefit a patient and to detect at the earliest time possible if and where a chosen therapy is working. In the post-human-genome era, multimodality scanners such as PET/CT and PET/MR will provide optimal tumor targeting information.

Determination of malignancy and characterization of hepatic tumor type with diffusion-weighted magnetic resonance imaging: comparison of apparent diffusion coefficient and intravoxel incoherent motion-derived measurements

OBJECTIVE

The objective of this study was to compare the value of the apparent diffusion coefficient (ADC) determined with 3 b values and the intravoxel incoherent motion (IVIM)-derived parameters in the determination of malignancy and characterization of hepatic tumor type.

MATERIALS AND METHODS

Seventy-six patients with 86 solid hepatic lesions, including 8 hemangiomas, 20 lesions of focal nodular hyperplasia, 9 adenomas, 30 hepatocellular carcinomas, 13 metastases, and 6 cholangiocarcinomas, were assessed in this prospective study. Diffusion-weighted images were acquired with 11 b values to measure the ADCs (with b = 0, 150, and 500 s/mm) and the IVIM-derived parameters, namely, the pure diffusion coefficient and the perfusion-related diffusion fraction and coefficient. The diffusion parameters were compared between benign and malignant tumors and between tumor types, and their diagnostic value in identifying tumor malignancy was assessed.

RESULTS

The apparent and pure diffusion coefficients were significantly higher in benign than in malignant tumors (benign: 2.32 [0.87] × 10 mm/s and 1.42 [0.37] × 10 mm/s vs malignant: 1.64 [0.51] × 10 mm/s and 1.14 [0.28] × 10 mm/s, respectively; P < 0.0001 and P = 0.0005), whereas the perfusion-related diffusion parameters did not differ significantly between the 2 groups. The apparent and pure diffusion coefficients provided similar accuracy in assessing tumor malignancy (areas under the receiver operating characteristic curve of 0.770 and 0.723, respectively). In the multigroup analysis, the ADC was found to be significantly higher in hemangiomas than in hepatocellular carcinomas, metastases, and cholangiocarcinomas. In the same manner, it was higher in lesions of focal nodular hyperplasia than in metastases and cholangiocarcinomas. However, the pure diffusion coefficient was significantly higher only in hemangiomas versus hepatocellular and cholangiocellular carcinomas.

CONCLUSIONS

Compared with the ADC, the diffusion parameters derived from the IVIM model did not improve the determination of malignancy and characterization of hepatic tumor type.

Parametric response maps of perfusion MRI may identify recurrent glioblastomas responsive to bevacizumab and irinotecan

BACKGROUND

Perfusion weighted imaging (PWI) can be used to measure key aspects of tumor vascularity in vivo and recent studies suggest that perfusion imaging may be useful in the early assessment of response to angiogenesis inhibitors. Aim of this work is to compare Parametric Response Maps (PRMs) with the Region Of Interest (ROI) approach in the analysis of tumor changes induced by bevacizumab and irinotecan in recurrent glioblastomas (rGBM), and to evaluate if changes in tumor blood volume measured by perfusion MRI may predict clinical outcome.

METHODS

42 rGBM patients with KPS ≥ 50 were treated until progression, as defined by MRI with RANO criteria. Relative cerebral blood volume (rCBV) variation after 8 weeks of treatment was calculated through semi-automatic ROI placement in the same anatomic region as in baseline. Alternatively, rCBV variations with respect to baseline were calculated into the evolving tumor region using a voxel-by-voxel difference. PRMs were created showing where rCBV significantly increased, decreased or remained unchanged.

RESULTS

An increased blood volume in PRM (PRMCBV+) higher than 18% (first quartile) after 8 weeks of treatment was associated with increased progression free survival (PFS; 24 versus 13 weeks, p = 0.045) and overall survival (OS; 38 versus 25 weeks, p = 0.016). After 8 weeks of treatment ROI analysis showed that mean rCBV remained elevated in non responsive patients (4.8 ± 0.9 versus 5.1 ± 1.2, p = 0.38), whereas decreased in responsive patients (4.2 ± 1.3 versus 3.8 ± 1.6 p = 0.04), and re-increased progressively when patients approached tumor progression.

CONCLUSIONS

Our data suggest that PRMs can provide an early marker of response to antiangiogenic treatment and warrant further confirmation in a larger cohort of GBM patients.

Image registration for quantitative parametric response mapping of cancer treatment response

Imaging biomarkers capable of early quantification of tumor response to therapy would provide an opportunity to individualize patient care. Image registration of longitudinal scans provides a method of detecting treatment associated changes within heterogeneous tumors by monitoring alterations in the quantitative value of individual voxels over time, which is unattainable by traditional volumetric-based histogram methods. The concepts involved in the use of image registration for tracking and quantifying breast cancer treatment response using parametric response mapping (PRM), a voxel-based analysis of diffusion-weighted magnetic resonance imaging (DW-MRI) scans, are presented. Application of PRM to breast tumor response detection is described, wherein robust registration solutions for tracking small changes in water diffusivity in breast tumors during therapy are required. Methodologies that employ simulations are presented for measuring expected statistical accuracy of PRM for response assessment. Test-retest clinical scans are used to yield estimates of system noise to indicate significant changes in voxel-based changes in water diffusivity. Overall, registration-based PRM image analysis provides significant opportunities for voxel-based image analysis to provide the required accuracy for early assessment of response to treatment in breast cancer patients receiving neoadjuvant chemotherapy.

Molecularly targeted therapies for malignant gliomas: advances and challenges

The identification of molecular markers associated with tumor but not with normal tissue has allowed the development of highly specific, targeted therapies for the treatment of cancer. Over the last several years, tremendous advances in our understanding of the genetic and molecular changes involved in the progression of malignant gliomas have triggered a large effort in the development of targeted therapies to treat these tumors. However, to date only a modest clinical benefit, limited to subsets of patients, has been demonstrated. Furthermore, despite a high degree of target selectivity, the use of targeted therapies often has systemic toxicity. The reasons behind this limited clinical success are complex and include the intricacy of the signaling pathways in gliomas and the heterogeneity of the disease process, compounded by existing limitations in assessing the efficacy of these novel agents when conventional end points and clinical trial designs are utilized. However, despite these difficulties targeted therapies remain a very attractive avenue of treatment for malignant gliomas. Three basic approaches are needed to overcome the hurdles associated with targeted therapies: first, further development of genetic profiling techniques will help to better determine the genetic changes and molecular pathways involved in gliomas and will potentially allow the design of individualized therapies based on the genetic and molecular signature of each tumor. Second, there is a need for the development of better combination strategies (complementary targeted agents or targeted agents with chemotherapy drugs) directed towards disease heterogeneity. Third, we need to optimize the design of preclinical and clinical trials to obtain the maximum amount of information in the shortest period of time.

Apparent diffusion coefficient is a prognostic factor of head and neck squamous cell carcinoma treated with radiotherapy

PURPOSE

To evaluate the correlation between apparent diffusion coefficient (ADC) and prognosis in head and neck squamous cell carcinoma (HNSCC) treated with radiotherapy.

MATERIALS AND METHODS

We retrospectively studied 41 patients (38 male and 3 female, ages 37-85 years) diagnosed with HNSCC (14 oropharynx, 22 hypopharynx, 4 larynx, 1 oral cavity) and treated with radiotherapy, with radiation dose to gross tumor volume over 60 Gy. The association between age, gender, performance status, tumor location, T stage, N stage, stage, dose, overall treatment time, treatment method, adjuvant therapy, or ADC and prognosis was analyzed using a Cox proportional hazard test.

RESULTS

ADC calculated with b-values of 300, 500, 750, and 1,000 s/mm(2) (ADC 300-1,000) alone showed a significant correlation with all of the analyses (p = 0.022 for local control, p = 0.0109 for regional control, p = 0.0041 for disease-free survival, and p = 0.0014 for overall survival). ADC calculated with b-values of 0, 100, and 200 s/mm(2) (ADC 0-200) showed a significant correlation with overall survival (p = 0.0012). N stage showed a significant correlation with regional control (p = 0.0241). Performance status showed significant association with local control (p = 0.0459), disease-free survival (p = 0.023), and overall survival (p = 0.0151), respectively.

CONCLUSION

ADC is an independent predictor of prognosis in HNSCC treated with radiotherapy.

Imaging angiogenesis, inflammation, and metastasis in the tumor microenvironment with magnetic resonance imaging

With the development of new imaging techniques, the potential for probing the molecular, cellular, and structural components of the tumor microenvironment in situ has increased dramatically. A multitude of imaging modalities have been successfully employed to probe different aspects of the tumor microenvironment, including expression of molecules, cell motion, cellularity, vessel permeability, vascular perfusion, metabolic and physiological changes, apoptosis, and inflammation. This chapter focuses on the most recent advances in magnetic resonance imaging methods, which offer a number of advantages over other methodologies, including high spatial resolution and the use of nonionizing radiation, as well as the use of such methods in the context of primary and secondary brain tumors. It also highlights how they can be used to assess the molecular and cellular changes in the tumor microenvironment in response to therapy.

High-field small animal magnetic resonance oncology studies

This review focuses on the applications of high magnetic field magnetic resonance imaging (MRI) and spectroscopy (MRS) to cancer studies in small animals. High-field MRI can provide information about tumor physiology, the microenvironment, metabolism, vascularity and cellularity. Such studies are invaluable for understanding tumor growth and proliferation, response to treatment and drug development. The MR techniques reviewed here include (1)H, (31)P, chemical exchange saturation transfer imaging and hyperpolarized (13)C MRS as well as diffusion-weighted, blood oxygen level dependent contrast imaging and dynamic contrast-enhanced MRI. These methods have been proven effective in animal studies and are highly relevant to human clinical studies.

Neuroimaging of primary central nervous system lymphoma in immunocompetent patients: comparison of recent and previous findings

The typical neuroimaging features of primary central nervous system lymphoma (PCNSL) have been described as single or multiple intra-axial, homogenous, contrast-enhancing lesions with marked perilesional edema and restricted diffusion, usually contacting the cerebrospinal fluid surface. Necrosis, peripheral enhancement, hemorrhages, and calcifications are unusual. Recently, some of our patients with PCNSL have had atypical neuroimaging features even before treatment. In this article, we review the neuroimaging characteristics of PCNSL in immunocompetent patients and analyzed how imaging findings over the last 10 years differ from those from more than 10 years ago. Neuroimaging findings suggest that PCNSL is a disease that affects the entire brain. Although some imaging findings are characteristic of PCNSL, the frequency of atypical findings on conventional neuroimaging is increasing. Atypical neuroimaging findings do not rule out PCNSL, even in immunocompetent patients.

Quantitative multiparametric MRI assessment of glioma response to radiotherapy in a rat model

BACKGROUND

The inability of structural MRI to accurately measure tumor response to therapy complicates care management for patients with gliomas. The purpose of this study was to assess the potential of several noninvasive functional and molecular MRI biomarkers for the assessment of glioma response to radiotherapy.

METHODS

Fourteen U87 tumor-bearing rats were irradiated using a small-animal radiation research platform (40 or 20 Gy), and 6 rats were used as controls. MRI was performed on a 4.7 T animal scanner, preradiation treatment, as well as at 3, 6, 9, and 14 days postradiation. Image features of the tumors, as well as tumor volumes and animal survival, were quantitatively compared.

RESULTS

Structural MRI showed that all irradiated tumors still grew in size during the initial days postradiation. The apparent diffusion coefficient (ADC) values of tumors increased significantly postradiation (40 and 20 Gy), except at day 3 postradiation, compared with preradiation. The tumor blood flow decreased significantly postradiation (40 and 20 Gy), but the relative blood flow (tumor vs contralateral) did not show a significant change at most time points postradiation. The amide proton transfer weighted (APTw) signals of the tumor decreased significantly at all time points postradiation (40 Gy), and also at day 9 postradiation (20 Gy). The blood flow and APTw maps demonstrated tumor features that were similar to those seen on gadolinium-enhanced T1-weighted images.

CONCLUSIONS

Tumor ADC, blood flow, and APTw were all useful imaging biomarkers by which to predict glioma response to radiotherapy. The APTw signal was most promising for early response assessment in this model.

Investigation of the diffusion abnormality index as a new imaging biomarker for early assessment of brain tumor response to radiation therapy

BACKGROUND

Diffusion MRI, although having the potential to be a biomarker for early assessment of tumor response to therapy, could be confounded by edema and necrosis in or near the brain tumors. This study aimed to develop and investigate the ability of the diffusion abnormality index (DAI) to be a new imaging biomarker for early assessment of brain metastasis response to radiation therapy (RT).

METHODS

Patients with either radiosensitive or radioresistant brain metastases that were treated by whole brain RT alone or combined with bortezomib as a radiation sensitizer had diffusion-weighted (DW) MRI pre-RT and 2 weeks (2W) after starting RT. A patient-specific diffusion abnormality probability function (DAProF) was created to account for abnormal low and high apparent diffusion coefficients differently, reflecting respective high cellularity and edema/necrosis. The DAI of a lesion was then calculated by the integral of DAProF-weighted tumor apparent diffusion coefficient histogram. The changes in DAI from pre-RT to 2W were evaluated for differentiating the responsive, stable, and progressive tumors and compared with the changes in gross tumor volume and conventional diffusion metrics during the same time interval.

RESULTS

In lesions treated with whole brain RT, the DAI performed the best among all metrics in predicting the posttreatment response of brain metastases to RT. In lesions treated with whole brain RT + bortezomib, although DAI was the best predictor, the performance of all metrics worsened compared with the first group.

CONCLUSIONS

The ability of DAI for early assessment of brain metastasis response to RT depends upon treatment regimes.

Challenges for the functional diffusion map in pediatric brain tumors

Background

The functional diffusion map (fDM) has been suggested as a tool for early detection of tumor treatment efficacy. We aim to study 3 factors that could act as potential confounders in the fDM: areas of necrosis, tumor grade, and change in tumor size.

Methods

Thirty-four pediatric patients with brain tumors were enrolled in a retrospective study, approved by the local ethics committee, to examine the fDM. Tumors were selected to encompass a range of types and grades. A qualitative analysis was carried out to compare how fDM findings may be affected by each of the 3 confounders by comparing fDM findings to clinical image reports.

Results

Results show that the fDM in areas of necrosis do not discriminate between treatment response and tumor progression. Furthermore, tumor grade alters the behavior of the fDM: a decrease in apparent diffusion coefficient (ADC) is a sign of tumor progression in high-grade tumors and treatment response in low-grade tumors. Our results also suggest using only tumor area overlap between the 2 time points analyzed for the fDM in tumors of varying size.

Conclusions

Interpretation of fDM results needs to take into account the underlying biology of both tumor and healthy tissue. Careful interpretation of the results is required with due consideration to areas of necrosis, tumor grade, and change in tumor size.

Impact of perfusion map analysis on early survival prediction accuracy in glioma patients

Studies investigating dynamic susceptibility contrast magnetic resonance imaging-determined relative cerebral blood volume (rCBV) maps as a metric of treatment response assessment have generated conflicting results. We evaluated the potential of various analytical techniques to predict survival of patients with glioma treated with chemoradiation. rCBV maps were acquired in patients with high-grade gliomas at 0, 1, and 3 weeks into chemoradiation therapy. Various analytical techniques were applied to the same cohort of serial rCBV data for early assessment of survival. Three different methodologies were investigated: 1) percentage change of whole tumor statistics (i.e., mean, median, and percentiles), 2) physiological segmentation (low rCBV, medium rCBV, or high rCBV), and 3) a voxel-based approach, parametric response mapping (PRM). All analyses were performed using the same tumor contours, which were determined using contrast-enhanced T1-weighted and fluid attenuated inversion recovery images. The predictive potential of each response metric was assessed at 1-year and overall survival. PRM was the only analytical approach found to generate a response metric significantly predictive of patient 1-year survival. Time of acquisition and contour volume were not found to alter the sensitivity of the PRM approach for predicting overall survival. We have demonstrated the importance of the analytical approach in early response assessment using serial rCBV maps. The PRM analysis shows promise as a unified early and robust imaging biomarker of treatment response in patients diagnosed with high-grade gliomas.

Comparison between diffusion-weighted MRI (DW-MRI) at 1.5 and 3 tesla: a phantom study

PURPOSE

To compare DW-MRI between 1.5 and 3 Tesla (T) in terms of image quality, apparent diffusion coefficient (ADC), reproducibility, lesion-to-background contrast and signal-to-noise ratio (SNR), using a test object.

MATERIALS AND METHODS

A spherical diffusion phantom was used for qualitatively assessing image quality and performing quantitative measurements between the two field strengths.

RESULTS

Distortions and signal losses degraded image quality at 3T even when the protocols were optimized for minimum TE. The ADC, in the majority of the phantom compartments, was significantly different between 1.5T and 3T (P < 0.009), while the average coefficient of variation, excluding the phantom compartments affected by artifacts, was <1.3% at both field strengths. The lesion-to-background contrast was improved at 1.5T for images acquired with b = 1000 s/mm(2) and comparable contrast was achieved at 3T with higher b-values. The SNR gain at 3T could, in theory, be balanced by the increased number of signal excitations one can accommodate at 1.5T to perform DW-MRI within the same acquisition time and possibly improved image quality, when 3T systems with no parallel transmission are used.

CONCLUSION

Further phantom and in vivo studies are required to investigate the utility of DW-MRI at 3T, if image quality and acquisition times comparable to the ones from 1.5T are assumed.

Diffusion-Weighted MRI as a Biomarker of Tumor Radiation Treatment Response Heterogeneity: A Comparative Study of Whole-Volume Histogram Analysis versus Voxel-Based Functional Diffusion Map Analysis

RATIONALE

Treatment of glioblastoma (GBM) remains challenging due in part to its histologic intratumoral heterogeneity that contributes to its overall poor treatment response. Our goal was to evaluate a voxel-based biomarker, the functional diffusion map (fDM), as an imaging biomarker to detect heterogeneity of tumor response in a radiation dose escalation protocol using a genetically engineered murine GBM model.

EXPERIMENTAL DESIGN

Twenty-four genetically engineered murine GBM models [Ink4a-Arf(-/-)/Pten(loxp/loxp)/Ntv-a RCAS/PDGF(+)/Cre(+)] were randomized in four treatment groups (n = 6 per group) consisting of daily doses of 0, 1, 2, and 4 Gy delivered for 5 days. Contrast-enhanced T1-weighted and diffusion-weighted magnetic resonance imaging (MRI) scans were acquired for tumor delineation and quantification of apparent diffusion coefficient (ADC) maps, respectively. MRI experiments were performed daily for a week and every 2 days thereafter. For each animal, the area under the curve (AUC) of the percentage change of the ADC (AUCADC) and that of the increase in fDM values (AUCfDM+) were determined within the first 5 days following therapy initiation.

RESULTS

Animal survival increased with increasing radiation dose. Treatment induced a dose-dependent increase in tumor ADC values. The strongest correlation between survival and ADC measurements was observed using the AUCfDM+ metric (R (2) = 0.88).

CONCLUSION

This study showed that the efficacy of a voxel-based imaging biomarker (fDM) was able to detect spatially varying changes in tumors, which were determined to be a more sensitive predictor of overall response versus whole-volume tumor measurements (AUCADC). Finally, fDM provided for visualization of treatment-associated spatial heterogeneity within the tumor.

Fractional change in apparent diffusion coefficient as an imaging biomarker for predicting treatment response in head and neck cancer treated with chemoradiotherapy

BACKGROUND AND PURPOSE

ADC provides a measure of water molecule diffusion in tissue. The aim of this study was to evaluate whether the fractional change in ADC during therapy can be used as a valid predictive indicator of treatment response in head and neck squamous cell carcinoma treated with chemoradiotherapy.

MATERIALS AND METHODS

Forty patients underwent DWI at pretreatment and 3 weeks after the start of treatment. The pretreatment ADC, fractional change in ADC, tumor regression rate, and other clinical variables were compared with locoregional control and locoregional failure and were analyzed by using logistic regression analysis and receiver operating characteristic analysis. Furthermore, progression-free survival curves divided by the corresponding threshold value were compared by means of the log-rank test.

RESULTS

The fractional change in ADCprimary, the fractional change in ADCnode, primary tumor volume, nodal volume, tumor regression ratenode, N stage, and tumor location revealed significant differences between locoregional failure and locoregional control (P < .05). In univariate analysis, the fractional change in ADCprimary, fractional change in ADCnode, tumor regression ratenode, N stage, and tumor location showed significant association with locoregional control (P < .05). In multivariate analysis, however, only the fractional change in ADCprimary was identified as a significant and independent predictor of locoregional control (P = .04). A threshold fractional change in ADCprimary of 0.24 revealed a sensitivity of 100%, specificity of 78.7%, and overall accuracy of 84.8% for the prediction of locoregional control. Progression-free survival of the 2 groups divided by the fractional change in ADCprimary at 0.24 showed a significant difference (P < .05).

CONCLUSIONS

The results suggest that the fractional change in ADCprimary is a valid imaging biomarker for predicting treatment response in head and neck squamous cell carcinoma treated with chemoradiotherapy.

Value of Magnetic Resonance Diffusion-Weighted Imaging for the Prediction of Radiosensitivity in Nasopharyngeal Carcinoma

Objective

The effectiveness of radiotherapy in nasopharyngeal carcinoma (NPC) is closely related to the radiosensitivity of the carcinoma; however, there is currently no effective method to predict radiosensitivity in NPC. We explored the predictive value of magnetic resonance diffusion-weighted imaging (MR-DWI) for radiosensitivity in NPC.

Study Design

Prospective cohort study.

Setting

Single hospital.

Subjects and Methods

Patients with NPC who received intensity-modulated radiotherapy (IMRT) with or without chemotherapy were enrolled from April 2010 through November 2011. Primary tumor apparent diffusion coefficient (ADC) was measured before treatment (ADC0) and 2 weeks after the start of IMRT (ADC1). ADC change (ΔADC) was calculated as (ADC1 – ADC0)/ADC0 * 100%. Three months after the end of radiotherapy, the short-term effect of radiotherapy was assessed using the World Health Organization’s response evaluation criteria in solid tumors.

Results

Of 134 eligible NPC patients, 121 received combination chemotherapy. Three months after radiotherapy, residual local tumors were detected in 23 (17.2%) cases, and no residual tumors were detected in 111 (82.8%) cases. There was no significant difference in the residual tumor rates of patients receiving combination chemotherapy vs those who did not ( P = 1.000). There were no significant differences in the ADC0 or ADC1 values of patients with and without residual tumors ( P = .083 and .262). The ΔADC values of patients with (49.77% ± 31.02%) and without (68.35% ± 34.22%) residual tumors were significantly different ( t = −2.406, P = .017). Logistic regression analysis indicated that ΔADC was an independent prognostic factor for the short-term effect of IMRT in NPC.

Conclusion

Magnetic resonance diffusion-weighted imaging may potentially have value for predicting radiosensitivity in NPC.

Potential role of preoperative conventional MRI including diffusion measurements in assessing epidermal growth factor receptor gene amplification status in patients with glioblastoma

BACKGROUND AND PURPOSE

Epidermal growth factor receptor amplification is a common molecular event in glioblastomas. The purpose of this study was to examine the potential usefulness of morphologic and diffusion MR imaging signs in the prediction of epidermal growth factor receptor gene amplification status in patients with glioblastoma.

MATERIALS AND METHODS

We analyzed pretreatment MR imaging scans from 147 consecutive patients with newly diagnosed glioblastoma and correlated MR imaging features with tumor epidermal growth factor receptor amplification status. The following morphologic tumor MR imaging features were qualitatively assessed: 1) border sharpness, 2) cystic/necrotic change, 3) hemorrhage, 4) T2-isointense signal, 5) restricted water diffusion, 6) nodular enhancement, 7) subependymal enhancement, and 8) multifocal discontinuous enhancement. A total of 142 patients had DWI available for quantitative analysis. ADC maps were calculated, and the ADCmean, ADCmin, ADCmax, ADCROI, and ADCratio were measured.

RESULTS

Epidermal growth factor receptor amplification was present in 60 patients (40.8%) and absent in 87 patients (59.2%). Restricted water diffusion correlated with epidermal growth factor receptor amplification (P = .04), whereas the other 7 morphologic MR imaging signs did not (P > .12). Quantitative DWI analysis found that all ADC measurements correlated with epidermal growth factor receptor amplification, with the highest correlations found with ADCROI (P = .0003) and ADCmean (P = .0007).

CONCLUSIONS

Our results suggest a role for diffusion MR imaging in the determination of epidermal growth factor receptor amplification status in glioblastoma. Additional work is necessary to confirm these results and isolate new imaging biomarkers capable of noninvasively characterizing the molecular status of these tumors.

Numerical simulations of MREIT conductivity imaging for brain tumor detection

Magnetic resonance electrical impedance tomography (MREIT) is a new modality capable of imaging the electrical properties of human body using MRI phase information in conjunction with external current injection. Recent in vivo animal and human MREIT studies have revealed unique conductivity contrasts related to different physiological and pathological conditions of tissues or organs. When performing in vivo brain imaging, small imaging currents must be injected so as not to stimulate peripheral nerves in the skin, while delivery of imaging currents to the brain is relatively small due to the skull's low conductivity. As a result, injected imaging currents may induce small phase signals and the overall low phase SNR in brain tissues. In this study, we present numerical simulation results of the use of head MREIT for brain tumor detection. We used a realistic three-dimensional head model to compute signal levels produced as a consequence of a predicted doubling of conductivity occurring within simulated tumorous brain tissues. We determined the feasibility of measuring these changes in a time acceptable to human subjects by adding realistic noise levels measured from a candidate 3 T system. We also reconstructed conductivity contrast images, showing that such conductivity differences can be both detected and imaged.

Unresectable hepatocellular carcinoma: MR imaging after intraarterial therapy. Part I. Identification and validation of volumetric functional response criteria

PURPOSE

To identify and validate the optimal thresholds for volumetric functional MR imaging response criteria to predict overall survival after intraarterial treatment (IAT) in patients with unresectable hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

Institutional review board approval and waiver of informed consent were obtained. A total of 143 patients who had undergone MR imaging before and 3-4 weeks after the first cycle of IAT were included. MR imaging analysis of one representative HCC index lesion was performed with proprietary software after initial treatment. Subjects were randomly divided into training (n = 114 [79.7%]) and validation (n = 29 [20.3%]) data sets. Uni- and multivariate Cox models were used to determine the best cutoffs, as well as survival differences, between response groups in the validation data set.

RESULTS

Optimal cutoffs in the training data set were 23% increase in apparent diffusion coefficient (ADC) and 65% decrease in volumetric enhancement in the portal venous phase (VE). Subsequently, 25% increase in ADC and 65% decrease in VE were used to stratify patients in the validation data set. Comparison of ADC responders (n = 12 [58.6%]) with nonresponders (n = 17 [34.5%]) showed significant differences in survival (25th percentile survival, 11.2 vs 4.9 months, respectively; P = .008), as did VE responders (n = 9 [31.0%]) compared with nonresponders (n = 20 [69.0%]; 25th percentile survival, 11.5 vs 5.1 months, respectively; P = .01). Stratification of patients with a combination of the criteria resulted in significant differences in survival between patients with lesions that fulfilled both criteria (n = 6 [20.7%]; too few cases to determine 25th percentile), one criterion (n = 9 [31.0%]; 25th percentile survival, 6.0 months), and neither criterion (n = 14 [48.3%]; 25th percentile survival, 5.1 months; P = .01). The association between the two criteria and overall survival remained significant in a multivariate analysis that included age, sex, Barcelona Clinic for Liver Cancer stage, and number of follow-up treatments.

CONCLUSION

After IAT for unresectable HCC, patients can be stratified into significantly different survival categories based on responder versus nonresponder status according to MR imaging ADC and VE cutoffs.

Unresectable hepatocellular carcinoma: MR imaging after intraarterial therapy. Part II. Response stratification using volumetric functional criteria after intraarterial therapy

PURPOSE

To assess whether volumetric functional magnetic resonance (MR) results 3-4 weeks after initial intraarterial therapy can aid accurate distinction between responders and nonresponders, to determine whether overall survival (OS) is improved, and to compare volumetric functional MR response with anatomic response criteria (Response Evaluation Criteria in Solid Tumors [RECIST], modified RECIST [mRECIST], European Association for the Study of the Liver [EASL]), as well as α1-fetoprotein [AFP] level.

MATERIALS AND METHODS

In this single-institution HIPAA-compliant retrospective, institutional review board-approved study, informed consent was waived; 143 patients with hepatocellular carcinoma underwent intraarterial therapy between October 2005 and February 2011. Volumetric functional MR response (25% or more increase in apparent diffusion coefficient, 65% or more decrease in enhancement) was stratified as follows: Dual-parameter responders fulfilled both criteria, single-parameter responders fulfilled one criterion, and those with stable disease (SD) fulfilled neither. RECIST, mRECIST, EASL, and AFP response criteria were determined. Kaplan-Meier technique, log-rank tests, and the Cox proportional hazards model were used to test whether OS was different per response.

RESULTS

OS differed significantly between single-parameter responders and dual-parameter responders (P = .01) and between single-parameter responders and those with SD (P = .001). Dual-parameter responders' response improved OS compared with single-parameter responders; risk of death decreased (hazard ratio [HR] = 0.28, P = .01). In those with SD compared with single-parameter responders, risk of death increased (HR = 2.09, P = .001). RECIST, mRECIST, and EASL stratification was short of significant; most lesions were classified as SD. Baseline AFP level increased in 55 patients; AFP responders versus AFP nonresponders had decreased risk of death (HR = 0.36, P = .002). Agreement between anatomic response criteria and volumetric functional MR findings (κ = 0.06-0.12) and between AFP response and imaging criteria (κ = -0.04 to 0.14) was low.

CONCLUSION

Volumetric functional MR response 3-4 weeks after initial intraarterial therapy showed improved OS. Volumetric functional MR was superior to current imaging (RECIST, mRECIST, and EASL) and biochemical (AFP level) response criteria.

Serial MR diffusion to predict treatment response in high-grade pediatric brain tumors: a comparison of regional and voxel-based diffusion change metrics

BACKGROUND

Assessment of treatment response by measuring tumor size is known to be a late and potentially confounded response index. Serial diffusion MRI has shown potential for allowing earlier and possibly more reliable response assessment in adult patients, with limited experience in clinical settings and in pediatric brain cancer. We present a retrospective study of clinical MRI data in children with high-grade brain tumors to assess and compare the values of several diffusion change metrics to predict treatment response.

METHODS

Eighteen patients (age range, 1.9-20.6 years) with high-grade brain tumors and serial diffusion MRI (pre- and posttreatment interval range, 1-16 weeks posttreatment) were identified after obtaining parental consent. The following diffusion change metrics were compared with the clinical response status assessed at 6 months: (1) regional change in absolute and normalized apparent diffusivity coefficient (ADC), (2) voxel-based fractional volume of increased (fiADC) and decreased ADC (fdADC), and (3) a new metric based on the slope of the first principal component of functional diffusion maps (fDM).

RESULTS

Responders (n = 12) differed significantly from nonresponders (n = 6) in all 3 diffusional change metrics demonstrating higher regional ADC increase, larger fiADC, and steeper slopes (P < .05). The slope method allowed the best response prediction (P < .01, η(2) = 0.78) with a classification accuracy of 83% for a slope of 58° using receiver operating characteristic (ROC) analysis.

CONCLUSIONS

We demonstrate that diffusion change metrics are suitable response predictors for high-grade pediatric tumors, even in the presence of variable clinical diffusion imaging protocols.

DW-MRI as a Predictive Biomarker of Radiosensitization of GBM through Targeted Inhibition of Checkpoint Kinases

PURPOSE

The inherent treatment resistance of glioblastoma (GBM) can involve multiple mechanisms including checkpoint kinase (Chk1/2)-mediated increased DNA repair capability, which can attenuate the effects of genotoxic chemotherapies and radiation. The goal of this study was to evaluate diffusion-weighted magnetic resonance imaging (DW-MRI) as a biomarker for Chk1/2 inhibitors in combination with radiation for enhancement of treatment efficacy in GBM.

EXPERIMENTAL DESIGN

We evaluated a specific small molecule inhibitor of Chk1/2, AZD7762, in combination with radiation using in vitro human cell lines and in vivo using a genetically engineered GBM mouse model. DW-MRI and T1-contrast MRI were used to follow treatment effects on intracranial tumor cellularity and growth rates, respectively.

RESULTS

AZD7762 inhibited clonal proliferation in a panel of GBM cell lines and increased radiosensitivity in p53-mutated GBM cell lines to a greater extent compared to p53 wild-type cells. In vivo efficacy of AZD7762 demonstrated a dose-dependent inhibitory effect on GBM tumor growth rate and a reduction in tumor cellularity based on DW-MRI scans along with enhancement of radiation efficacy.

CONCLUSION

DW-MRI was found to be a useful imaging biomarker for the detection of radiosensitization through inhibition of checkpoint kinases. Chk1/2 inhibition resulted in antiproliferative activity, prevention of DNA damage-induced repair, and radiosensitization in preclinical GBM tumor models, both in vitro and in vivo. The effects were found to be maximal in p53-mutated GBM cells. These results provide the rationale for integration of DW-MRI in clinical translation of Chk1/2 inhibition with radiation for the treatment of GBM.

Abdominal applications of diffusion-weighted magnetic resonance imaging: Where do we stand

Diffusion-weighted imaging (DWI) is one of the magnetic resonance imaging (MRI) sequences providing qualitative as well as quantitative information at a cellular level. It has been widely used for various applications in the central nervous system. Over the past decade, various extracranial applications of DWI have been increasingly explored, as it may detect changes even before signal alterations or morphological abnormalities become apparent on other pulse sequences. Initial results from abdominal MRI applications are promising, particularly in oncological settings and for the detection of abscesses. The purpose of this article is to describe the clinically relevant basic concepts of DWI, techniques to perform abdominal DWI, its analysis and applications in abdominal visceral MR imaging, in addition to a brief overview of whole body DWI MRI.

Posttreatment evaluation of central nervous system gliomas

Although conventional contrast-enhanced MR imaging remains the standard-of-care imaging method in the posttreatment evaluation of gliomas, recent developments in therapeutic options such as chemoradiation and antiangiogenic agents have caused the neuro-oncology community to rethink traditional imaging criteria. This article highlights the latest recommendations. These recommendations should be viewed as works in progress. As more is learned about the pathophysiology of glioma treatment response, quantitative imaging biomarkers will be validated within this context. There will likely be further refinements to glioma response criteria, although the lack of technical standardization in image acquisition, postprocessing, and interpretation also need to be addressed.

ESR statement on the stepwise development of imaging biomarkers

Development of imaging biomarkers is a structured process in which new biomarkers are discovered, verified, validated and qualified against biological processes and clinical end-points. The validation process not only concerns the determination of the sensitivity and specificity but also the measurement of reproducibility. Reproducibility assessments and standardisation of the acquisition and data analysis methods are crucial when imaging biomarkers are used in multicentre trials for assessing response to treatment. Quality control in multicentre trials can be performed with the use of imaging phantoms. The cost-effectiveness of imaging biomarkers also needs to be determined. A lot of imaging biomarkers are being developed, but there are still unmet needs—for example, in the detection of tumour invasiveness.

Main Messages

• Using imaging biomarkers to streamline drug discovery and disease progression is a huge advancement in healthcare.

• The qualification and technical validation of imaging biomarkers pose unique challenges in that the accuracy, methods, standardisations and reproducibility are strictly monitored.

• The clinical value of new biomarkers is of the highest priority in terms of patient management, assessing risk factors and disease prognosis.

Functional diffusion map as an imaging predictor of functional outcome in patients with primary intracerebral haemorrhage

OBJECTIVE

Predicting outcome in patients with primary intracerebral haemorrhage (ICH) in the acute stage can provide information to determine the best therapeutic and rehabilitation strategies. We prospectively investigated the predictive value of the functional diffusion map (fDM) in the acute stage of ICH.

METHODS

47 patients with ICH were enrolled for clinical evaluation and MRI within 24 h of symptom onset and 5 days after ICH. Functional diffusion mapping prospectively monitored the apparent diffusion coefficient (ADC) maps of perihaematomal oedema. Consequently, the change in perihaematomal oedema was classified into three categories: increased, decreased, or no significant change. Clinical outcomes were evaluated 6 months after ICH according to the modified Rankin Scale. Correlation between clinical outcome and the fDMs was performed.

RESULTS

Among the clinical variables, thalamic haematoma, serum glucose level and National Institutes of Health Stroke Scale scores were significantly different between the good- and poor-outcome groups. The percentage of oedematous tissue undergoing significant change between baseline and Day 5 was also significantly different between the groups.

CONCLUSION

fDMs allow for spatial voxel-by-voxel tracking of changes in ADC values. It may be feasible to use fDMs to predict the functional outcome of patients with ICH during the acute stage. Advances in knowledge The use of fDMs for stroke study is demonstrated. fDMs may be more suitable to reflect the pathophysiological heterogeneity within oedemas and may facilitate another thinking process for imaging study of stroke and other neurological diseases.

Quantitative probabilistic functional diffusion mapping in newly diagnosed glioblastoma treated with radiochemotherapy

BACKGROUND

Functional diffusion mapping (fDM) is a cancer imaging technique that uses voxel-wise changes in apparent diffusion coefficients (ADC) to evaluate response to treatment. Despite promising initial results, uncertainty in image registration remains the largest barrier to widespread clinical application. The current study introduces a probabilistic approach to fDM quantification to overcome some of these limitations.

METHODS

A total of 143 patients with newly diagnosed glioblastoma who were undergoing standard radiochemotherapy were enrolled in this retrospective study. Traditional and probabilistic fDMs were calculated using ADC maps acquired before and after therapy. Probabilistic fDMs were calculated by applying random, finite translational, and rotational perturbations to both pre-and posttherapy ADC maps, then repeating calculation of fDMs reflecting changes after treatment, resulting in probabilistic fDMs showing the voxel-wise probability of fDM classification. Probabilistic fDMs were then compared with traditional fDMs in their ability to predict progression-free survival (PFS) and overall survival (OS).

RESULTS

Probabilistic fDMs applied to patients with newly diagnosed glioblastoma treated with radiochemotherapy demonstrated shortened PFS and OS among patients with a large volume of tumor with decreasing ADC evaluated at the posttreatment time with respect to the baseline scans. Alternatively, patients with a large volume of tumor with increasing ADC evaluated at the posttreatment time with respect to baseline scans were more likely to progress later and live longer. Probabilistic fDMs performed better than traditional fDMs at predicting 12-month PFS and 24-month OS with use of receiver-operator characteristic analysis. Univariate log-rank analysis on Kaplan-Meier data also revealed that probabilistic fDMs could better separate patients on the basis of PFS and OS, compared with traditional fDMs.

CONCLUSIONS

Results suggest that probabilistic fDMs are a more predictive biomarker in terms of 12-month PFS and 24-month OS in newly diagnosed glioblastoma, compared with traditional fDM analysis.

Assessing breast cancer angiogenesis in vivo: which susceptibility contrast MRI biomarkers are relevant?

PURPOSE

There is an impending need for noninvasive biomarkers of breast cancer angiogenesis to evaluate the efficacy of new anti-angiogenic therapies in vivo. The purpose of this study was to systematically evaluate the sensitivity of in vivo steady-state susceptibility contrast-MRI biomarkers of angiogenesis in a human breast cancer model.

METHODS

Orthotopic MDA-MB-231 human breast cancer xenografts were imaged by steady-state susceptibility contrast-MRI at post-inoculation week 3 and post-inoculation week 5, followed by ex vivo whole tumor 3D micro-CT angiography. "Absolute" (i.e., measures of vascular morphology in appropriate units) and "relative" (i.e., proportional to measures of vascular morphology) MRI biomarkers of tumor blood volume, vessel size, and vessel density were computed and their ability to predict the corresponding micro-CT analogs assessed using cross-validation analysis.

RESULTS

All MRI biomarkers significantly correlated with their micro-CT analogs and were sensitive to the micro-CT-measured decreases in tumor blood volume and vessel density from post-inoculation week 3 to post-inoculation week 5. However, cross-validation analysis revealed there was no significant difference between the predictive accuracy of "absolute" and "relative" biomarkers.

CONCLUSION

As "relative" biomarkers are more easily computed from steady-state susceptibility contrast-MRI (i.e., without additional MRI measurements) than "absolute" biomarkers, it makes them promising candidates for assessing breast cancer angiogenesis in vivo.

PET Parametric Response Mapping for Clinical Monitoring and Treatment Response Evaluation in Brain Tumors

PET parametric response maps (PRMs) are a provocative new molecular imaging technique for quantifying brain tumor response to therapy in individual patients. By aligning sequential PET scans over time using anatomic MR imaging information, the voxel-wise change in radiotracer uptake can be quantified and visualized. PET PRMs can be performed before and after a particular therapy to test whether the tumor is responding favorably, or performed relative to a distant time point to monitor changes through the course of a treatment. This article focuses on many of the technical details involved in generating, visualizing, and quantifying PET PRMs, and practical applications and example case studies.

Correlation of MRI-derived apparent diffusion coefficients in newly diagnosed gliomas with [18F]-fluoro-L-dopa PET: what are we really measuring with minimum ADC?

BACKGROUND AND PURPOSE

There is significant interest in whether diffusion-weighted MR imaging indices, such as the minimum apparent diffusion coefficient, may be useful clinically for preoperative tumor grading and treatment planning. To help establish the pathologic correlate of minimum ADC, we undertook a study investigating the relationship between minimum ADC and maximum FDOPA PET uptake in patients with newly diagnosed glioblastoma multiforme.

MATERIALS AND METHODS

MR imaging and FDOPA PET data were acquired preoperatively from 15 patients who were subsequently diagnosed with high-grade brain tumor (WHO grade III or IV) by histopathologic analysis. ADC and SUVR normalized FDOPA PET maps were registered to the corresponding CE MR imaging. Regions of minimum ADC within the FDOPA-defined tumor volume were anatomically correlated with areas of maximum FDOPA SUVR uptake.

RESULTS

Minimal anatomic overlap was found between regions exhibiting minimum ADC (a putative marker of tumor cellularity) and maximum FDOPA SUVR uptake (a marker of tumor infiltration and proliferation). FDOPA SUVR measures for tumoral regions exhibiting minimum ADC (1.36±0.22) were significantly reduced compared with those with maximum FDOPA uptake (2.45±0.88, P=.0001).

CONCLUSIONS

There was a poor correlation between minimum ADC and the most viable/aggressive component of high-grade gliomas. This study suggests that other factors, such as tissue compression and ischemia, may be contributing to restricted diffusion in GBM. Caution should be exercised in the clinical use of minimum ADC as a marker of tumor grade and the use of this index for guiding tumor biopsies preoperatively.

Clinical applications of imaging biomarkers. Part 3. The neuro-oncologist's perspective

Radiation therapy is an important treatment modality in the management of brain tumours. Imaging biomarkers continue to be a focus of active investigation and there is increasing evidence of the utility of biomarkers in refining the overall management plan. This article briefly reviews the literature and outlines the possible clinical applications of imaging biomarkers in neuro-oncology.

Specific biomarkers of receptors, pathways of inhibition and targeted therapies: clinical applications

A deeper understanding of the role of specific genes, proteins, pathways and networks in health and disease, coupled with the development of technologies to assay these molecules and pathways in patients, promises to revolutionise the practice of clinical medicine. In particular, the discovery and development of novel drugs targeted to disease-specific alterations could benefit significantly from non-invasive imaging techniques assessing the dynamics of specific disease-related parameters. Here we review the application of imaging biomarkers in the management of patients with brain tumours, especially malignant glioma. This first part of the review focuses on imaging biomarkers of general biochemical and physiological processes related to tumour growth such as energy, protein, DNA and membrane metabolism, vascular function, hypoxia and cell death. These imaging biomarkers are an integral part of current clinical practice in the management of primary brain tumours. The second article of the review discusses the use of imaging biomarkers of specific disease-related molecular genetic alterations such as apoptosis, angiogenesis, cell membrane receptors and signalling pathways. Current applications of these biomarkers are mostly confined to experimental small animal research to develop and validate these novel imaging strategies with future extrapolation in the clinical setting as the primary objective.

Diagnosis and treatment in neuro-oncology: an oncological perspective

Although brain tumours are rare compared with other malignancies, they are responsible, in many cases, for severe physical and cognitive disability and have a high case fatality rate (13% overall survival at 5 years). Gliomas account for over 60% of primary brain tumours and usually present with one or more symptoms of raised intracranial pressure, progressive neurological deficit, seizures, focal or global cognitive decline. The diagnosis is made by a combination of imaging and histological examination of tumour specimen. Contrast-enhanced MRI is the gold standard imaging modality and provides highly sensitive anatomical information about the tumour. Advanced imaging modalities provide complementary information about brain tumour metabolism, blood flow and ultrastructure and are being increasingly incorporated into routine clinical sequences. Imaging is essential for guiding surgery and radiotherapy treatments and for monitoring response to, and progression of, therapy. However, changes in imaging over time may be misinterpreted and lead to incorrect assumptions about the effectiveness of treatments. Thus, the disappearance of contrast enhancement and resolution of oedema after anti-angiogenesis treatments is seen early while conventional T(2) weighted/FLAIR sequences demonstrate continual tumour growth (pseudoregression). Conversely imaging may suggest lack of efficacy of treatment e.g. increasing tumour size and contrast enhancement following chemoradiation for malignant gliomas (pseudoprogression), which then stabilise or resolve after a few months of continued treatment and that paradoxically may be associated with a better outcome. These factors have led to a re-evaluation of the role of standard sequences in the assessment of treatment response spurning interest in the development of quantitative biomarkers.

Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression

Chronic obstructive pulmonary disease (COPD) is increasingly being recognized as a highly heterogeneous disorder, composed of varying pathobiology. Accurate detection of COPD subtypes by image biomarkers are urgently needed to enable individualized treatment thus improving patient outcome. We adapted the Parametric Response Map (PRM), a voxel-wise image analysis technique, for assessing COPD phenotype. We analyzed whole lung CT scans of 194 COPD individuals acquired at inspiration and expiration from the COPDGene Study. PRM identified the extent of functional small airways disease (fSAD) and emphysema as well as provided CT-based evidence that supports the concept that fSAD precedes emphysema with increasing COPD severity. PRM is a versatile imaging biomarker capable of diagnosing disease extent and phenotype, while providing detailed spatial information of disease distribution and location. PRMs ability to differentiate between specific COPD phenotypes will allow for more accurate diagnosis of individual patients complementing standard clinical techniques.

An approach to identify, from DCE MRI, significant subvolumes of tumors related to outcomes in advanced head-and-neck cancer

PURPOSE

To develop and investigate a method to identify, from dynamic contrast enhanced (DCE) MRI, significant subvolumes of tumors related to treatment outcomes.

METHODS

A method, called global-initiated regularized local fuzzy clustering, was proposed to identify subvolumes of head-and-neck cancers (HNC) from heterogeneous distributions of tumor blood volume (BV) and blood flow (BF) for assessment of therapy response. BV and BF images, derived from DCE MRI, of 14 patients with advanced HNC were obtained before treatment and 2 weeks after the start of 7-week chemoradiation therapy (chemo-RT). The delineated subvolumes of tumors with low BV or BF before and during treatment were evaluated for their associations with local failure (LF). Receiver operating characteristic (ROC) analysis was used to assess performance of the method for prediction of local failure of HNC.

RESULTS

The sizes of the subvolumes of primary tumors with low BV, delineated by our method before and week 2 during treatment, were significantly greater in the patients with LF than with local control (LC) (p = 0.02 for pre-RT and 0.01 for week 2). While the total primary tumor volumes were reduced from baseline to week 2 during therapy to a similar extent for both the patients with LF and LC, the percentage decreases in the subvolumes of the primary tumors with low BV in the same time interval were significantly smaller for the patients with LF than those with LC (p < 0.05). ROC analysis shows that for any given sensitivity, the subvolume of the tumor with low BV week 2 during treatment has greater specificity for prediction of local failure than the pretreatment total tumor volume, the percentage change in the tumor volume week 2 during treatment, or the change in the averaged BV values of the entire tumor week 2 during therapy.

CONCLUSIONS

We developed a method to identify the significant subvolumes of primary tumors related to local failure. Large poorly perfused subvolumes of primary or nodal HNC before treatment and persisting during the early course of chemo-RT have the potential for prediction of local or regional failure, and could be candidates for local dose intensification.