An imaging biomarker of early treatment response in prostate cancer that has metastasized to the bone

Diffusion-Weighted MRI for Treatment Response Assessment in Osteoblastic Metastases-A Repeatability Study

The apparent diffusion coefficient (ADC) is a candidate marker of treatment response in osteoblastic metastases that are not evaluable by morphologic imaging. However, it is unclear whether the ADC meets the basic requirement for reliable treatment response evaluation, namely a low variance of repeated measurements in relation to the differences found between viable and nonviable metastases. The present study addresses this question by analyzing repeated in vivo ADCmedian measurements of 65 osteoblastic metastases in nine patients, as well as phantom measurements. PSMA-PET served as a surrogate for bone metastasis viability. Measures quantifying repeatability were calculated and differences in mean ADC values according to PSMA-PET status were examined. The relative repeatability coefficient %RC of ADCmedian measurements was 5.8% and 12.9% for phantom and in vivo measurements, respectively. ADCmedian values of bone metastases ranged from 595×10-6mm2/s to 2090×10-6mm2/s with an average of 63% higher values in nonviable metastases compared with viable metastases (p < 0.001). ADC shows a small repeatability coefficient in relation to the difference in ADC values between viable and nonviable metastases. Therefore, ADC measurements fulfill the technical prerequisite for reliable treatment response evaluation in osteoblastic metastases.

Voxel-wise prostate cell density prediction using multiparametric magnetic resonance imaging and machine learning

BACKGROUND

There are currently no methods to estimate cell density in the prostate. This study aimed to develop predictive models to estimate prostate cell density from multiparametric magnetic resonance imaging (mpMRI) data at a voxel level using machine learning techniques.

MATERIAL AND METHODS

In vivo mpMRI data were collected from 30 patients before radical prostatectomy. Sequences included T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced imaging. Ground truth cell density maps were computed from histology and co-registered with mpMRI. Feature extraction and selection were performed on mpMRI data. Final models were fitted using three regression algorithms including multivariate adaptive regression spline (MARS), polynomial regression (PR) and generalised additive model (GAM). Model parameters were optimised using leave-one-out cross-validation on the training data and model performance was evaluated on test data using root mean square error (RMSE) measurements.

RESULTS

Predictive models to estimate voxel-wise prostate cell density were successfully trained and tested using the three algorithms. The best model (GAM) achieved a RMSE of 1.06 (± 0.06) × 10³ cells/mm² and a relative deviation of 13.3 ± 0.8%.

CONCLUSION

Prostate cell density can be quantitatively estimated non-invasively from mpMRI data using high-quality co-registered data at a voxel level. These cell density predictions could be used for tissue classification, treatment response evaluation and personalised radiotherapy.

Circulating tumor cells in prostate cancer: Precision diagnosis and therapy

The primary cause of tumor-associated mortality in prostate cancer (PCa) remains distant metastasis. The dissemination of tumor cells from the primary tumor to distant sites through the bloodstream cannot be detected early by standard imaging methods. Circulating tumor cells (CTCs) represent an effective prognostic and predictive biomarker, which are able to monitor efficacy of adjuvant therapies, detect early development of metastases, and finally, assess therapeutic responses of advanced disease earlier than traditional diagnostic methods. In addition, since repeated tissue biopsies are invasive, costly and not always feasible, the assessment of tumor characteristics on CTCs, by a peripheral blood sample as a liquid biopsy, represents an attractive opportunity. The implementation of molecular and genomic characterization of CTCs may contribute to improve the treatment selection and thus, to move toward more precise diagnosis and therapy in PCa. The present study summarizes the current advances in CTC enrichment and detection strategies and reviews how CTCs may contribute to significant insights in the metastatic process, as well as how they may be utilized in clinical application in PCa. Although it is proposed that CTCs may offer insights into the prognosis and management of PCa, there are a number of challenges in the study of circulating tumor cells, and their clinical utility remains under investigation.

A Pilot Study of Quantitative MRI Parametric Response Mapping of Bone Marrow Fat for Treatment Assessment in Myelofibrosis

Myelofibrosis (MF) is a hematologic neoplasm arising as a primary disease or secondary to other myeloproliferative neoplasms (MPNs). Both primary and secondary MF are uniquely associated with progressive bone marrow fibrosis, displacing normal hematopoietic cells from the marrow space and disrupting normal production of mature blood cells. Activation of the JAK2 signaling pathway in hematopoietic stem cells commonly causes MF, and ruxolitinib, a drug targeting this pathway, is the treatment of choice for many patients. However, current measures of disease status in MF do not necessarily predict response to treatment with ruxolitinib or other drugs in MF. Bone marrow biopsies are invasive and prone to sampling error, while measurements of spleen volume only indirectly reflect bone marrow status. Toward the goal of developing an imaging biomarker for treatment response in MF, we present preliminary results from a prospective clinical study evaluating parametric response mapping (PRM) of quantitative Dixon MRI bone marrow fat fraction maps in four MF patients treated with ruxolitinib. PRM allows for the voxel-wise identification of significant change in quantitative imaging readouts over time, in this case the bone marrow fat content. We identified heterogeneous response patterns of bone marrow fat among patients and within different bone marrow sites in the same patient. We also observed discordance between changes in bone marrow fat fraction and reductions in spleen volume, the standard imaging metric for treatment efficacy. This study provides initial support for PRM analysis of quantitative MRI of bone marrow fat to monitor response to therapy in MF, setting the stage for larger studies to further develop and validate this method as a complementary imaging biomarker for this disease.

Diffusion MRI with Semi-Automated Segmentation Can Serve as a Restricted Predictive Biomarker of the Therapeutic Response of Liver Metastasis

PURPOSE

To assess the value of semi-automated segmentation applied to diffusion MRI for predicting the therapeutic response of liver metastasis.

METHODS

Conventional diffusion weighted magnetic resonance imaging (MRI) was performed using b-values of 0, 150, 300 and 450s/mm(2) at baseline and days 4, 11 and 39 following initiation of a new chemotherapy regimen in a pilot study with 18 women with 37 liver metastases from primary breast cancer. A semi-automated segmentation approach was used to identify liver metastases. Linear regression analysis was used to assess the relationship between baseline values of the apparent diffusion coefficient (ADC) and change in tumor size by day 39.

RESULTS

A semi-automated segmentation scheme was critical for obtaining the most reliable ADC measurements. A statistically significant relationship between baseline ADC values and change in tumor size at day 39 was observed for minimally treated patients with metastatic liver lesions measuring 2-5cm in size (p=0.002), but not for heavily treated patients with the same tumor size range (p=0.29), or for tumors of smaller or larger sizes. ROC analysis identified a baseline threshold ADC value of 1.33μm(2)/ms as 75% sensitive and 83% specific for identifying non-responding metastases in minimally treated patients with 2-5cm liver lesions.

CONCLUSION

Quantitative imaging can substantially benefit from a semi-automated segmentation scheme. Quantitative diffusion MRI results can be predictive of therapeutic outcome in selected patients with liver metastases, but not for all liver metastases, and therefore should be considered to be a restricted biomarker.

Multimodal imaging of bone metastases: From preclinical to clinical applications

Metastases to the skeletal system are commonly observed in cancer patients, highly affecting the patients' quality of life. Imaging plays a major role in detection, follow-up, and molecular characterisation of metastatic disease. Thus, imaging techniques have been optimised and combined in a multimodal and multiparametric manner for assessment of complementary aspects in osseous metastases. This review summarises both application of the most relevant imaging techniques for bone metastasis in preclinical models and the clinical setting.

Integrated multimodal imaging of dynamic bone-tumor alterations associated with metastatic prostate cancer

Bone metastasis occurs for men with advanced prostate cancer which promotes osseous growth and destruction driven by alterations in osteoblast and osteoclast homeostasis. Patients can experience pain, spontaneous fractures and morbidity eroding overall quality of life. The complex and dynamic cellular interactions within the bone microenvironment limit current treatment options thus prostate to bone metastases remains incurable. This study uses voxel-based analysis of diffusion-weighted MRI and CT scans to simultaneously evaluate temporal changes in normal bone homeostasis along with prostate bone metatastsis to deliver an improved understanding of the spatiotemporal local microenvironment. Dynamic tumor-stromal interactions were assessed during treatment in mouse models along with a pilot prospective clinical trial with metastatic hormone sensitive and castration resistant prostate cancer patients with bone metastases. Longitudinal changes in tumor and bone imaging metrics during delivery of therapy were quantified. Studies revealed that voxel-based parametric response maps (PRM) of DW-MRI and CT scans could be used to quantify and spatially visualize dynamic changes during prostate tumor growth and in response to treatment thereby distinguishing patients with stable disease from those with progressive disease (p<0.05). These studies suggest that PRM imaging biomarkers are useful for detection of the impact of prostate tumor-stromal responses to therapies thus demonstrating the potential of multi-modal PRM image-based biomarkers as a novel means for assessing dynamic alterations associated with metastatic prostate cancer. These results establish an integrated and clinically translatable approach which can be readily implemented for improving the clinical management of patients with metastatic bone disease.

Multi-site clinical evaluation of DW-MRI as a treatment response metric for breast cancer patients undergoing neoadjuvant chemotherapy

PURPOSE

To evaluate diffusion weighted MRI (DW-MR) as a response metric for assessment of neoadjuvant chemotherapy (NAC) in patients with primary breast cancer using prospective multi-center trials which provided MR scans along with clinical outcome information.

MATERIALS AND METHODS

A total of 39 patients with locally advanced breast cancer accrued from three different prospective clinical trials underwent DW-MR examination prior to and at 3-7 days (Hull University), 8-11 days (University of Michigan) and 35 days (NeoCOMICE) post-treatment initiation. Thirteen patients, 12 of which participated in treatment response study, from UM underwent short interval (<1hr) MRI examinations, referred to as "test-retest" for examination of repeatability. To further evaluate stability in ADC measurements, a thermally controlled diffusion phantom was used to assess repeatability of diffusion measurements. MRI sequences included contrast-enhanced T1-weighted, when appropriate, and DW images acquired at b-values of 0 and 800 s/mm2. Histogram analysis and a voxel-based analytical technique, the Parametric Response Map (PRM), were used to derive diffusion response metrics for assessment of treatment response prediction.

RESULTS

Mean tumor apparent diffusion coefficient (ADC) values generated from patient test-retest examinations were found to be very reproducible (|ΔADC|<0.1x10-3mm2/s). This data was used to calculate the 95% CI from the linear fit of tumor voxel ADC pairs of co-registered examinations (±0.45x10-3mm2/s) for PRM analysis of treatment response. Receiver operating characteristic analysis identified the PRM metric to be predictive of outcome at the 8-11 (AUC = 0.964, p = 0.01) and 35 day (AUC = 0.770, p = 0.05) time points (p<.05) while whole-tumor ADC changes where significant at the later 35 day time interval (AUC = 0.825, p = 0.02).

CONCLUSION

This study demonstrates the feasibility of performing a prospective analysis of DW-MRI as a predictive biomarker of NAC in breast cancer patients. In addition, we provide experimental evidence supporting the use of sensitive analytical tools, such as PRM, for evaluating ADC measurements.

Use of diffusion-weighted, intravoxel incoherent motion, and dynamic contrast-enhanced MR imaging in the assessment of response to radiotherapy of lytic bone metastases from breast cancer

RATIONALE AND OBJECTIVES

To investigate the value of diffusion-weighted (DW), perfusion-sensitive, and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) techniques in assessing the response of bone metastases from breast cancer to radiotherapy, with particular emphasis on the role of intravoxel incoherent motion (IVIM)-DW parameters as a potential valuable imaging marker of tumor response.

MATERIALS AND METHODS

Fifteen women having breast cancer and bone metastases underwent MRI before and after radiotherapy (3 weeks [time 1], 2 months [time 2], and 4 months [time 3]), consisting of DW, perfusion-sensitive (IVIM), and DCE acquisitions. MR-based DW and perfusion parameters, including water diffusivity (D), perfusion fraction (f), pseudodiffusion (D*), total apparent diffusion coefficient (ADC-total), fractionated ADCs (ADC-high and ADC-low), and initial area under the gadolinium concentration curve after the first 60 seconds (IAUGC60), were determined. The morphologic MRI findings were also recorded. A one-way repeated measures analysis of variance was used to compare the value of MR-based parameters at the different time points.

RESULTS

A significant variation between pretreatment (time 0) and post-treatment (times 1, 2, and 3) was found for ADC-total and D parameters (P < .001). A statistically significant reduction was also found for IAUGC60 values between times 0 and 3 (P < .001). A significant change across the different time points was observed for D* and IAUGC60 parameters (P < .001). On the contrary, there was no statistically significant change over time for parameters ADC-total, D, f, and IAUGC60 comparing response between each metastasis, that is, the response to therapy was similar for each metastasis.

CONCLUSIONS

DW, IVIM, and DCE-MRI techniques show effectiveness in assessing the response to radiotherapy in bone metastases from breast cancer.

Monitoring the response of bone metastases to treatment with Magnetic Resonance Imaging and nuclear medicine techniques: a review and position statement by the European Organisation for Research and Treatment of Cancer imaging group

Assessment of the response to treatment of metastases is crucial in daily oncological practice and clinical trials. For soft tissue metastases, this is done using computed tomography (CT), Magnetic Resonance Imaging (MRI) or Positron Emission Tomography (PET) using validated response evaluation criteria. Bone metastases, which frequently represent the only site of metastases, are an exception in response assessment systems, because of the nature of the fixed bony defects, their complexity, which ranges from sclerotic to osteolytic and because of the lack of sensitivity, specificity and spatial resolution of the previously available bone imaging methods, mainly bone scintigraphy. Techniques such as MRI and PET are able to detect the early infiltration of the bone marrow by cancer, and to quantify this infiltration using morphologic images, quantitative parameters and functional approaches. This paper highlights the most recent developments of MRI and PET, showing how they enable early detection of bone lesions and monitoring of their response. It reviews current knowledge, puts the different techniques into perspective, in terms of indications, strengths, weaknesses and complementarity, and finally proposes recommendations for the choice of the most adequate imaging technique.

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.

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.

A radiologist's guide to treatment response criteria in oncologic imaging: functional, molecular, and disease-specific imaging biomarkers

OBJECTIVE

This article reviews the functional, molecular, and disease-specific imaging biomarkers of treatment response.

CONCLUSION

Substantial progress has been made in the evolution of drugs directed at specific targets of the tumor lifecycle. These novel agents are predominantly cytostatic, and their efficacy may be optimally evaluated by functional, molecular, and disease-specific imaging biomarkers.

Parametric response mapping of CT images provides early detection of local bone loss in a rat model of osteoporosis

Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization. Onset of bone loss resulting from disease increases the risk of incurring fractures and subsequent pain, increasing medical expenses while reducing quality of life. Although current standard CT-based protocols provide adequate prognostic information for assessing bone loss, many of the techniques for evaluating CT scans rely on measures based on whole-bone summary statistics. This reduces the sensitivity at identifying local regions of bone resorption, as well as formation. In this study, we evaluate the effectiveness of a voxel-based image post-processing technique, called the Parametric Response Map (PRM), for identifying local changes in bone mass in weight-bearing bones on CT scans using an established animal model of osteoporosis. Serial CT scans were evaluated weekly using PRM subsequent to ovariectomy or sham surgeries over the period of one month. For comparison, bone volume fraction and mineral density measurements were acquired and found to significantly differ between groups starting 3 weeks post-surgery. High resolution ex vivo measurements acquired four weeks post-surgery validated the extent of bone loss in the surgical groups. In contrast to standard methodologies for assessing bone loss, PRM results were capable of identifying local decreases in bone mineral by week 2, which were found to be significant between groups. This study concludes that PRM is able to detect changes in bone mineral with higher sensitivity and spatial differentiation than conventional techniques for evaluating CT scans, which may aid in clinical decision making for patients suffering from bone loss.

Optimizing the functional diffusion map using Monte Carlo simulations

PURPOSE

To optimize the diagnostic accuracy of the functional diffusion map for monitoring tumor treatment response in cancer patients.

MATERIALS AND METHODS

Using Monte Carlo simulations, measurement precision of the apparent diffusion coefficient (ADC), and particularly accuracy of threshold determination from healthy reference tissue, are evaluated by investigating the repeatability limit of the ADC as a function of different degrees of diffusion weighting of the sequence. Phantom and in-vivo experiments are performed to verify and illustrate the results of the simulations.

RESULTS

While diagnostic accuracy of the functional diffusion map is hardly diminished by differing values of the T(2) relaxation time in tumor and reference tissue, it is shown to be impaired by differing ADCs, resulting in erroneously determined segmentation thresholds. This problem can be addressed by decreasing the maximum b-factor and increasing the number of signal averages at the maximum b-factor or, alternatively, the number of b-factors while favoring schemes with higher b-factors. Phantom experiments confirm the results of the simulations. In-vivo data are presented to illustrate the effect of sequence optimization on the diagnostic accuracy of the functional diffusion map.

CONCLUSION

The present work demonstrates that the diagnostic accuracy of the functional diffusion map can be impaired by inaccurate segmentation thresholds and derives means for its optimization that will increase the fidelity of future clinical studies.

MRI of metastasis-permissive microenvironments

One of the earliest documented observations of the importance of the microenvironment in metastasis was made by Stephen Paget in 1889. More than a century later, the metastatic cascade remains a major cause of mortality from cancer. Cancer meets the criterion of a successful organization that is able to survive by adapting to changing environments. In fact, the tumor microenvironment and stroma are co-opted and shaped by cancer cells to derive a survival advantage. Cohesive strategies integrating advances in molecular biology and chemistry, with noninvasive multimodality imaging, provide new insights into the role of the tumor microenvironment in promoting metastasis from primary tumors as well as insights into environments that attract and permit cancer cells to establish colonies in distant organs. This article provides an overview of molecular and functional imaging characterization of microenvironments that can promote or permit cancer cells to metastasize and the microenvironmental characteristics of distant metastases.

Differential microstructure and physiology of brain and bone metastases in a rat breast cancer model by diffusion and dynamic contrast enhanced MRI

Pharmacological approaches to treat breast cancer metastases in the brain have been met with limited success. In part, the impermeability of the blood brain barrier (BBB) has hindered delivery of chemotherapeutic agents to metastatic tumors in the brain. BBB-permeable chemotherapeutic drugs are being developed, and noninvasively assessing the efficacy of these agents will be important in both preclinical and clinical settings. In this regard, dynamic contrast enhanced (DCE) and diffusion weighted imaging (DWI) are magnetic resonance imaging (MRI) techniques to monitor tumor vascular permeability and cellularity, respectively. In a rat model of metastatic breast cancer, we demonstrate that brain and bone metastases develop with distinct physiological characteristics as measured with MRI. Specifically, brain metastases have limited permeability of the BBB as assessed with DCE and an increased apparent diffusion coefficient (ADC) measured with DWI compared to the surrounding brain. Microscopically, brain metastases were highly infiltrative, grew through vessel co-option, and caused extensive edema and injury to the surrounding neurons and their dendrites. By comparison, metastases situated in the leptomenengies or in the bone had high vascular permeability and significantly lower ADC values suggestive of hypercellularity. On histological examination, tumors in the bone and leptomenengies were solid masses with distinct tumor margins. The different characteristics of these tissue sites highlight the influence of the microenvironment on metastatic tumor growth. In light of these results, the suitability of DWI and DCE to evaluate the response of chemotherapeutic and anti-angiogenic agents used to treat co-opted brain metastases, respectively, remains a formidable challenge.

Effect of Prostate Biopsy Hemorrhage on MRDW and MRS Imaging

Purpose

To retrospectively evaluate the effect of post-prostate-biopsy hemorrhage on the interpretation of magnetic resonance diffusion-weighted (MRDW) and magnetic resonance spectroscopic (MRS) imaging in the detection of prostate cancer. We also investigated the optimal timing for magnetic resonance examination after prostate biopsy.

Materials and Methods

We reviewed the records of 135 men. All patients underwent prostate magnetic resonance imaging (MRI). The prostate was divided into eight regions according to the biopsy site. Subsequently, we measured hemorrhage on apparent diffusion coefficient (ADC) values and (choline+creatinine)/citrate ([Cho+Cr]/Cit) ratios in the same regions on the MRI. We investigated the effect of hemorrhage at ADC values and (Cho+Cr)/Cit ratios on MRI and the relationship between prostate biopsy results and MRI findings.

Results

The mean patient age was 68.7 years and the mean time between biopsy and MRI was 23.5 days. The total hemorrhagic score demonstrated no significant associations with intervals from biopsy to MRI. Higher hemorrhagic scores were associated with higher ADC values, prostate cancer, and noncancer groups, respectively (p<0.001). ADC values were lower in tumors than in normal tissue (p<0.001), and ADC values were inversely correlated with tumor Gleason score in biopsy cores (p<0.001). However, (Cho+Cr)/Cit ratios did not exhibit any association with prostate biopsy results and hemorrhage.

Conclusions

Hemorrhage had no significant associations with the interval from biopsy to MRI. ADC values may help to detect prostate cancer and predict the aggressiveness of cancer; however, it is important to consider the bias effect of hemorrhage on the interpretation of MRDW imaging given that hemorrhage affects ADC values.

Applications of molecular imaging

Today molecular imaging technologies play a central role in clinical oncology. The use of imaging techniques in early cancer detection, treatment response, and new therapy development is steadily growing and has already significantly impacted on clinical management of cancer. In this chapter, we overview three different molecular imaging technologies used for the understanding of disease biomarkers, drug development, or monitoring therapeutic outcome. They are (1) optical imaging (bioluminescence and fluorescence imaging), (2) magnetic resonance imaging (MRI), and (3) nuclear imaging (e.g., single-photon emission computed tomography (SPECT) and positron emission tomography (PET)). We review the use of molecular reporters of biological processes (e.g., apoptosis and protein kinase activity) for high-throughput drug screening and new cancer therapies, diffusion MRI as a biomarker for early treatment response and PET and SPECT radioligands in oncology.

Applications of molecular MRI and optical imaging in cancer

Some of the most exciting advances in molecular-functional imaging of cancer are occurring at the interface between chemistry and imaging. Several of these advances have occurred through the development of novel imaging probes that report on molecular pathways, the tumor micro-environment and the response of tumors to treatment; as well as through novel image-guided platforms such as nanoparticles and nanovesicles that deliver therapeutic agents against specific targets and pathways. Cancer cells have a remarkable ability to evade destruction despite the armamentarium of drugs currently available. While these drugs can destroy cancer cells, normal tissue toxicity is a major limiting factor, a problem further compounded by poor drug delivery. One major challenge for chemistry continues to be to eliminate cancer cells without damaging normal tissues. Here we have selected examples of MRI and optical imaging, to demonstrate how integrating imaging with novel probes can facilitate the successful treatment of this multifaceted disease.

Comparison of diffusion-weighted MRI and MR volumetry in the evaluation of early treatment outcomes after preoperative chemoradiotherapy for locally advanced rectal cancer

PURPOSE

To compare diffusion-weighted imaging (DWI) and magnetic resonance (MR) volumetry for predicting treatment outcomes of locally advanced rectal cancers with preoperative chemoradiotherapy (CRT).

MATERIALS AND METHODS

This prospective study was approved by our Institutional Review Board. Thirty-four patients underwent three MR examinations: pre-CRT (before CRT), early CRT (2 weeks after CRT initiation), and post-CRT (before surgery). The tumor apparent diffusion coefficient (ADC), ADC increase rate, and volume reduction rate were compared between responders and nonresponders using three reference standards: downstaging, modified Response Evaluation Criteria in Solid Tumors (mRECIST), and tumor regression grade (TRG). For DWI and volumetry, differences between responders and nonresponders were assessed by receiver operating characteristic analysis.

RESULTS

The median early tumor volume reduction rate of responders, subgrouped by downstaging and mRECIST (47.97% and 53.97%, respectively), was significantly higher than that of nonresponders (20.94% and 20.36%; P = 0.0024 and 0.0001, respectively), but there were no significant differences in pre-CRT ADC and early ADC increase rate using all references. When using the downstaging and mRECIST, the diagnostic performance of early tumor volume reduction rate (Az = 0.81 and 0.94, respectively) was higher than that of pre-CRT ADC (Az = 0.55 and 0.62; P = 0.033 and 0.007) and early ADC increase rate (Az = 0.58 and 0.64; P = 0.055 and 0.01) for predicting the treatment outcome. For TRG, there were no significant differences between DWI and volumetry.

CONCLUSION

Early tumor volume reduction rate at the second week after CRT initiation may be a better indicator than DWI based on the mean ADC measurements for predicting CRT treatment outcome.

Assessing response in bone metastases in prostate cancer with diffusion weighted MRI

OBJECTIVES

To determine whether changes in ADC of bone metastases secondary to prostate carcinoma are significantly different in responders compared with progressors on chemotherapy.

METHODS

Twenty-six patients with known bone metastases secondary to prostate carcinoma underwent diffusion-weighted MRI of the lumbar spine and pelvis at baseline and 12 weeks following chemotherapy. RECIST assessment of staging CT and PSA taken at the same time points were used to classify patients as responders, progressors or stable. ADC (from b = 0,50,100,250,500,750 smm⁻²) and ADC(slow) (from b = 100,250,500,750 smm⁻²) were calculated for up to 5 lesions per patient.

RESULTS

Mean ADC/ADC(slow) in lesions from responders and progressors showed a significant increase. Although the majority of lesions demonstrated an ADC/ADC(slow) rise, some lesions in both responders and progressors demonstrated a fall in ADC beyond the limits of reproducibility.

CONCLUSIONS

Mean ADC is not an appropriate measure of response in bone metastases. The heterogeneity of changes in ADC is likely to be related to the composition of bone marrow with changes that have opposing effects on ADC.

Registration accuracy for MR images of the prostate using a subvolume based registration protocol

Background

In recent years, there has been a considerable research effort concerning the integration of magnetic resonance imaging (MRI) into the external radiotherapy workflow motivated by the superior soft tissue contrast as compared to computed tomography. Image registration is a necessary step in many applications, e.g. in patient positioning and therapy response assessment with repeated imaging. In this study, we investigate the dependence between the registration accuracy and the size of the registration volume for a subvolume based rigid registration protocol for MR images of the prostate.

Methods

Ten patients were imaged four times each over the course of radiotherapy treatment using a T2 weighted sequence. The images were registered to each other using a mean square distance metric and a step gradient optimizer for registration volumes of different sizes. The precision of the registrations was evaluated using the center of mass distance between the manually defined prostates in the registered images. The optimal size of the registration volume was determined by minimizing the standard deviation of these distances.

Results

We found that prostate position was most uncertain in the anterior-posterior (AP) direction using traditional full volume registration. The improvement in standard deviation of the mean center of mass distance between the prostate volumes using a registration volume optimized to the prostate was 3.9 mm (p < 0.001) in the AP direction. The optimum registration volume size was 0 mm margin added to the prostate gland as outlined in the first image series.

Conclusions

Repeated MR imaging of the prostate for therapy set-up or therapy assessment will both require high precision tissue registration. With a subvolume based registration the prostate registration uncertainty can be reduced down to the order of 1 mm (1 SD) compared to several millimeters for registration based on the whole pelvis.

Magnetic resonance in the era of molecular imaging of cancer

Magnetic resonance imaging (MRI) has played an important role in the diagnosis and management of cancer since it was first developed, but other modalities also continue to advance and provide complementary information on the status of tumors. In the future, there will be a major continuing role for noninvasive imaging in order to obtain information on the location and extent of cancer, as well as assessments of tissue characteristics that can monitor and predict treatment response and guide patient management. Developments are currently being undertaken that aim to provide improved imaging methods for the detection and evaluation of tumors, for identifying important characteristics of tumors such as the expression levels of cell surface receptors that may dictate what types of therapy will be effective and for evaluating their response to treatments. Molecular imaging techniques based mainly on radionuclide imaging can depict numerous, specific, cellular and molecular markers of disease and have unique potential to address important clinical and research challenges. In this review, we consider what continuing and evolving roles will be played by MRI in this era of molecular imaging. We discuss some of the challenges for MRI of detecting imaging agents that report on molecular events, but highlight also the ability of MRI to assess other features such as cell density, blood flow and metabolism which are not specific hallmarks of cancer but which reflect molecular changes. We discuss the future role of MRI in cancer and describe the use of selected quantitative imaging techniques for characterizing tumors that can be translated to clinical applications, particularly in the context of evaluating novel treatments.

Molecular imaging metrics to evaluate response to preclinical therapeutic regimens

Molecular imaging comprises a range of techniques, spanning not only several imaging modalities but also many disease states and organ sites. While advances in new technology platforms have enabled a deeper understanding of the cellular and molecular basis of malignancy, reliable non-invasive imaging metrics remain an important tool for both diagnostics and patient management. Furthermore, the non- invasive nature of molecular imaging can overcome shortcomings associated with traditional biological approaches and provide valuable information relevant to patient care. Integration of information from multiple imaging techniques has the potential to provide a more comprehensive understanding of specific tumor characteristics, tumor status, and treatment response.

Predicting and monitoring cancer treatment response with diffusion-weighted MRI

An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, nonimage based clinical outcome metrics include morphology, clinical, and laboratory parameters, however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pretreatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response.

Sorafenib tosylate and paclitaxel induce anti-angiogenic, anti-tumour and anti-resorptive effects in experimental breast cancer bone metastases

PURPOSE

In this study we investigated sorafenib tosylate and paclitaxel as single and combination therapies regarding their effects on tumour growth and vasculature as well as their potency to inhibit osteolysis in experimental breast cancer bone metastases.

EXPERIMENTAL DESIGN

Nude rats bearing breast cancer bone metastases were treated with sorafenib tosylate (7 mg/kg, n=11), paclitaxel (5mg/kg, n=11) or the combination of both (n=10) and were compared to untreated controls (n=11). In a longitudinal study, volumes of osteolyses and respective soft tissue tumours were measured in these groups by MRI and volume CT, while changes in cellularity within bone metastases were assessed by diffusion-weighted imaging. Dynamic contrast-enhanced MRI and vessel size imaging was performed to determine changes of tumour vasculature within osseous lesions non-invasively.

RESULTS

Animals treated with sorafenib tosylate or paclitaxel showed significantly reduced growth of both, the osteolytic lesions and the soft tissue tumours as well as a decreased cellularity in bone metastases compared to control rats. Effects on the tumour vasculature of these drugs included significantly reduced blood volume as well as significant changes of the vessel permeability and the mean vessel calibers. When combining sorafenib tosylate with paclitaxel for the treatment of bone metastases positive combination effects were observed, particularly on reducing vessel permeability in these lesions.

CONCLUSION

The application of sorafenib tosylate monotherapy or in combination with paclitaxel is effective against experimental breast cancer bone metastases resulting in anti-angiogenic, anti-tumour and anti-resorptive effects.

Drug-induced vessel remodeling in bone metastases as assessed by dynamic contrast enhanced magnetic resonance imaging and vessel size imaging: a longitudinal in vivo study

PURPOSE

The aim of this study was to assess the antiangiogenic treatment effects of zoledronic acid (ZA) and sunitinib malate (SM) noninvasively in experimental breast cancer bone metastases by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and vessel size imaging.

EXPERIMENTAL DESIGN

Nude rats bearing bone metastases after inoculation of MDA-MB-231 breast cancer cells were treated with ZA (40 microg/kg weekly; n = 8 rats), SM (20 mg/kg daily; n = 8 rats), or their combination (ZA and SM; n = 8 rats) and compared with sham-treated controls (n = 10 rats). Vascular changes in bone metastases were longitudinally imaged in vivo using DCE-MRI [amplitude (A) and exchange rate coefficient (k(ep))] and vessel size imaging [blood volume (BV) and vessel size index (VI)]. In addition, antiresorptive and antitumor changes were assessed in these lesions by flat-panel volumetric computed tomography as well as morphologic MRI and diffusion-weighted imaging.

RESULTS

In bone metastases, significant changes in A, k(ep), BV, and VI in accordance with decreased blood volume and vessel permeability as well as with increased mean vessel diameters were observed after application of ZA and SM as compared with controls. In this longitudinal study, antiangiogenic changes preceded the inhibition of osteolysis and antitumor effects after treatment.

CONCLUSIONS

These results indicate vessel remodeling in breast cancer bone metastases on ZA and SM treatment and implicate substantial effects on imaging and treatment of malignant bone lesions.

Evaluation of treatment-associated inflammatory response on diffusion-weighted magnetic resonance imaging and 2-[18F]-fluoro-2-deoxy-D-glucose-positron emission tomography imaging biomarkers

PURPOSE

Functional imaging biomarkers of cancer treatment response offer the potential for early determination of outcome through the assessment of biochemical, physiologic, and microenvironmental readouts. Cell death may result in an immunologic response, thus complicating the interpretation of biomarker readouts. This study evaluated the temporal effect of treatment-associated inflammatory activity on diffusion magnetic resonance imaging and 2-[(18)F]-fluoro-2-deoxy-D-glucose-positron emission tomography imaging (FDG-PET) biomarkers to delineate the effects of the inflammatory response on imaging readouts.

EXPERIMENTAL DESIGN

Rats with intracerebral 9L gliosarcomas were separated into four groups consisting of control, an immunosuppressive agent dexamethasone (Dex), 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU), and BCNU+Dex. Animals were imaged using diffusion-weighted magnetic resonance imaging and FDG-PET at 0, 3, and 7 days posttreatment.

RESULTS

In the BCNU- and BCNU+Dex-treated animal groups, diffusion values increased progressively over the 7-day study period to approximately 23% over baseline. The FDG percentage change of standard uptake value decreased at day 3 (-30.9%) but increased over baseline levels at day 7 (+20.1%). FDG-PET of BCNU+Dex-treated animals were found to have percentage of standard uptake value reductions of -31.4% and -24.7% at days 3 and 7, respectively, following treatment. Activated macrophages were observed on day 7 in the BCNU treatment group with much fewer found in the BCNU+Dex group.

CONCLUSIONS

Results revealed that treatment-associated inflammatory response following tumor therapy resulted in the accentuation of tumor diffusion response along with a corresponding increase in tumor FDG uptake due to the presence of glucose-consuming activated macrophages. The dynamics and magnitude of potential inflammatory response should be considered when interpreting imaging biomarker results.

Robust estimation of the apparent diffusion coefficient (ADC) in heterogeneous solid tumors

The least-squares algorithm is known to bias apparent diffusion coefficient (ADC) values estimated from magnitude MR data, although this effect is commonly assumed to be negligible. In this study the effect of this bias on tumor ADC estimates was evaluated in vivo and was shown to introduce a consistent and significant underestimation of ADC, relative to those given by a robust maximum likelihood approach (on average, a 23.4 +/- 12% underestimation). Monte Carlo simulations revealed that the magnitude of the bias increased with ADC and decreasing signal-to-noise ratio (SNR). In vivo, this resulted in a much-reduced ability to resolve necrotic regions from surrounding viable tumor tissue compared with a maximum likelihood approach. This has significant implications for the evaluation of diffusion MR data in vivo, in particular in heterogeneous tumor tissue, when evaluating bi- and multiexponential tumor diffusion models for the modeling of data acquired with larger b-values (b > 1000 s/mm(2)) and for data with modest SNR. Use of a robust approach to modeling magnitude MR data from tumors is therefore recommended over the least-squares approach when evaluating data from heterogeneous tumors.

Voxel-by-voxel functional diffusion mapping for early evaluation of breast cancer treatment

Quantitative isotropic diffusion MRI and voxel-based analysis of the apparent diffusion coefficient (ADC) changes have been demonstrated to be able to accurately predict early response of brain tumors to therapy. The ADC value changes measured during pre- and posttherapy interval are closely correlated to treatment response. This work was demonstrated using a voxel-based analysis of ADC change during therapy in the brains of both rats and humans, following rigidly registering pre- and post-therapeutic ADC MRI exams. The primary goal of this paper is to extend this voxel-by-voxel analysis to assess therapeutic response in breast cancer. Nonlinear registration (with higher degrees of freedom) between the pre- and post-treatment exams is needed to ensure that the corresponding voxels actually contain similar cellular partial contributions due to soft tissue deformations in the breast and compartmental tumor changes during treatment as well. With limited data sets, we have observed the correlation between changes of ADC values and treatment response also exists in breast cancers. With diffusion scans acquired at three different timepoints (pre-treatment, early post-treatment and late post-treatment), we have also shown that ADC changes across responders within 5 weeks are a function of time interval after the initiation of treatment. Comparison of the experimental results with pathology shows that ADC changes can be used to evaluate early response of breast cancer treatment.

Diffusion-weighted magnetic resonance imaging for predicting and detecting early response to chemoradiation therapy of squamous cell carcinomas of the head and neck

PURPOSE

The aim of this study was to investigate the utility of apparent diffusion coefficient (ADC) for prediction and early detection of treatment response in head and neck squamous cell carcinomas (HNSCC).

EXPERIMENTAL DESIGN

Diffusion-weighted magnetic resonance imaging studies were performed on 40 patients with newly diagnosed HNSCC before, during, and after the end of chemoradiation therapy. Analysis was done on data from 33 patients after exclusion of 7 patients that had incomplete data.

RESULTS

Pretreatment ADC value of complete responders (1.04 +/- 0.19 x 10(-3) mm2/s) was significantly lower (P < 0.05) than that from partial responders (1.35 +/- 0.30 x 10(-3) mm2/s). A significant increase in ADC was observed in complete responders within 1 week of treatment (P < 0.01), which remained high until the end of the treatment. The complete responders also showed significantly higher increase in ADC than the partial responders by the first week of chemoradiation (P < 0.01). When pretreatment ADC value was used for predicting treatment response, the area under the receiver operating characteristic curve was 0.80 with a sensitivity of 65% and a specificity of 86%. However, change in ADC within the first week of chemoradiation therapy resulted in an area under the receiver operating characteristic curve of 0.88 with 86% sensitivity and 83% specificity for prediction of treatment response.

CONCLUSIONS

These results suggest that ADC can be used as a marker for prediction and early detection of response to concurrent chemoradiation therapy in HNSCC.

Challenges in clinical prostate cancer: role of imaging

OBJECTIVE

This article reviews a recent 2-day workshop on prostate cancer and imaging technology that was conducted by the Cancer Imaging Program of the National Cancer Institute. The workshop dealt with research trends and avenues for improving imaging and applications across the clinical spectrum of the disease.

CONCLUSION

After a summary of prostate cancer incidence and mortality, four main clinical challenges in prostate cancer treatment and management-diagnostic accuracy; risk stratification, initial staging, active surveillance, and focal therapy; prostate-specific antigen relapse after radiation therapy or radical prostatectomy; and assessing response to therapy in advanced disease-were discussed by the 55-member panel. The overarching issue in prostate cancer is distinguishing lethal from nonlethal disease. New technologies and fresh uses for established procedures make imaging effective in both assessing and treating prostate cancer.

Imaging response to systemic therapy for bone metastases

In patients with osteotropic primary tumours such as breast and prostate cancer, imaging treatment response of bone metastases is essential for the clinical management. After treatment of skeletal metastases, morphological changes, in particular of bone structure, occur relatively late and are difficult to quantify using conventional X-rays, CT or MRI. Early treatment response in these lesions can be assessed from functional imaging techniques such as dynamic contrast-enhanced techniques by MRI or CT and by diffusion-weighted MRI, which are quantifiable. Among the techniques within nuclear medicine, PET offers the acquisition of quantifiable parameters for response evaluation. PET, therefore, especially in combination with CT and MRI using hybrid techniques, holds great promise for early and quantifiable assessment of treatment response in bone metastases. This review summarises the classification systems and the use of imaging techniques for evaluation of treatment response and suggests parameters for the early detection and quantification of response to systemic therapy.

Synergy between anti-CCL2 and docetaxel as determined by DW-MRI in a metastatic bone cancer model

Metastatic prostate cancer continues to be the second leading cause of cancer death in American men with an estimated 28,660 deaths in 2008. Recently, monocyte chemoattractant protein-1 (MCP-1, CCL2) has been identified as an important factor in the regulation of prostate metastasis. CCL2, shown to attract macrophages to the tumor site, has a direct promotional effect on tumor cell proliferation, migration, and survival. Previous studies have shown that anti-CCL2 antibodies given in combination with docetaxel were able to induce tumor regression in a pre-clinical prostate cancer model. A limitation for evaluating new treatments for metastatic prostate cancer to bone is the inability of imaging to objectively assess response to treatment. Diffusion-weighted MRI (DW-MRI) assesses response to anticancer therapies by quantifying the random (i.e., Brownian) motion of water molecules within the tumor mass, thus identifying cells undergoing apoptosis. We sought to measure the treatment response of prostate cancer in an osseous site to docetaxel, an anti-CCL2 agent, and combination treatments using DW-MRI. Measurements of tumor apparent diffusion coefficient (ADC) values were accomplished over time during a 14-day treatment period and compared to response as measured by bioluminescence imaging and survival studies. The diffusion data provided early predictive evidence of the most effective therapy, with survival data results correlating with the DW-MRI findings. DW-MRI is under active investigation in the pre-clinical and clinical settings to provide a sensitive and quantifiable means for early assessment of cancer treatment outcome.

The parametric response map is an imaging biomarker for early cancer treatment outcome

Here we describe the parametric response map (PRM), a voxel-wise approach for image analysis and quantification of hemodynamic alterations during treatment for 44 patients with high-grade glioma. Relative cerebral blood volume (rCBV) and flow (rCBF) maps were acquired before treatment and after 1 and 3 weeks of therapy. We compared the standard approach using region-of-interest analysis for change in rCBV or rCBF to the change in perfusion parameters on the basis of PRM (PRM(rCBV) and PRM(rCBF)) for their accuracy in predicting overall survival. Neither the percentage change of rCBV or rCBF predicted survival, whereas the regional response evaluations made on the basis of PRM were highly predictive of survival. Even when accounting for baseline rCBV, which is prognostic, PRM(rCBV) proved more predictive of overall survival.

Imaging anti-angiogenic treatment response with DCE-VCT, DCE-MRI and DWI in an animal model of breast cancer bone metastasis

As current classification systems for the assessment of treatment response in bone metastasis do not meet the needs of oncologists, new imaging biomarkers are desirable. Therefore, the diagnostic impact of dynamic contrast enhanced (DCE)-volumetric computed tomography (VCT) (descriptive analysis), DCE-MRI (two-compartment model) and diffusion weighted imaging (DWI) for monitoring anti-angiogenic therapy effects of the VEGF antibody bevacizumab in breast cancer bone metastases in rats was studied. Nude rats (n=8 animals treated with bevacizumab and n=9 untreated control rats) with site-specific osteolytic bone metastasis of the hind leg were imaged with a 1.5T clinical MRI-scanner in an animal coil as well as in a volumetric CT-scanner at days 30, 40, 50 and 60 after inoculation of MDA-MB-231 human breast cancer cells. From these data, osteolytic lesion size (OLS), peak enhancement (PE), area under the curve (AUC), amplitude (A), exchange rate constant (k(ep)) and apparent diffusion coefficient (ADC) were determined in bone metastases. Prior to changes in OLS (p< or =0.05 at days 50 and 60) there was already a significant decrease in PE, AUC and A (p< or =0.05 at days 40-60) in treated animals compared to controls. However, for k(ep) and ADC there were no significant differences between the groups at any time point (p>0.05 at days 40-60). In conclusion, anti-angiogenic treatment response in osteolytic breast cancer bone metastases can be assessed early with surrogate markers of vascularization, while DWI appears to be insensitive.

Correlation of diffusion-weighted magnetic resonance data with cellularity in prostate cancer

OBJECTIVE

To assess the relationship between the apparent diffusion coefficient (ADC) on magnetic resonance imaging (MRI) and cell density (CD) obtained from radical prostatectomy (RP) specimens.

PATIENTS AND METHODS

In all, 36 patients with prostate cancer were recruited; T2-weighted and diffusion-weighted MRI was obtained axially using a 3.0 T scanner. Patients then proceeded to RP; the prostate was whole-mounted and sectioned axially. Slices (3 microm) were cut from the surface of each section and stained with haematoxylin and eosin (H&E). Five randomly positioned areas from the tumour and normal peripheral zone (PZ) were examined by light microscopy at x 200, then digitally photographed and analysed to obtain automatic CD. ADC values were determined from the MRI data using the H&E slides as a reference. ADC and CD values were measured in both malignant lesions and the PZ, and the correlation between ADC and CD assessed.

RESULTS

ADC values were lower (P <or= 0.001) in regions pathologically determined as tumour, with a mean (sd) of 1.45 (0.26) x 10(-3) mm(2)/s, vs normal PZ, of 1.90 (0.33) x 10(-3) mm(2)/s. Similarly, the mean CD over the five fields was higher (P <or= 0.001) in tumour than in normal PZ, with values of 18.89 (4.93)% vs 9.22 (3.23)%. There was a significant correlation between the ADC values and CD (r = -0.50, P < 0.001) regardless of tissue type. CD values were high in cancer which had lower ADC values than normal PZ.

CONCLUSIONS

ADC values were correlated successfully with CD; this information cannot be obtained with conventional MRI and is useful in characterizing prostate cancer.

Functional diffusion map as an early imaging biomarker for high-grade glioma: correlation with conventional radiologic response and overall survival

PURPOSE

Assessment of radiologic response (RR) for brain tumors utilizes the Macdonald criteria 8 to 10 weeks from the start of treatment. Diffusion magnetic resonance imaging (MRI) using a functional diffusion map (fDM) may provide an earlier measure to predict patient survival.

PATIENTS AND METHODS

Sixty patients with high-grade glioma were enrolled onto a study of intratreatment MRI at 1, 3, and 10 weeks. Receiver operating characteristic curve analysis was used to evaluate imaging parameters as a function of patient survival at 1 year. Both log-rank and Cox proportional hazards models were utilized to assess overall survival.

RESULTS

Greater increases in diffusion in response to therapy over time were observed in those patients alive at 1 year compared with those who died as a result of disease. The volume of tumor with increased diffusion by fDM at 3 weeks was the strongest predictor of patient survival at 1 year, with larger fDM predicting longer median survival (52.6 v 10.9 months; log-rank, P < .003; hazard ratio [HR] = 2.7; 95% CI, 1.5 to 5.9). Radiologic response at 10 weeks had similar prognostic value (median survival, 31.6 v 10.9 months; log-rank P < .0007; HR = 2.9; 95% CI, 1.7 to 7.2). Radiologic response and fDM differed in 25% of cases. A composite index of response including fDM and RR provided a robust predictor of patient survival and may identify patients in whom RR does not correlate with clinical outcome.

CONCLUSION

Compared with conventional neuroimaging, fDM provided an earlier assessment of equal predictive value, and the combination of fDM and RR provided a more accurate prediction of patient survival than either metric alone.

Using extracellular biomarkers for monitoring efficacy of therapeutics in cancer patients: an update

Rapidly detectable and easily accessible markers of tumor cell death are needed for evaluating early therapeutic efficacy for immunotherapy and chemotherapy so that patients and their physicians can decide whether to remain with a given therapeutic strategy. Currently, image-based tests such as computed tomography scans and magnetic resonance imaging are used to visualize the response of a patient's tumor, but often these evaluations are not conducted for weeks to months after treatment begins. While serum levels of secreted proteins such as carcinoembryonic antigen and prostate specific antigen are commonly monitored to gauge tumor status during therapy and between image evaluations, the levels of these proteins do not always correlate well with the actual tumor response. In laboratory studies, it has been shown that tumor cells undergoing apoptosis can release cellular components into cell culture media such as cytochrome c, nucleosomes, cleaved cytokeratin-18 and E-cadherin. Studies of patient sera have found that these and other macromolecules can be found in circulation during cancer therapy, providing a potential source of material for monitoring treatment efficacy. In the future, analysis of biofluids from severe combined immunodeficiency mice bearing patient tumor specimens treated with a targeted therapy such as Apo2L/tumor necrosis factor-related apoptosis-inducing ligand will be useful in the preclinical identification of therapy response markers. In this review, the current status of the identification of serum markers of tumor cell apoptosis is provided, as well as a discussion of critical research questions that must be addressed and the considerations necessary when identifying a marker that reflects true clinical outcome.