A feasibility study of parametric response map analysis of diffusion-weighted magnetic resonance imaging scans of head and neck cancer patients for providing early detection of therapeutic efficacy

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.

Potential for Early Fracture Risk Assessment in Patients with Metastatic Bone Disease using Parametric Response Mapping of CT Images

Pathologic vertebral compression fractures (PVCFs) cause significant morbidity in patients with metastatic bone disease. Limitations in existing clinical biomarkers leave clinicians without reliable metrics for predicting PVCF, thus impeding efforts to prevent this severe complication. To establish the feasibility of a new method for defining the risk of a PVCF, we retrospectively analyzed serial computed tomography (CT) scans from 5 breast cancer patients using parametric response mapping (PRM) to quantify dynamic bone miniral density (BMD) changes that preceded an event. Vertebrae segmented from each scan were registered to the same spatial frame and voxel classification was accomplished using a predetermined threshold of change in Hounsfield units (HU), resulting in relative volumes of increased (PRM_HU+), decreased (PRM_HU−), or unchanged (PRM_HU0) attenuation. A total of 7 PVCFs were compared to undiseased vertebrae in each patient serving as controls. A receiver operator curve (ROC) analysis identified optimal imaging times for group stratification. BMD changes were apparent by an elevated PRM_HU+ as early as 1 year before fracture. ROC analysis showed poor performance of PRM_HU− in stratifying PVCFs versus controls. As early as 6 months before PVCF, PRM_HU+ was significantly larger (12.9 ± 11.6%) than control vertebrae (2.3 ± 2.5%), with an area under the curve of 0.918 from an ROC analysis. Mean HU changes were also significant between PVCF (26.8 ± 26.9%) and control (−2.2 ± 22.0%) over the same period. A PRM analysis of BMD changes using standard CT imaging was sensitive for spatially resolving changes that preceded structural failure in these patients.

Analysis and correction of gradient nonlinearity bias in apparent diffusion coefficient measurements

PURPOSE

Gradient nonlinearity of MRI systems leads to spatially dependent b-values and consequently high non-uniformity errors (10-20%) in apparent diffusion coefficient (ADC) measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements.

METHODS

All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations.

RESULTS

Spatial dependence of nonlinearity correction terms accounts for the bulk (75-95%) of ADC bias for FA = 0.3-0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems.

CONCLUSIONS

The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients.

Role of quantitative magnetic resonance imaging parameters in the evaluation of treatment response in malignant tumors

OBJECTIVE

To elaborate the role of quantitative magnetic resonance imaging (MRI) parameters in the evaluation of treatment response in malignant tumors.

DATA SOURCES

Data cited in this review were obtained mainly from PubMed in English from 1999 to 2014, with keywords "dynamic contrast-enhanced (DCE)-MRI," "diffusion-weighted imaging (DWI)," "microcirculation," "apparent diffusion coefficient (ADC)," "treatment response" and "oncology."

STUDY SELECTION

Articles regarding principles of DCE-MRI, principles of DWI, clinical applications as well as opportunity and aspiration were identified, retrieved and reviewed.

RESULTS

A significant correlation between ADC values and treatment response was reported in most DWI studies. Most quantitative DCE-MRI studies showed a significant correlation between K trans values and treatment response. However, in different tumors and studies, both high and low pretreatment ADC or K trans values were found to be associated with response rate. Both DCE-MRI and DWI demonstrated changes in their parameters hours to days after treatment, showing a decrease in K trans or an increase in ADC associated with response in most cases.

CONCLUSIONS

Combinations of quantitative MRI play an important role in the evaluation of treatment response of malignant tumors and hold promise for use as a cancer treatment response biomarker. However, validation is hampered by the lack of reproducibility and standardization. MRI acquisition protocols and quantitative image analysis approaches should be properly addressed prior to further testing the clinical use of quantitative MRI parameters in the assessment of treatments.

Practical estimate of gradient nonlinearity for implementation of apparent diffusion coefficient bias correction

PURPOSE

To describe an efficient procedure to empirically characterize gradient nonlinearity and correct for the corresponding apparent diffusion coefficient (ADC) bias on a clinical magnetic resonance imaging (MRI) scanner.

MATERIALS AND METHODS

Spatial nonlinearity scalars for individual gradient coils along superior and right directions were estimated via diffusion measurements of an isotropicic e-water phantom. Digital nonlinearity model from an independent scanner, described in the literature, was rescaled by system-specific scalars to approximate 3D bias correction maps. Correction efficacy was assessed by comparison to unbiased ADC values measured at isocenter.

RESULTS

Empirically estimated nonlinearity scalars were confirmed by geometric distortion measurements of a regular grid phantom. The applied nonlinearity correction for arbitrarily oriented diffusion gradients reduced ADC bias from 20% down to 2% at clinically relevant offsets both for isotropic and anisotropic media. Identical performance was achieved using either corrected diffusion-weighted imaging (DWI) intensities or corrected b-values for each direction in brain and ice-water. Direction-average trace image correction was adequate only for isotropic medium.

CONCLUSION

Empiric scalar adjustment of an independent gradient nonlinearity model adequately described DWI bias for a clinical scanner. Observed efficiency of implemented ADC bias correction quantitatively agreed with previous theoretical predictions and numerical simulations. The described procedure provides an independent benchmark for nonlinearity bias correction of clinical MRI scanners.

Prospective, longitudinal, multi-modal functional imaging for radical chemo-IMRT treatment of locally advanced head and neck cancer: the INSIGHT study

BACKGROUND

Radical chemo-radiotherapy (CRT) is an effective organ-sparing treatment option for patients with locally advanced head and neck cancer (LAHNC). Despite advances in treatment for LAHNC, a significant minority of these patients continue to fail to achieve complete response with standard CRT. By constructing a multi-modality functional imaging (FI) predictive biomarker for CRT outcome for patients with LAHNC we hope to be able to reliably identify those patients at high risk of failing standard CRT. Such a biomarker would in future enable CRT to be tailored to the specific biological characteristics of each patients' tumour, potentially leading to improved treatment outcomes.

METHODS/DESIGN

The INSIGHT study is a single-centre, prospective, longitudinal multi-modality imaging study using functional MRI and FDG-PET/CT for patients with LAHNC squamous cell carcinomas receiving radical CRT. Two cohorts of patients are being recruited: one treated with, and another treated without, induction chemotherapy. All patients receive radical intensity modulated radiotherapy with concurrent chemotherapy. Patients undergo functional imaging before, during and 3 months after completion of radiotherapy, as well as at the time of relapse, should that occur within the first two years after treatment. Serum samples are collected from patients at the same time points as the FI scans for analysis of a panel of serum markers of tumour hypoxia.

DISCUSSION

The primary aim of the INSIGHT study is to acquire a prospective multi-parametric longitudinal data set comprising functional MRI, FDG PET/CT, and serum biomarker data from patients with LAHNC undergoing primary radical CRT. This data set will be used to construct a predictive imaging biomarker for outcome after CRT for LAHNC. This predictive imaging biomarker will be used in future studies of functional imaging based treatment stratification for patients with LAHNC. Additional objectives are: defining the reproducibility of FI parameters; determining robust methods for defining FI based biological target volumes for IMRT planning; creation of a searchable database of functional imaging data for data mining. The INSIGHT study will help to establish the role of FI in the clinical management of LAHNC.

TRIAL REGISTRATION

NCRI H&N CSG ID 13860.

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.

Feasibility analysis of the parametric response map as an early predictor of treatment efficacy in head and neck cancer

BACKGROUND AND PURPOSE

Estimating changes in the volume transfer constant, normalized area under the contrast-enhancement time curve at 60 seconds, and fractional blood plasma volume by using dynamic contrast-enhanced MR imaging may be useful in predicting tumor response to chemoradiation. We hypothesized that the parametric response map, a voxel-by-voxel analysis of quantitative dynamic contrast-enhanced MR imaging maps, predicts survival in patients with head and neck cancer.

MATERIALS AND METHODS

Ten patients with locoregionally advanced head and neck squamous cell carcinoma underwent definitive concurrent chemoradiation therapy. For each patient, dynamic contrast-enhanced MR imaging data were collected before and 2 weeks after treatment initiation. Change in perfusion parameters within the primary tumor volume with time was analyzed by parametric response mapping and by whole-tumor mean percentage change. Outcome was defined as overall survival. The perfusion parameter and metric most predictive of outcome were identified. Overall survival was estimated by the log-rank test and Kaplan-Meier survival curve.

RESULTS

The volume transfer constant and normalized area under the contrast-enhancement time curve at 60 seconds were predictive of survival both in parametric response map analysis (volume transfer constant, P = .002; normalized area under the contrast-enhancement time curve at 60 seconds, P = .02) and in the percentage change analysis (volume transfer constant, P = .04; normalized area under the contrast-enhancement time curve at 60 seconds, P = .02). Blood plasma volume predicted survival in neither analysis.

CONCLUSIONS

Parametric response mapping of MR perfusion biomarkers could potentially guide treatment modification in patients with predicted treatment failure. Larger studies are needed to determine whether parametric response map analysis or percentage signal change in these perfusion parameters is the stronger predictor of survival.

Multimodality functional imaging in radiation therapy planning: relationships between dynamic contrast-enhanced MRI, diffusion-weighted MRI, and 18F-FDG PET

OBJECTIVES

Biologically guided radiotherapy needs an understanding of how different functional imaging techniques interact and link together. We analyse three functional imaging techniques that can be useful tools for achieving this objective.

MATERIALS AND METHODS

The three different imaging modalities from one selected patient are ADC maps, DCE-MRI, and 18F-FDG PET/CT, because they are widely used and give a great amount of complementary information. We show the relationship between these three datasets and evaluate them as markers for tumour response or hypoxia marker. Thus, vascularization measured using DCE-MRI parameters can determine tumour hypoxia, and ADC maps can be used for evaluating tumour response.

RESULTS

ADC and DCE-MRI include information from 18F-FDG, as glucose metabolism is associated with hypoxia and tumour cell density, although 18F-FDG includes more information about the malignancy of the tumour. The main disadvantage of ADC maps is the distortion, and we used only low distorted regions, and extracellular volume calculated from DCE-MRI can be considered equivalent to ADC in well-vascularized areas.

CONCLUSION

A dataset for achieving the biologically guided radiotherapy must include a tumour density study and a hypoxia marker. This information can be achieved using only MRI data or only PET/CT studies or mixing both datasets.

Parametric response mapping of dynamic CT as an imaging biomarker to distinguish viability of hepatocellular carcinoma treated with transcatheter arterial chemoembolization

PURPOSE

Accurate assessment of viability of hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE) is important for therapy planning. The purpose of this study is to determine the diagnostic value of a novel image analysis method called parametric response mapping (PRM) in predicting viability of tumor in HCC treated with TACE for dynamic CT images.

METHODS

35 patients who had 35 iodized-oil defect areas (IODAs) in HCCs treated with TACE were included in our study. These patients were divided into two groups, one group with viable tumors (n = 22) and the other group with non-viable tumors (n = 13) in the IODA. All patients were followed up using triple-phase dynamic CT after the treatment. We compared (a) manual analysis, (b) using PRM results, and (c) using PRM results with automatic classifier to distinguish between two tumor groups based on dynamic CT images from two longitudinal exams. Two radiologists performed the manual analysis. The PRM approach was implemented using prototype software. We adopted an off-the-shelf k nearest neighbor (kNN) classifier and leave-one-out cross-validation for the third approach. The area under the curve (AUC) values were compared for three approaches.

RESULTS

Manual analysis yielded AUC of 0.74, using PRM results yielded AUC of 0.84, and using PRM results with an automatic classifier yielded AUC of 0.87.

CONCLUSIONS

We improved upon the standard manual analysis approach by adopting a novel image analysis method of PRM combined with an automatic classifier.

Clinical applications for diffusion magnetic resonance imaging in radiotherapy

In this article, we review the clinical applications of diffusion magnetic resonance imaging (MRI) in the radiotherapy treatment of several key clinical sites, including those of the central nervous system, the head and neck, the prostate, and the cervix. Diffusion-weighted MRI (DWI) is an imaging technique that is rapidly gaining widespread acceptance owing to its ease and wide availability. DWI measures the mobility of water within tissue at the cellular level without the need of any exogenous contrast agent. For radiotherapy treatment planning, DWI improves upon conventional imaging techniques, by better characterization of tumor tissue properties required for tumor grading, diagnosis, and target volume delineation. Because DWI is also a sensitive marker for alterations in tumor cellularity, it has potential clinical applications in the early assessment of treatment response following radiation therapy.

Diffusion-weighted EPI- and HASTE-MRI and 18F-FDG-PET-CT early during chemoradiotherapy in advanced head and neck cancer

MAIN PROBLEM

Diffusion-weighted MRI (DW-MRI) has potential to predict chemoradiotherapy (CRT) response in head and neck squamous cell carcinoma (HNSCC) and is generally performed using echo-planar imaging (EPI). However, EPI-DWI is susceptible to geometric distortions. Half-fourier acquisition single-shot turbo spin-echo (HASTE)-DWI may be an alternative. This prospective pilot study evaluates the potential predictive value of EPI- and HASTE-DWI and 18F-fluorodeoxyglucose PET-CT (18F-FDG-PET-CT) early during CRT for locoregional outcome in HNSCC.

METHODS

Eight patients with advanced HNSCC (7 primary tumors and 25 nodal metastases) scheduled for CRT, underwent DW-MRI (using both EPI- and HASTE-DWI) and 18F-FDG-PET(-CT) pretreatment, early during treatment and three months after treatment. Median follow-up time was 38 months.

RESULTS

No local recurrences were detected during follow-up. Median Apparent Diffusion Coefficient (ADC)EPI-values in primary tumors increased from 77×10(-5) mm(2)/s pretreatment, to 113×10(-5) mm(2)/s during treatment (P=0.02), whereas ADCHASTE did not increase (74 and 74 mm(2)/s, respectively). Two regional recurrences were diagnosed. During treatment, ADCEPI tended to be higher for patients with regional control [(117.3±12.1)×10(-5) mm(2)/s] than for patients with a recurrence [(98.0±4.2)×10(-5) mm(2)/s]. This difference was not seen with ADCHASTE. No correlations between ΔADCEPI and ΔSUV (Standardized Uptake Value) were found in the primary tumor or nodal metastases.

CONCLUSIONS

HASTE-DWI seems to be inadequate in early CRT response prediction, compared to EPI-DWI which has potential to predict locoregional outcome. EPI-DWI and 18F-FDG-PET-CT potentially provide independent information in the early response to treatment, since no correlations were found between ΔADCEPI and ΔSUV.

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.

Non-Gaussian analysis of diffusion weighted imaging in head and neck at 3T: a pilot study in patients with nasopharyngeal carcinoma

PURPOSE

To technically investigate the non-Gaussian diffusion of head and neck diffusion weighted imaging (DWI) at 3 Tesla and compare advanced non-Gaussian diffusion models, including diffusion kurtosis imaging (DKI), stretched-exponential model (SEM), intravoxel incoherent motion (IVIM) and statistical model in the patients with nasopharyngeal carcinoma (NPC).

MATERIALS AND METHODS

After ethics approval was granted, 16 patients with NPC were examined using DWI performed at 3T employing an extended b-value range from 0 to 1500 s/mm(2). DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models on primary tumor, metastatic node, spinal cord and muscle. Non-Gaussian parameter maps were generated and compared to apparent diffusion coefficient (ADC) maps in NPC.

RESULTS

Diffusion in NPC exhibited non-Gaussian behavior at the extended b-value range. Non-Gaussian models achieved significantly better fitting of DWI signal than the mono-exponential model. Non-Gaussian diffusion coefficients were substantially different from mono-exponential ADC both in magnitude and histogram distribution.

CONCLUSION

Non-Gaussian diffusivity in head and neck tissues and NPC lesions could be assessed by using non-Gaussian diffusion models. Non-Gaussian DWI analysis may reveal additional tissue properties beyond ADC and holds potentials to be used as a complementary tool for NPC characterization.

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.

Redefining the target early during treatment. Can we visualize regional differences within the target volume using sequential diffusion weighted MRI?

PURPOSE

In head and neck cancer, diffusion weighted MRI (DWI) can predict response early during treatment. Treatment-induced changes and DWI-specific artifacts hinder an accurate registration between apparent diffusion coefficient (ADC) maps. The aim of the study was to develop a registration tool which calculates and visualizes regional changes in ADC.

METHODS

Twenty patients with stage IV HNC treated with primary radiotherapy received an MRI including DWI before and early during treatment. Markers were manually placed at anatomical landmarks on the different modalities at both time points. A registration method, consisting of a fully automatic rigid and nonrigid registration and two semi-automatic thin-plate spline (TPS) warps was developed and applied to the image sets. After each registration step the mean registration errors were calculated and ΔADC was compared between good and poor responders.

RESULTS

Adding the TPS warps significantly reduced the registration error (in mm, 6.3 ± 6.2 vs 3.2 ± 3.3 mm, p<0.001). After the marker based registration the median ΔADC in poor responders was significantly lower than in good responders (7% vs. 21%; p<0.001).

CONCLUSIONS

This registration method allowed for a significant reduction of the mean registration error. Furthermore the voxel-wise calculation of the ΔADC early during radiotherapy allowed for a visualization of the regional differences of ΔADC within the tumor.

Diffusion weighted MRI in head-and-neck cancer: geometrical accuracy

INTRODUCTION

The aim of this study is to assess the geometric accuracy of diffusion weighted (DW)-MRI by quantification of geometric distortions in the gross tumor volume (GTV) in head and neck (HN) cancer.

MATERIALS & METHODS

A retrospective analysis was performed on the data of 23 patients (with 24 lesions). For these patients, magnetic field maps and DW-MRI were acquired. The magnetic field maps were converted to voxel displacement maps. GTV delineations were transferred onto these voxel displacement maps and the voxel shifts in the GTV were analyzed.

RESULTS

The median shift was 3.2mm and the maximal posterior and anterior shifts were up to 15.0 and 26.0mm respectively. The range of shifts varied from 11.8 to 25.6mm. The percentage of GTV voxels that showed a shift of at least 6mm was found to be 23.2%.

CONCLUSIONS

Current DW-MRI images of HN tumors show severe distortions up to centimeters, which restrict the use of DW-MRI scans for GTV definition in RT treatment planning.

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.

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.

Changes in functional imaging parameters following induction chemotherapy have important implications for individualised patient-based treatment regimens for advanced head and neck cancer

BACKGROUND

When induction chemotherapy (IC) is used prior to chemoradiotherapy (CRT) in head and neck cancer (HNC), functional imaging (FI) may inform adaptation of treatment plans with the aim of optimising outcomes. Understanding the impact of IC on FI parameters is, therefore, essential.

PURPOSE

To prospectively evaluate the feasibility of acquiring serial FI ((18)F-FDG-PET, diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI) and its role in defining individualised treatment regimens following IC in HNC.

METHODS AND MATERIALS

Ten patients with stage III and IV HNC underwent conventional (CT and MRI) and functional (DW, DCE-MRI and (18)F-FDG-PET/CT) imaging at baseline and following two cycles of IC prior to definitive CRT.

RESULTS

One patient withdrew due to claustrophobia. Seven out of nine patients had a complete metabolic response to IC on (18)F-FDG-PET imaging. DCE-MRI showed a significant fall in transfer constant (K(trans)) (0.209 vs 0.129 min(-1)P<0.01) and integrated area under gadolinium curve at 60s (IAUGC6O) (18.4 vs 11.9 mmol/min, P<0.01) and DW-MRI a rise in ADC (0.89 vs 1.06 × 10(-3) mm(2)/s, P<0.01) following IC.

CONCLUSIONS

Acquiring FI sequences is feasible in HNC. There are marked changes in FI parameters following IC which may guide adaptation of individualised treatment regimens.

Neuroradiology back to the future: head and neck imaging

SUMMARY

Imaging of the head and neck was initially described within the first year after Roentgen's discovery of the x-ray and was used to localize foreign bodies in the head and neck area, including the orbital, laryngeal, and esophageal regions. Subsequently, x-rays were used to evaluate the air-filled paranasal sinuses, the pneumatized temporal bone, and the upper aerodigestive tract. Special views for evaluating these structures were developed by early investigators. As contrast agents were developed, a variety of invasive procedures were developed to assess the structures of the head and neck. CT and MR imaging were applied to the extracranial head and neck slightly later than the brain and spine; these modalities revolutionized head and neck radiology, finally allowing assessment of the deeper structures of this complex anatomic region.

Head and neck squamous cell carcinoma: diagnostic performance of diffusion-weighted MR imaging for the prediction of treatment response

PURPOSE

To determine the diagnostic performance of diffusion-weighted (DW) imaging for the prediction of treatment failure in primary head and neck squamous cell carcinoma (HNSCC).

MATERIALS AND METHODS

The study was approved by the local institutional ethics committee and conducted with informed written consent in patients with primary HNSCC treated with radiation therapy and chemotherapy. DW imaging of the primary tumor was performed before treatment in 37 patients and was repeated within 2 weeks of treatment in 30 patients. Histograms of apparent diffusion coefficients (ADCs) were analyzed, and mean ADC, kurtosis, skewness, and their respective percentage change were correlated for local failure and local control at 2 years by using the Student t test. Univariate and multivariate analyses of the ADC parameters, T stage, and tumor volume were performed by using logistic regression for prediction of local failure.

RESULTS

Local failure occurred in 16 of 37 (43%) patients and local control occurred in 21 of 37 (57%) patients. Pretreatment ADC parameters showed no correlation with local failure. There was significant intratreatment increase in mean ADC and a decrease in skewness and kurtosis (P < .001, P < .001, P = .024, respectively) for the whole group of patients when compared with those before treatment. During treatment, primary tumors showed a significantly lower increase in percentage change of mean ADC, higher skewness, and higher kurtosis for local failure than for local control (P = .016, .015, and .040, respectively). These ADC parameters also were significant for predicting local failure with use of univariate but not multivariate analysis.

CONCLUSION

Early intratreatment DW imaging has the potential to allow prediction of treatment response at the primary site in patients with HNSCC.

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.

Therapy response with diffusion MRI: an update

The efficiency of an oncological treatment regimen is often assessed by morphological criteria such as tumour size evaluated by cross-sectional imaging, or by laboratory measurements of plasma biomarkers. Because these types of measures typically allow for assessment of treatment response several weeks or even months after the start of therapy, earlier response assessment that provides insight into tumour function is needed. This is particularly urgent for the evaluation of newer targeted therapies and for fractionated therapies that are delivered over a period of weeks to allow for a change of treatment in non-responding patients. Diffusion-weighted MRI (DW-MRI) is a non-invasive imaging tool that does not involve radiation or contrast media, and is sensitive to tissue microstructure and function on a cellular level. DW-MRI parameters have shown sensitivity to treatment response in a growing number of tumour types and organ sites, with additional potential as predictive parameters for treatment outcome. A brief overview of DW-MRI principles is provided here, followed by a review of recent literature in which DW-MRI has been used to monitor and predict tumour response to various therapeutic regimens.

Multi-system repeatability and reproducibility of apparent diffusion coefficient measurement using an ice-water phantom

PURPOSE

To determine quantitative quality control procedures to evaluate technical variability in multi-center measurements of the diffusion coefficient of water as a prerequisite to use of the biomarker apparent diffusion coefficient (ADC) in multi-center clinical trials.

MATERIALS AND METHODS

A uniform data acquisition protocol was developed and shared with 18 participating test sites along with a temperature-controlled diffusion phantom delivered to each site. Usable diffusion weighted imaging data of ice water at five b-values were collected on 35 clinical MRI systems from three vendors at two field strengths (1.5 and 3 Tesla [T]) and analyzed at a central processing site.

RESULTS

Standard deviation of bore-center ADCs measured across 35 scanners was <2%; error range: -2% to +5% from literature value. Day-to-day repeatability of the measurements was within 4.5%. Intra-exam repeatability at the phantom center was within 1%. Excluding one outlier, inter-site reproducibility of ADC at magnet isocenter was within 3%, although variability increased for off-center measurements. Significant (>10%) vendor-specific and system-specific spatial nonuniformity ADC bias was detected for the off-center measurement that was consistent with gradient nonlinearity.

CONCLUSION

Standardization of DWI protocol has improved reproducibility of ADC measurements and allowed identifying spatial ADC nonuniformity as a source of error in multi-site clinical studies.

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.

Diffusion-weighted MR imaging in the head and neck

Extracranial applications of diffusion-weighted (DW) magnetic resonance (MR) imaging are gaining increasing importance, including in head and neck radiology. The main indications for performing DW imaging in this relatively small but challenging region of the body are tissue characterization, nodal staging, therapy monitoring, and early detection of treatment failure by differentiating recurrence from posttherapeutic changes. Lower apparent diffusion coefficients (ADCs) have been reported in the head and neck region of adults and children for most malignant lesions, as compared with ADCs of benign lesions. For nodal staging, DW imaging has shown promise in helping detect lymph node metastases, even in small (subcentimeter) nodes with lower ADCs, as compared with normal or reactive nodes. Follow-up of early response to treatment is reflected in an ADC increase in the primary tumor and nodal metastases; whereas nonresponding lesions tend to reveal only a slight increase or even a decrease in ADC during follow-up. Optimization and standardization of DW imaging technical parameters, comparison of DW images with morphologic images, and increasing experience, however, are prerequisites for successful application of this challenging technique in the evaluation of various head and neck pathologic conditions.

Boron neutron capture therapy (BNCT) in Finland: technological and physical prospects after 20 years of experiences

Boron Neutron Capture Therapy (BNCT) is a binary radiotherapy method developed to treat patients with certain malignant tumours. To date, over 300 treatments have been carried out at the Finnish BNCT facility in various on-going and past clinical trials. In this technical review, we discuss our research work in the field of medical physics to form the groundwork for the Finnish BNCT patient treatments, as well as the possibilities to further develop and optimize the method in the future. Accordingly, the following aspects are described: neutron sources, beam dosimetry, treatment planning, boron imaging and determination, and finally the possibilities to detect the efficacy and effects of BNCT on patients.

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.

Utility of pretreatment mean apparent diffusion coefficient and apparent diffusion coefficient histograms in prediction of outcome to chemoradiation in head and neck squamous cell carcinoma

PURPOSE

This study aimed to evaluate pretreatment whole-tumor mean apparent diffusion coefficient (ADC) and ADC histogram as predictors of outcome to chemoradiation in patients with head and neck squamous cell carcinoma (HNSCC).

MATERIALS AND METHODS

Patients with HNSCC underwent pretreatment 3-T diffusion-weighted magnetic resonance imaging with calculation of mean ADC and ADC histograms. Outcomes were determined 2 years after chemoradiation. Positive outcome was defined as no abnormal 18-fluoro deoxy glucose uptake on posttherapy computed tomography-positron emission tomography (or abnormal uptake that was proven benign), no locoregional recurrence or metastatic disease, and no requirement for salvage surgery. Negative outcome was defined as residual abnormal 18-fluoro deoxy glucose avidity that was proven malignant, salvage surgery requirement, locoregional recurrence or metastatic disease, death, or a combination of these. A 2-sample t test was used to compare the mean ADC between patients with positive and negative outcomes. The ADC cut point for dividing the groups was determined by looking at its distribution. A Kaplan-Meier plot was produced, and a log-rank test was conducted with calculation of sensitivity, specificity, and positive and negative predictive values.

RESULTS

Nine patients showed positive and 8 showed negative outcomes. Significant difference (P = 0.03) was seen in mean ADC (in 10 mm/s) between patients showing positive and negative outcomes (1.18 and 1.43, respectively). According to the log-rank test, tumors with greater than 45% of their volume below the ADC threshold of 1.15 × 10 mm/s were more likely to have a positive outcome (accuracy, 77%).

CONCLUSIONS

Patients with HNSCC demonstrating lower pretreatment ADC and with greater than 45% of volume below ADC threshold of 1.15 × 10 mm/s may have better outcome to chemoradiation at 2 years.

Diffusion coefficient measurement using a temperature-controlled fluid for quality control in multicenter studies

PURPOSE

To present the use of a quality control ice-water phantom for diffusion-weighted magnetic resonance imaging (DW-MRI). DW-MRI has emerged as an important cancer imaging biomarker candidate for diagnosis and early treatment response assessment. Validating imaging biomarkers through multicenter trials requires calibration and performance testing across sites.

MATERIALS AND METHODS

The phantom consisted of a center tube filled with distilled water surrounded by ice water. Following preparation of the phantom, ≈30 minutes was allowed to reach thermal equilibrium. DW-MRI data were collected at seven institutions, 20 MRI scanners from three vendors, and two field strengths (1.5 and 3T). The phantom was also scanned on a single system on 16 different days over a 25-day period. All data were transferred to a central processing site at the University of Michigan for analysis.

RESULTS

Results revealed that the variation of measured apparent diffusion coefficient (ADC) values between all systems tested was ±5%, indicating excellent agreement between systems. Reproducibility of a single system over a 25-day period was also found to be within ±5% ADC values. Overall, the use of an ice-water phantom for assessment of ADC was found to be a reasonable candidate for use in multicenter trials.

CONCLUSION

The ice-water phantom described here is a practical and universal approach to validate the accuracy of ADC measurements with ever changing MRI sequence and hardware design and can be readily implemented in multicenter clinical trial designs.

Functional imaging: what evidence is there for its utility in clinical trials of targeted therapies?

Key issues in early clinical trials of targeted agents include the determination of target inhibition, rational patient selection based on pre-treatment tumour characteristics, and assessment of tumour response in the absence of actual shrinkage. There is accumulating evidence that functional imaging using advanced techniques such as dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI), DCE-computerised tomography (CT) and DCE-ultrasound, diffusion weighted-MRI, magnetic resonance spectroscopy and positron emission tomography-CT using various labelled radioactive tracers has the potential to address all three. This article reviews this evidence with examples from trials using targeted agents with established clinical efficacy and summarises the clinical utility of the various techniques. We therefore recommend that input from specialist radiologists is sought at the early stages of trial design, in order to ensure that functional imaging is incorporated appropriately for the agent under study. There is an urgent need to strengthen the evidence base for these techniques as they evolve, and to ensure standardisation of the methodology.

Whole-body diffusion-weighted MR imaging in cancer: current status and research directions

Diffusion-weighted (DW) magnetic resonance (MR) imaging is emerging as a powerful clinical tool for directing the care of patients with cancer. Whole-body DW imaging is almost at the stage where it can enter widespread clinical investigations, because the technology is stable and protocols can be implemented for the majority of modern MR imaging systems. There is a continued need for further improvements in data acquisition and analysis and in display technologies. Priority areas for clinical research include clarification of histologic relationships between tissues of interest and DW MR imaging biomarkers at diagnosis and during therapy response. Because whole-body DW imaging excels at bone marrow assessments at diagnosis and for therapy response, it can potentially address a number of unmet clinical and pharmaceutical requirements. There are compelling needs to document and understand how common and novel treatments affect whole-body DW imaging results and to establish response criteria that can be tested in prospective clinical studies that incorporate measures of patient benefit.

Apparent diffusion coefficient from magnetic resonance imaging as a biomarker in oncology drug development

Magnetic resonance imaging (MRI) can be made sensitive to diffusion of water molecules in biological tissues: this phenomenon can be quantitated to provide a biomarker, the apparent diffusion coefficient (ADC). Over the past decade, evidence has accumulated from numerous clinical and animal studies that ADC is abnormal in tumours; that elevated ADC reflects an elevated non-cellular fraction; and that acute increases in ADC following therapy can indicate that tumour cells have been killed. However there remain substantial challenges in ensuring robust and valid ADC measurements, particularly in multicentre studies in common sites of metastasis such as lung and liver. Moreover, there is uncertainty about how best to select the timing of observation post-therapy to avoid false-negatives, and how to minimise the confounding factors which could decouple drug-induced ADC increase from drug-induced cell kill. In this review we summarise the physical basis of the biomarker, the evidence that it reflects non-viable fraction, particularly in extracranial tumours, and suggest a roadmap for validation and qualification.

Biologic imaging of head and neck cancer: the present and the future

While anatomic imaging (CT and MR imaging) of HNC is focused on diagnosing and/or characterizing the disease, defining its local extent, and evaluating distant spread, accurate assessment of the biologic status of the cancer (cellularity, growth rate, response to nonsurgical chemoradiation therapy, and so forth) can be invaluable for prognostication, planning therapy, and follow-up of lesions after therapy. The combination of anatomic and biologic imaging techniques can thus provide a more comprehensive evaluation of the patient. The purpose of this work was to review the present and future clinical applications of advanced biologic imaging techniques in HNC evaluation and management. As part of the biologic imaging array, we discuss MR spectroscopy, diffusion and perfusion MR imaging, CTP, and FDG-PET scanning and conclude with exciting developments that hold promise in assessment of tumor hypoxia and neoangiogenesis.

Head and neck cancer as a model for advances in imaging prognosis, early assessment, and posttherapy evaluation

Novel noninvasive functional imaging methods are necessary to predict therapeutic outcome and thereby improve the ability to properly select patients for treatment with both conventional and targeted therapies, to better evaluate therapeutic effectiveness during the early phases of treatment, and to enhance a priori risk assessment for treatment induced toxicity. Functional metabolic imaging typically involves pretreatment baseline magnetic resonance imaging (MRI) and/or positron emission tomographic (PET) scans and performance of subsequent scans during and/or after treatment. Imaging parameter changes are routinely attributed to the intervening therapy and clinical outcomes subsequently correlated with these changes. The physiologic parameter(s) that best correlate with clinical outcome and the relative utility of MRI versus PET are unknown, however. Furthermore, tumor vascular physiology and metabolic parameters are heterogeneous and dynamic processes. Large daily fluctuations often occur in the absence of treatment. The magnitude of this temporal variability is not established for MRI or for PET. Routine and meaningful clinical application of functional imaging requires understanding and quantification of the intrinsic variability of the underlying biologic processes and a demonstration that treatment-induced changes exceed intrinsic temporal variation.

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.

Prospective analysis of parametric response map-derived MRI biomarkers: identification of early and distinct glioma response patterns not predicted by standard radiographic assessment

PURPOSE

Currently, radiologic response of brain tumors is assessed according to the Macdonald criteria 10 weeks from the start of therapy. There exists a critical need to identify nonresponding patients early in the course of their therapy for consideration of alternative treatment strategies. Our study assessed the effectiveness of the parametric response map (PRM) imaging biomarker to provide for an earlier measure of patient survival prediction.

EXPERIMENTAL DESIGN

Forty-five high-grade glioma patients received concurrent chemoradiation. Quantitative MRI including apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired pretreatment and 3 weeks midtreatment on a prospective institutional-approved study. PRM, a voxel-by-voxel image analysis method, was evaluated as an early prognostic biomarker of overall survival. Clinical and conventional MR parameters were also evaluated.

RESULTS

Multivariate analysis showed that PRM(ADC+) in combination with PRM(rCBV-) obtained at week 3 had a stronger correlation to 1-year and overall survival rates than any baseline clinical or treatment response imaging metric. The composite biomarker identified three distinct patient groups, nonresponders [median survival (MS) of 5.5 months, 95% CI: 4.4-6.6 months], partial responders (MS of 16 months, 95% CI: 8.6-23.4 months), and responders (MS has not yet been reached).

CONCLUSIONS

Inclusion of PRM(ADC+) and PRM(rCBV-) into a single imaging biomarker metric provided early identification of patients resistant to standard chemoradiation. In comparison to the current standard of assessment of response at 10 weeks (Macdonald criteria), the composite PRM biomarker potentially provides a useful opportunity for clinicians to identify patients who may benefit from alternative treatment strategies.