Improved detection of air trapping on expiratory computed tomography using deep learning.

BACKGROUND: Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are highly variable, resulting in limited efficacy for monitoring disease progression. OBJECTIVE: To investigate the effectiveness of a convolutional neural network (CNN) model for quantifying and monitoring AT, and to compare it with other quantitative AT measures obtained from threshold-based techniques. MATERIALS AND METHODS: Paired volumetric whole lung inspiratory and expiratory CT scans were obtained at four time points (0, 3, 12 and 24 months) on 36 subjects with mild CF lung disease. A densely connected CNN (DN) was trained using AT segmentation maps generated from a personalized threshold-based method (PTM). Quantitative AT (QAT) values, presented as the relative volume of AT over the lungs, from the DN approach were compared to QAT values from the PTM method. Radiographic assessment, spirometric measures, and clinical scores were correlated to the DN QAT values using a linear mixed effects model. RESULTS: QAT values from the DN were found to increase from 8.65% ± 1.38% to 21.38% ± 1.82%, respectively, over a two-year period. Comparison of CNN model results to intensity-based measures demonstrated a systematic drop in the Dice coefficient over time (decreased from 0.86 ± 0.03 to 0.45 ± 0.04). The trends observed in DN QAT values were consistent with clinical scores for AT, bronchiectasis, and mucus plugging. In addition, the DN approach was found to be less susceptible to variations in expiratory deflation levels than the threshold-based approach. CONCLUSION: The CNN model effectively delineated AT on expiratory CT scans, which provides an automated and objective approach for assessing and monitoring AT in CF patients.

Parametric Response Mapping of FLAIR MRI Provides an Early Indication of Progression Risk in Glioblastoma.

RATIONALE AND OBJECTIVES: Glioblastoma image evaluation utilizes Magnetic Resonance Imaging contrast-enhanced, T1-weighted, and noncontrast T2-weighted fluid-attenuated inversion recovery (FLAIR) acquisitions. Disease progression assessment relies on changes in tumor diameter, which correlate poorly with survival. To improve treatment monitoring in glioblastoma, we investigated serial voxel-wise comparison of anatomically-aligned FLAIR signal as an early predictor of GBM progression. MATERIALS AND METHODS: We analyzed longitudinal normalized FLAIR images (rFLAIR) from 52 subjects using voxel-wise Parametric Response Mapping (PRM) to monitor volume fractions of increased (PRMrFLAIR+), decreased (PRMrFLAIR-), or unchanged (PRMrFLAIR0) rFLAIR intensity. We determined response by rFLAIR between pretreatment and 10 weeks posttreatment. Risk of disease progression in a subset of subjects (N = 26) with stable disease or partial response as defined by Response Assessment in Neuro-Oncology (RANO) criteria was assessed by PRMrFLAIR between weeks 10 and 20 and continuously until the PRMrFLAIR+ exceeded a defined threshold. RANO defined criteria were compared with PRM-derived outcomes for tumor progression detection. RESULTS: Patient stratification for progression-free survival (PFS) and overall survival (OS) was achieved at week 10 using RANO criteria (PFS: p <0.0001; OS: p <0.0001), relative change in FLAIR-hyperintense volume (PFS: p = 0.0011; OS: p <0.0001), and PRMrFLAIR+ (PFS: p <0.01; OS: p <0.001). PRMrFLAIR+ also stratified responding patients' progression between weeks 10 and 20 (PFS: p <0.05; OS: p = 0.01) while changes in FLAIR-volume measurements were not predictive. As a continuous evaluation, PRMrFLAIR+ exceeding 10% stratified patients for PFA after 5.6 months (p<0.0001), while RANO criteria did not stratify patients until 15.4 months (p <0.0001). CONCLUSION: PRMrFLAIR may provide an early biomarker of disease progression in glioblastoma.

Influence of Inspiratory/Expiratory CT Registration on Quantitative Air Trapping.

RATIONALE AND OBJECTIVES: The aim of this study was to assess variability in quantitative air trapping (QAT) measurements derived from spatially aligned expiration CT scans. MATERIALS AND METHODS: Sixty-four paired CT examinations, from 16 school-age cystic fibrosis subjects examined at four separate time intervals, were used in this study. For each pair, visually inspected lobe segmentation maps were generated and expiration CT data were registered to the inspiration CT frame. Measurements of QAT, the percentage of voxels on the expiration CT scan below a set threshold were calculated for each lobe and whole-lung from the registered expiration CT and compared to the true values from the unregistered data. RESULTS: A mathematical model, which simulates the effect of variable regions of lung deformation on QAT values calculated from aligned to those from unaligned data, showed the potential for large bias. Assessment of experimental QAT measurements using Bland-Altman plots corroborated the model simulations, demonstrating biases greater than 5% when QAT was approximately 40% of lung volume. These biases were removed when calculating QAT from aligned expiration CT data using the determinant of the Jacobian matrix. We found, by Dice coefficient analysis, good agreement between aligned expiration and inspiration segmentation maps for the whole-lung and all but one lobe (Dice coefficient > 0.9), with only the lingula generating a value below 0.9 (mean and standard deviation of 0.85 ± 0.06). CONCLUSION: The subtle and predictable variability in corrected QAT observed in this study suggests that image registration is reliable in preserving the accuracy of the quantitative metrics.

Multimodal imaging provides insight into targeted therapy response in metastatic prostate cancer to the bone.

Metastatic prostate cancer to bone remains incurable, driving efforts to develop individualized, targeted therapies to improve clinical outcomes while limiting adverse side-effects. Due to the complexity in cellular signaling pathways and the interaction between cancer and its microenvironment, multiparametric imaging approaches for treatment response may improve understanding of the biological effects of therapy. An orthotopic model of castration resistant prostate cancer (CRPC) bone metastasis was treated with the tyrosine kinase inhibitor Cabozantinib (CABO). Response was assessed using CT to monitor bone volumes, 99mTc-MDP SPECT for bone metabolism, and anatomical and diffusion MRI for tumor volume and cell death. A concurrent clinical trial of CABO for CRPC patients also evaluated multimodality imaging in correlation with standard response criteria. Response in the preclinical study found significant slowing in tumor growth rate (P<0.01), rise in tumor apparent diffusion coefficient (ADC, P<0.001), and drop in 99mTc-MDP adsorption (P<0.05). Loss of bone volume did not slow with treatment, attributed to the highly aggressive and osteolytic nature of the PC3 cell line. Clinical trial analysis found only a single subject who progressed after 12 weeks of therapy. Imaging at 6 weeks corroborated the 12-week radiological assessment with positive response visible as increased ADC and decreased vascular metrics. Conversely, the subject who progressed at 12 weeks had no change in ADC, and substantial drops in vascular metrics. These results showcase a multifaceted translational imaging approach for detecting targeted treatment response with effective blockade of tumor vascularization, tumor cell kill, and reduced proliferation.

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.

Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping.

Management of glioblastoma multiforme remains a challenging problem despite recent advances in targeted therapies. Timely assessment of therapeutic agents is hindered by the lack of standard quantitative imaging protocols for determining targeted response. Clinical response assessment for brain tumors is determined by volumetric changes assessed at 10 weeks post-treatment initiation. Further, current clinical criteria fail to use advanced quantitative imaging approaches, such as diffusion and perfusion magnetic resonance imaging. Development of the parametric response mapping (PRM) applied to diffusion-weighted magnetic resonance imaging has provided a sensitive and early biomarker of successful cytotoxic therapy in brain tumors while maintaining a spatial context within the tumor. Although PRM provides an earlier readout than volumetry and sometimes greater sensitivity compared with traditional whole-tumor diffusion statistics, it is not routinely used for patient management; an automated and standardized software for performing the analysis and for the generation of a clinical report document is required for this. We present a semiautomated and seamless workflow for image coregistration, segmentation, and PRM classification of glioblastoma multiforme diffusion-weighted magnetic resonance imaging scans. The software solution can be integrated using local hardware or performed remotely in the cloud while providing connectivity to existing picture archive and communication systems. This is an important step toward implementing PRM analysis of solid tumors in routine clinical practice.

Development of a Multiparametric Voxel-Based Magnetic Resonance Imaging Biomarker for Early Cancer Therapeutic Response Assessment.

Quantitative magnetic resonance imaging (MRI)-based biomarkers, which capture physiological and functional tumor processes, were evaluated as imaging surrogates of early tumor response following chemoradiotherapy in glioma patients. A multiparametric extension of a voxel-based analysis, referred as the parametric response map (PRM), was applied to quantitative MRI maps to test the predictive potential of this metric for detecting response. Fifty-six subjects with newly diagnosed high-grade gliomas treated with radiation and concurrent temozolomide were enrolled in a single-site prospective institutional review board-approved MRI study. Apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired before therapy and 3 weeks after therapy was initiated. Multiparametric PRM (mPRM) was applied to both physiological MRI maps and evaluated as an imaging biomarker of patient survival. For comparison, single-biomarker PRMs were also evaluated in this study. The simultaneous analysis of ADC and rCBV by the mPRM approach was found to improve the predictive potential for patient survival over single PRM measures. With an array of quantitative imaging parameters being evaluated as biomarkers of therapeutic response, mPRM shows promise as a new methodology for consolidating physiologically distinct imaging parameters into a single interpretable and quantitative metric.

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.

Phosphorylation of FADD by the kinase CK1α promotes KRASG12D-induced lung cancer.

Genomic amplification of the gene encoding and phosphorylation of the protein FADD (Fas-associated death domain) is associated with poor clinical outcome in lung cancer and in head and neck cancer. Activating mutations in the guanosine triphosphatase RAS promotes cell proliferation in various cancers. Increased abundance of phosphorylated FADD in patient-derived tumor samples predicts poor clinical outcome. Using immunohistochemistry analysis and in vivo imaging of conditional mouse models of KRAS(G12D)-driven lung cancer, we found that the deletion of the gene encoding FADD suppressed tumor growth, reduced the proliferative index of cells, and decreased the activation of downstream effectors of the RAS-MAPK (mitogen-activated protein kinase) pathway that promote the cell cycle, including retinoblastoma (RB) and cyclin D1. In mouse embryonic fibroblasts, the induction of mitosis upon activation of KRAS required FADD and the phosphorylation of FADD by CK1α (casein kinase 1α). Deleting the gene encoding CK1α in KRAS mutant mice abrogated the phosphorylation of FADD and suppressed lung cancer development. Phosphorylated FADD was most abundant during the G2/M phase of the cell cycle, and mass spectrometry revealed that phosphorylated FADD interacted with kinases that mediate the G2/M transition, including PLK1 (Polo-like kinase 1), AURKA (Aurora kinase A), and BUB1 (budding uninhibited by benzimidazoles 1). This interaction was decreased in cells treated with a CKI-7, a CK1α inhibitor. Therefore, as the kinase that phosphorylates FADD downstream of RAS, CK1α may be a therapeutic target for KRAS-driven lung cancer.

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

Pathologic vertebral compression fractures (PVCF) cause significant morbidity in patients with bone metastases from breast cancer and other malignancies. Due to limitations of existing biochemical and imaging biomarkers, clinicians currently have no reliable metrics to identify patients with impending PVCF, impeding efforts to prevent this severe complication. To establish the feasibility of a new method for defining risk of PVCF, we retrospectively analyzed serial CT scans from five breast cancer patients using parametric response mapping (PRM) to quantify dynamic bone density changes that preceded an event. Vertebrae segmented from each scan were registered to vertebrae at the earliest time point (i.e. furthest from PVCF) and voxel classification accomplished using a predetermined threshold of change in HU values, resulting in relative volumes of increased (PRMHU+), decreased (PRMHU-), or unchanged (PRMHU0) attenuation. A total of seven PVCF were compared to un-diseased vertebrae in each patient serving as controls. Receiver operator curve (ROC) analysis identified optimal image acquisition and analysis times for group stratification. Bone density changes were visualized by an increasing trend in PRMHU+ as early as one year before fracture. PRMHU- demonstrated negligible changes over the course of the study. These observations were consistent with ROC results, showing poor performance of PRMHU- in stratifying PVCF versus control. As early as 6 months prior to PVCF, PRMHU+ was significantly larger (12.9 ± 11.6%) compared to control vertebrae (2.3 ± 2.5%), with an AUC of 0.918 from a receiver operator curve analysis. Mean HU changes were also significant between PVCF (+26.8 ± 26.9%) and control (-2.2 ± 22.0%) over the same period. PRM analysis of bone density changes using standard CT imaging was sensitive for spatially resolving bone remodeling which preceded structural failure in patients with breast cancer vertebral metastases.

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.

Imaging proteolytic activity in live cells and animal models.

In addition to their degradative role in protein turnover, proteases play a key role as positive or negative regulators of signal transduction pathways and therefore their dysregulation contributes to many disease states. Regulatory roles of proteases include their hormone-like role in triggering G protein-coupled signaling (Protease-Activated-Receptors); their role in shedding of ligands such as EGF, Notch and Fas; and their role in signaling events that lead to apoptotic cell death. Dysregulated activation of apoptosis by the caspase family of proteases has been linked to diseases such as cancer, autoimmunity and inflammation. In an effort to better understand the role of proteases in health and disease, a luciferase biosensor is described which can quantitatively report proteolytic activity in live cells and mouse models. The biosensor, hereafter referred to as GloSensor Caspase 3/7 has a robust signal to noise (50-100 fold) and dynamic range such that it can be used to screen for pharmacologically active compounds in high throughput campaigns as well as to study cell signaling in rare cell populations such as isolated cancer stem cells. The biosensor can also be used in the context of genetically engineered mouse models of human disease wherein conditional expression using the Cre/loxP technology can be implemented to investigate the role of a specific protease in living subjects. While the regulation of apoptosis by caspase's was used as an example in these studies, biosensors to study additional proteases involved in the regulation of normal and pathological cellular processes can be designed using the concepts presented herein.

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.

Multimodality imaging of tumor and bone response in a mouse model of bony metastasis.

Cancer drug development generally performs in vivo evaluation of treatment effects that have traditionally relied on detection of morphologic changes. The emergence of new targeted therapies, which may not result in gross morphologic changes, has spurred investigation into more specific imaging methods to quantify response, such as targeted fluorescent probes and bioluminescent cells. The present study investigated tissue response to docetaxel or zoledronic acid (ZA) in a mouse model of bony metastasis. Intratibial implantations of breast cancer cells (MDA-MB-231) were monitored throughout this study using several modalities: molecular resonance imaging (MRI) tumor volume and apparent diffusion coefficient (ADC), micro-computed tomography (µCT) bone volume, bioluminescence imaging (BLI) reporting cancer cell apoptosis, and fluorescence using Osteosense 800 and CatK 680-FAST. Docetaxel treatment resulted in tumor cell kill reflected by ADC and BLI increases and tumor volume reduction, with delayed bone recovery seen in µCT prefaced by increased osteoblastic activity (Osteosense 800). In contrast, the ZA treatment group produced similar values in MRI, BLI, and Osteosense 800 fluorescence imaging readouts when compared to controls. However, µCT bone volume increased significantly by the first week post-treatment and the CatK 680-FAST signal was slightly diminished by 4 weeks following ZA treatment. Multimodality imaging provides a more comprehensive tool for new drug evaluation and efficacy screening through identification of morphology as well as function and apoptotic signaling.

DCE and DW-MRI monitoring of vascular disruption following VEGF-Trap treatment of a rat glioma model.

Vascular-targeted therapies have shown promise as adjuvant cancer treatment. As these agents undergo clinical evaluation, sensitive imaging biomarkers are needed to assess drug target interaction and treatment response. In this study, dynamic contrast enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) were evaluated for detecting response of intracerebral 9 L gliosarcomas to the antivascular agent VEGF-Trap, a fusion protein designed to bind all forms of Vascular Endothelial Growth Factor-A (VEGF-A) and Placental Growth Factor (PGF). Rats with 9 L tumors were treated twice weekly for two weeks with vehicle or VEGF-Trap. DCE- and DW-MRI were performed one day prior to treatment initiation and one day following each administered dose. Kinetic parameters (K(trans), volume transfer constant; k(ep), efflux rate constant from extravascular/extracellular space to plasma; and v(p), blood plasma volume fraction) and the apparent diffusion coefficient (ADC) over the tumor volumes were compared between groups. A significant decrease in kinetic parameters was observed 24 hours following the first dose of VEGF-Trap in treated versus control animals (p < 0.05) and was accompanied by a decline in ADC values. In addition to the significant hemodynamic effect, VEGF-Trap treated animals exhibited significantly longer tumor doubling times (p < 0.05) compared to the controls. Histological findings were found to support imaging response metrics. In conclusion, kinetic MRI parameters and change in ADC have been found to serve as sensitive and early biomarkers of VEGF-Trap anti-vascular targeted therapy.

Convection enhanced delivery of carboplatin in combination with radiotherapy for the treatment of brain tumors.

The purpose of this study was to further evaluate the therapeutic efficacy of convection enhanced delivery (CED) of carboplatin in combination with radiotherapy for treatment of the F98 rat glioma. Tumor cells were implanted stereotactically into the brains of syngeneic Fischer rats, and 13 or 17 d. later carboplatin (20 µg/10 µl) was administered by either CED over 30 min or by Alzet osmotic pumps (0.5 µg/µl/h for 168 h.) beginning at 7 d after tumor implantation. Rats were irradiated with a 15 Gy fractionated dose (5 Gy × 3) of 6 MV photons to the whole brain beginning on the day after drug administration. Other groups of rats received either carboplatin or X-irradiation alone. The tumor carboplatin concentration following CED of 20 µg in 10 µl was 10.4 µg/g, which was equal to that observed following i.v. administration of 100 mg/kg b.w. Rats bearing small tumors, treated with carboplatin and X-irradiation, had a mean survival time (MST) of 83.4 d following CED and 111.8 d following pump delivery with 40% of the latter surviving >180 d (i.e. cured) compared to 55.2 d for CED and 77.2 d. for pump delivery of carboplatin alone and 31.8 d and 24.2 d, respectively, for X-irradiated and untreated controls. There was no microscopic evidence of residual tumor in the brains of all long-term survivors. Not surprisingly, rats with large tumors had much shorter MSTs. Only modest increases in MSTs were observed in animals that received either oral administration or CED of temozolomide plus X-irradiation (23.2 d and 29.3 d) compared to X-irradiation alone. The present survival data, and those previously reported by us, are among the best ever obtained with the F98 glioma model. Initially, they could provide a platform for a Phase I clinical trial to evaluate the safety and potential therapeutic efficacy of CED of carboplatin in patients with recurrent glioblastomas, and ultimately a Phase II trial of carboplatin in combination with radiation therapy.

Assessment of multiexponential diffusion features as MRI cancer therapy response metrics.

The aim of this study was to empirically test the effect of chemotherapy-induced tissue changes in a glioma model as measured by several diffusion indices calculated from nonmonoexponential formalisms over a wide range of b-values. We also compared these results to the conventional two-point apparent diffusion coefficient calculation using nominal b-values. Diffusion-weighted imaging was performed over an extended range of b-values (120-4000 sec/mm(2) ) on intracerebral rat 9L gliomas before and after a single dose of 1,3-bis(2-chloroethyl)-1-nitrosourea. Diffusion indices from three formalisms of diffusion-weighted signal decay [(a) two-point analytical calculation using either low or high b-values, (b) a stretched exponential formalism, and (c) a biexponential fit] were tested for responsiveness to therapy-induced differences between control and treated groups. Diffusion indices sensitive to "fast diffusion" produced the largest response to treatment, which resulted in significant differences between groups. These trends were not observed for "slow diffusion" indices. Although the highest rate of response was observed from the biexponential formalism, this was not found to be significantly different from the conventional monoexponential apparent diffusion coefficient method. In conclusion, parameters from the more complicated nonmonoexponential formalisms did not provide additional sensitivity to treatment response in this glioma model beyond that observed from the two-point conventional monoexponential apparent diffusion coefficient method.

The brain tumor window model: a combined cranial window and implanted glioma model for evaluating intraoperative contrast agents.

OBJECTIVE: Optical contrast agents for brain tumor delineation have been previously evaluated in ex vivo specimens from animals with implanted gliomas and may not reflect the true visual parameters encountered during surgery. This study describes a novel model system designed to evaluate optical contrast agents for tumor delineation in vivo. METHODS: Biparietal craniectomies were performed on 8-week-old Sprague-Dawley rats. 9L glioma cells were injected intraparenchymally. A cover slip was bonded to the cranial defect with cyanoacrylate glue. When the tumor radius reached 1 mm, Coomassie Blue was administered intravenously while the appearance of the cortical surface was recorded. Computerized image analysis of the red/green/blue color components was used to quantify visible differences between tumor and nonneoplastic tissue and to compare delineation in the brain tumor window (BTW) model with the conventional 9L glioma model. RESULTS: The tumor margin in the BTW model was poorly defined before contrast administration but readily apparent after contrast administration. Based on red component intensity, tumor delineation improved 4-fold at 50 minutes after contrast administration in the BTW model (P < .002). The conventional 9L glioma model overestimated the degree of delineation compared with the BTW model at the same dose of Coomassie Blue (P < .03). CONCLUSION: Window placement overlying an implanted glioma is technically possible and well tolerated in the rat. The BTW model is a valid system for evaluating optical contrast agents designed to delineate brain tumor margins. To our knowledge, we have described the first in vivo model system for evaluating optical contrast agents for tumor delineation.

The functional diffusion map: an imaging biomarker for the early prediction of cancer treatment outcome.

Functional diffusion map (fDM) has been recently reported as an early and quantitative biomarker of clinical brain tumor treatment outcome. This approach spatially maps and quantifies treatment-induced changes in tumor water diffusion values resulting from alterations in cell density/cell membrane function and microenvironment. This current study was designed to evaluate the capability of fDM for preclinical evaluation of dose escalation studies and to determine if these changes were correlated with outcome measures (cell kill and overall survival). Serial T2-weighted were carried out on rodents with orthotopically implanted 9L brain tumors receiving three doses of 1,3-bis(2-chloroethyl)-1-nitrosourea (6.65, 13.3, and 26.6 mg/kg, i.p.). All images were coregistered to baseline T2-weighted images for fDM analysis. Analysis of tumor fDM data on day 4 posttreatment detected dose-dependent changes in tumor diffusion values, which were also found to be spatially dependent. Histologic analysis of treated tumors confirmed spatial changes in cellularity as observed by fDM. Early changes in tumor diffusion values were found to be highly correlative with drug dose and independent biologic outcome measures (cell kill and survival). Therefore, The fDM imaging biomarker for early prediction of treatment efficacy can be used in the drug development process.

Dynamic imaging of emerging resistance during cancer therapy.

One of the greatest challenges in developing therapeutic regimens is the inability to rapidly and objectively assess tumor response due to treatment. Moreover, tumor response to therapeutic intervention in many cases is transient, and progressive alterations within the tumor may mask the effectiveness of an initially successful therapy. The ability to detect these changes as they occur would allow timely initiation of alternative approaches, maximizing therapeutic outcome. We investigated the ability of diffusion magnetic resonance imaging (MRI) to provide a sensitive measure of tumor response throughout the course of treatment, possibly identifying changes in sensitivity to the therapy. Orthotopic 9L gliomas were subjected to two separate therapeutic regimens, with one group receiving a single 5-day cycle (1omega) of low-dose 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU) and a second group receiving two cycles at the same dose, bisected with 2 days of rest (2omega). Apparent diffusion coefficient maps were acquired before and throughout treatment to observe changes in water mobility, and these observations were correlated to standard measures of therapeutic response and outcome. Our results showed that diffusion MRI was indeed able to detect the emergence of a drug-resistant tumor subpopulation subsequent to an initially successful cycle of BCNU therapy, leading to minimal gains from a second cycle. These diffusion MRI findings were highly correlated with tumor growth delay, animal survival, and ex vivo growth inhibition assays showing emerging resistance in excised tumors. Overall, this study highlights the ability of diffusion MRI to provide sensitive dynamic assessment of therapy-induced response, allowing early opportunities for optimization of therapeutic protocols.