Chronic obstructive pulmonary disease (COPD) is now known to be a heterogeneous disorder, hence the pressing need to develop imaging biomarkers to differentiate between the broad range of COPD phenotypes–all of which require different treatments. Here, Craig Galban and his colleagues have adapted the parametric response map technique for the voxel-by-voxel classification analysis of CT lung images taken from a national COPD trial, providing a more objective characterization of the phenotypic contributions of functional small airways disease and emphysema in COPD. 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 is 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 computed tomography (CT) scans acquired at inspiration and expiration of 194 individuals with COPD 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. PRM's ability to differentiate between specific COPD phenotypes will allow for more accurate diagnosis of individual patients, complementing standard clinical techniques.

Background: A surrogate marker for treatment response that can be observed earlier than comparison of sequential magnetic resonance imaging (MRI) scans, which depends on relatively slow changes in tumor volume, may improve survival of brain tumor patients by providing more time for secondary therapeutic interventions. Previous studies in animals with the use of diffusion MRI revealed rapid changes in tumor water diffusion values after successful therapeutic intervention. Methods: The present study examined the sensitivity of diffusion MRI measurements in orthotopic rat brain tumors derived from implanted rat 9L glioma cells. The effectiveness of therapy for individual brain cancer patients was evaluated by measuring changes in tumor volume on neuroimaging studies conducted 6–8 weeks after the conclusion of a treatment cycle. Results: Diffusion MRI could detect water diffusion changes in orthotopic 9L gliomas after doses of 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU or carmustine) that resulted in as little as 0.2 log cell kill, a measure of tumor cell death. Mean apparent diffusion coefficients in tumors were found to be correlated with and highly sensitive to changes in tumor cellularity (r = .78; two-sided P = .041). The feasibility of serial diffusion MRI in the clinical management of primary brain tumor patients was also demonstrated. Increased diffusion values could be detected in human brain tumors shortly after treatment initiation. The magnitude of the diffusion changes corresponded with clinical outcome. Conclusions: These results suggest that diffusion MRI will provide an early surrogate marker for quantification of treatment response in patients with brain tumors.

Assessment of radiation and chemotherapy efficacy for brain cancer patients is traditionally accomplished by measuring changes in tumor size several months after therapy has been administered. The ability to use noninvasive imaging during the early stages of fractionated therapy to determine whether a particular treatment will be effective would provide an opportunity to optimize individual patient management and avoid unnecessary systemic toxicity, expense, and treatment delays. We investigated whether changes in the Brownian motion of water within tumor tissue as quantified by using diffusion MRI could be used as a biomarker for early prediction of treatment response in brain cancer patients. Twenty brain tumor patients were examined by standard and diffusion MRI before initiation of treatment. Additional images were acquired 3 weeks after initiation of chemo- and/or radiotherapy. Images were coregistered to pretreatment scans, and changes in tumor water diffusion values were calculated and displayed as a functional diffusion map (fDM) for correlation with clinical response. Of the 20 patients imaged during the course of therapy, 6 were classified as having a partial response, 6 as stable disease, and 8 as progressive disease. The fDMs were found to predict patient response at 3 weeks from the start of treatment, revealing that early changes in tumor diffusion values could be used as a prognostic indicator of subsequent volumetric tumor response. Overall, fDM analysis provided an early biomarker for predicting treatment response in brain tumor patients.

Current assessment of orthotopic tumor models in animals utilizes survival as the primary therapeutic end point. In vivo bioluminescence imaging (BLI) is a sensitive imaging modality that is rapid and accessible, and may comprise an ideal tool for evaluating antineoplastic therapies. Using human tumor cell lines constitutively expressing luciferase, the kinetics of tumor growth and response to therapy have been assessed in intraperitoneal, and subcutaneous, and intravascular cancer models. However, use of this approach for evaluating orthotopic tumor models has not been demonstrated. In this report, the ability of BLI to noninvasively quantitate the growth and therapeutic-induced cell kill of orthotopic rat brain tumors derived from 9L gliosarcoma cells genetically engineered to stably express firefly luciferase (9LLuc) was investigated. Intracerebral tumor burden was monitored over time by quantitation of photon emission and tumor volume using a cryogenically cooled CCD camera and magnetic resonance imaging (MRI), respectively. There was excellent correlation (r=0.91) between detected photons and tumor volume. A quantitative comparison of tumor cell kill determined from serial MRI volume measurements and BLI photon counts following 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU) treatment revealed that both imaging modalities yielded statistically similar cell kill values (P=.951). These results provide direct validation of BLI imaging as a powerful and quantitative tool for the assessment of antineoplastic therapies in living animals.

Diffuse malignant gliomas, the most common type of brain tumor, carry a dire prognosis and are poorly responsive to initial treatment. The response to treatment is typically evaluated by measurements obtained from radiographic images several months after the start of treatment; therefore, an early biomarker of tumor response would be useful for making early treatment decisions and for prognostic information. Thirty-four patients with malignant glioma were examined by diffusion MRI before treatment and 3 weeks later. These images were coregistered, and differences in tumor-water diffusion values were calculated as functional diffusion maps (fDM), which were correlated with the radiographic response, time-to-progression (TTP), and overall survival (OS). Changes in fDM at 3 weeks were closely associated with the radiographic response at 10 weeks. The percentage of the tumor undergoing a significant change in the diffusion of water ( V _T ) was different between patients with progressive disease (PD) vs. stable disease (SD) ( P < 0.001). Patients classified as PD by fDM analysis at 3 weeks were found to have a shorter TTP compared with SD (median TTP, 4.3 vs. 7.3 months; P < 0.04). By using fDM, early patient stratification also was correlated with shorter OS in the PD group compared with SD patients (median survival, 8.0 vs. 18.2 months; P < 0.01). On the basis of fDM, tumor assessment provided an early biomarker for response, TTP, and OS in patients with malignant glioma. Further evaluation of this technique is warranted to determine whether it may be useful in the individualization of treatment or evaluation of the response in clinical protocols.