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Craig J Galbán,
Meilan K Han,
Jennifer L Boes,
Komal A Chughtai, Charles R Meyer,
Timothy D Johnson,
Stefanie Galbán,
Alnawaz Rehemtulla,
Ella A Kazerooni,
Fernando J Martinez,
Brian D Ross
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ABSTRACT: 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.
Nature medicine 10/2012; · 27.14 Impact Factor
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ABSTRACT: 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. J. Magn. Reson. Imaging 2012. © 2012 Wiley Periodicals, Inc.
Journal of Magnetic Resonance Imaging 09/2012; · 2.70 Impact Factor
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Benjamin A Hoff,
Kenneth M Kozloff,
Jennifer L Boes,
Jean-Christophe Brisset,
Stefanie Galbán,
Catherine H Van Poznak,
Jon A Jacobson,
Timothy D Johnson, Charles R Meyer,
Alnawaz Rehemtulla,
Brian D Ross,
Craig J Galbán
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ABSTRACT: 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.
Bone 04/2012; 51(1):78-84. · 4.02 Impact Factor
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ABSTRACT: We assessed the performance of parametric fusion PET/MRI based on (11)C-choline PET/CT and apparent diffusion coefficient (ADC) maps derived from diffusion-weighted MRI for the identification of primary prostate cancer.
(11)C-choline PET/CT and MRI were performed in 17 patients with untreated primary prostate cancer, followed by prostatectomy. Registration of in vivo imaging with histology was achieved using a mutual-information objective function and by performing ex vivo MRI of the prostatectomy specimen (obtained at 3 T) and whole-mount sectioning with block-face photography as intermediate steps. Data analysis included volumetrically registered whole-mount histology with Gleason scoring, (11)C-choline, and ADC data (obtained at 1.5 T). Volumes of interest were defined on the basis of histologically proven tumor tissue to calculate tumor-to-benign prostate background ratios (TBRs) for (11)C-choline, ADC, and a derived fusion PET/MRI parameter calculating the quotient of (11)C-choline over ADC (P(CHOL/ADC)).
Fifty-one tumor nodules were identified at pathology. The TBRs for (11)C-choline (P < 0.05) and P(CHOL/ADC) (P < 0.005) were significantly higher in prostate cancers with a Gleason score of ≥3 + 4 than with a Gleason score of ≤3 + 3 disease and controls. For Gleason ≥ 3 + 4, the ADC TBRs were significantly lower than controls and Gleason ≤ 3 + 3 disease (P < 0.05). The absolute value of TBRs obtained from Gleason ≥ 3 + 4 cancers increased from ADC to (11)C-choline PET/CT and from (11)C-choline PET/CT to P(CHOL/ADC), with each step being statistically significant.
Our data indicate that parametric PET/MRI using P(CHOL/ADC) improves lesion-to-background contrast (TBRs) of Gleason ≥ 3 + 4 disease, compared with (11)C-choline PET/CT or diffusion-weighted MRI, and thus hold promise that parametric imaging performed on hybrid PET/MRI may further improve identification and localization of significant primary prostate cancer.
Journal of Nuclear Medicine 03/2012; 53(4):546-51. · 6.38 Impact Factor
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ABSTRACT: The prognosis for patients with high grade gliomas is poor, with a median survival of 1 year. Treatment efficacy assessment is typically unavailable until 5-6 months post diagnosis. Investigators hypothesize that quantitative magnetic resonance imaging can assess treatment efficacy 3 weeks after therapy starts, thereby allowing salvage treatments to begin earlier. The purpose of this work is to build a predictive model of treatment efficacy by using quantitative magnetic resonance imaging data and to assess its performance. The outcome is 1-year survival status. We propose a joint, two-stage Bayesian model. In stage I, we smooth the image data with a multivariate spatiotemporal pairwise difference prior. We propose four summary statistics that are functionals of posterior parameters from the first-stage model. In stage II, these statistics enter a generalized non-linear model as predictors of survival status. We use the probit link and a multivariate adaptive regression spline basis. Gibbs sampling and reversible jump Markov chain Monte Carlo methods are applied iteratively between the two stages to estimate the posterior distribution. Through both simulation studies and model performance comparisons we find that we can achieve higher overall correct classification rates by accounting for the spatiotemporal correlation in the images and by allowing for a more complex and flexible decision boundary provided by the generalized non-linear model.
Applied Statistics 01/2012; 61(1):83-98. · 0.83 Impact Factor
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Benjamin A Hoff,
Mahaveer S Bhojani,
John Rudge,
Thomas L Chenevert, Charles R Meyer,
Stefanie Galbán,
Timothy D Johnson,
Judith Sebolt Leopold,
Alnawaz Rehemtulla,
Brian D Ross,
Craig J Galbán
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ABSTRACT: 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.
NMR in Biomedicine 12/2011; 25(7):935-42. · 3.21 Impact Factor
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ABSTRACT: Assuming that early tumor volume change is a biomarker for response to therapy, accurate quantification of early volume changes could aid in adapting an individual patient's therapy and lead to shorter clinical trials. We investigated an image registration-based approach for tumor volume change quantification that may more reliably detect smaller changes that occur in shorter intervals than can be detected by existing algorithms.
Variance and bias of the registration-based approach were evaluated using retrospective, in vivo, very-short-interval diffusion magnetic resonance imaging scans where true zero tumor volume change is unequivocally known and synthetic data, respectively. The interval scans were nonlinearly registered using two similarity measures: mutual information (MI) and normalized cross-correlation (NCC).
The 95% confidence interval of the percentage volume change error was (-8.93% to 10.49%) for MI-based and (-7.69%, 8.83%) for NCC-based registrations. Linear mixed-effects models demonstrated that error in measuring volume change increased with increase in tumor volume and decreased with the increase in the tumor's normalized mutual information, even when NCC was the similarity measure being optimized during registration. The 95% confidence interval of the relative volume change error for the synthetic examinations with known changes over ±80% of reference tumor volume was (-3.02% to 3.86%). Statistically significant bias was not demonstrated.
A low-noise, low-bias tumor volume change measurement algorithm using nonlinear registration is described. Errors in change measurement were a function of tumor volume and the normalized mutual information content of the tumor.
International journal of radiation oncology, biology, physics 12/2011; 83(3):1038-46. · 4.59 Impact Factor
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ABSTRACT: 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.
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 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.
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.
Journal of Magnetic Resonance Imaging 10/2011; 34(4):983-7. · 2.70 Impact Factor
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Craig J Galbán,
Thomas L Chenevert, Charles R Meyer,
Christina Tsien,
Theodore S Lawrence,
Daniel A Hamstra,
Larry Junck,
Pia C Sundgren,
Timothy D Johnson,
Stefanie Galbán,
Judith S Sebolt-Leopold,
Alnawaz Rehemtulla,
Brian D Ross
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ABSTRACT: 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.
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.
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).
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.
Clinical Cancer Research 04/2011; 17(14):4751-60. · 7.74 Impact Factor
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Samuel G. Armato,
Geoffrey McLennan,
Luc Bidaut,
Michael F. McNitt-Gray, Charles R. Meyer,
Anthony P. Reeves,
Binsheng Zhao,
Denise R. Aberle,
Claudia I. Henschke,
Eric A. Hoffman, [......],
Michael H. Kuhn,
Ekta Dharaiya,
Richard Burns,
David S. Fryd,
Marcos Salganicoff,
Vikram Anand,
Uri Shreter,
Stephen Vastagh,
Barbara Y. Croft,
Laurence P. Clarke
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ABSTRACT: Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.
Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (“nodule ≥ 3 mm,” “nodule<3 mm,” and “non-nodule ≥ 3 mm”). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus.
Results: The Database contains 7371 lesions marked “nodule” by at least one radiologist. 2669 of these lesions were marked “nodule ≥ 3 mm” by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings.
Conclusions: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.
Medical Physics 01/2011; 38(2):915-931. · 2.83 Impact Factor
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Christina Tsien,
Craig J Galbán,
Thomas L Chenevert,
Timothy D Johnson,
Daniel A Hamstra,
Pia C Sundgren,
Larry Junck, Charles R Meyer,
Alnawaz Rehemtulla,
Theodore Lawrence,
Brian D Ross
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ABSTRACT: To assess whether a new method of quantifying therapy-associated hemodynamic alterations may help to distinguish pseudoprogression from true progression in patients with high-grade glioma.
Patients with high-grade glioma received concurrent chemoradiotherapy. Relative cerebral blood volume (rCBV) and blood flow (rCBF) maps were acquired before chemoradiotherapy and at week 3 during treatment on a prospective institutional review board-approved study. Pseudoprogression was defined as imaging changes 1 to 3 months after chemoradiotherapy that mimic tumor progression but stabilized or improved without change in treatment or for which resection revealed radiation effects only. Clinical and conventional magnetic resonance (MR) parameters, including average percent change of rCBV and CBF, were evaluated as potential predictors of pseudoprogression. Parametric response map (PRM), an innovative, voxel-by-voxel method of image analysis, was also performed.
Median radiation dose was 72 Gy (range, 60 to 78 Gy). Of 27 patients, stable disease/partial response was noted in 13 patients and apparent progression was noted in 14 patients. Adjuvant temozolomide was continued in all patients. Pseudoprogression occurred in six patients. Based on PRM analysis, a significantly reduced blood volume (PRM(rCBV)) at week 3 was noted in patients with progressive disease as compared with those with pseudoprogression (P < .01). In contrast, change in average percent rCBV or rCBF, MR tumor volume changes, age, extent of resection, and Radiation Therapy Oncology Group recursive partitioning analysis classification did not distinguish progression from pseudoprogression.
PRM(rCBV) at week 3 during chemoradiotherapy is a potential early imaging biomarker of response that may be helpful in distinguishing pseudoprogression from true progression in patients with high-grade glioma.
Journal of Clinical Oncology 04/2010; 28(13):2293-9. · 18.37 Impact Factor
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Thomas C. Kwee MD,
Craig J. Galbán PhD,
Christina Tsien MD,
Larry Junck MD,
PhD Pia C. Sundgren MD,
Marko K. Ivancevic PhD,
Timothy D. Johnson PhD,
Charles R. Meyer PhD,
Alnawaz Rehemtulla PhD,
Brian D. Ross PhD, [......],
Craig J. Galbán,
Christina Tsien,
Larry Junck,
Pia C. Sundgren,
Marko K. Ivancevic,
Timothy D. Johnson, Charles R. Meyer,
Alnawaz Rehemtulla,
Brian D. Ross,
Thomas L. Chenevert
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ABSTRACT: Purpose:To compare apparent diffusion coefficients (ADCs) with distributed diffusion coefficients (DDCs) in high-grade gliomas.Materials and Methods:Twenty patients with high-grade gliomas prospectively underwent diffusion-weighted MRI. Traditional ADC maps were created using b-values of 0 and 1000 s/mm2. In addition, DDC maps were created by applying the stretched-exponential model using b-values of 0, 1000, 2000, and 4000 s/mm2. Whole-tumor ADCs and DDCs (in 10−3 mm2/s) were measured and analyzed with a paired t-test, Pearson's correlation coefficient, and the Bland-Altman method.Results:Tumor ADCs (1.14 ± 0.26) were significantly lower (P = 0.0001) than DDCs (1.64 ± 0.71). Tumor ADCs and DDCs were strongly correlated (R = 0.9716; P < 0.0001), but mean bias ± limits of agreement between tumor ADCs and DDCs was −0.50 ± 0.90. There was a clear trend toward greater discordance between ADC and DDC at high ADC values.Conclusion:Under the assumption that the stretched-exponential model provides a more accurate estimate of the average diffusion rate than the mono-exponential model, our results suggest that for a little diffusion attenuation the mono-exponential fit works rather well for quantifying diffusion in high-grade gliomas, whereas it works less well for a greater degree of diffusion attenuation. J. Magn. Reson. Imaging 2010;31:531–537. © 2010 Wiley-Liss, Inc.
Journal of Magnetic Resonance Imaging 02/2010; 31(3):531 - 537. · 2.70 Impact Factor
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Craig J Galbán,
Mahaveer S Bhojani,
Kuei C Lee, Charles R Meyer,
Marcian E Van Dort,
Kyle K Kuszpit,
Robert A Koeppe,
Rajesh Ranga,
Bradford A Moffat,
Timothy D Johnson,
Thomas L Chenevert,
Alnawaz Rehemtulla,
Brian D Ross
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ABSTRACT: Functional imaging biomarkers of cancer treatment response offer the potential for early determination of outcome through the assessment of biochemical, physiologic, and microenvironmental readouts. Cell death may result in an immunologic response, thus complicating the interpretation of biomarker readouts. This study evaluated the temporal effect of treatment-associated inflammatory activity on diffusion magnetic resonance imaging and 2-[(18)F]-fluoro-2-deoxy-D-glucose-positron emission tomography imaging (FDG-PET) biomarkers to delineate the effects of the inflammatory response on imaging readouts.
Rats with intracerebral 9L gliosarcomas were separated into four groups consisting of control, an immunosuppressive agent dexamethasone (Dex), 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU), and BCNU+Dex. Animals were imaged using diffusion-weighted magnetic resonance imaging and FDG-PET at 0, 3, and 7 days posttreatment.
In the BCNU- and BCNU+Dex-treated animal groups, diffusion values increased progressively over the 7-day study period to approximately 23% over baseline. The FDG percentage change of standard uptake value decreased at day 3 (-30.9%) but increased over baseline levels at day 7 (+20.1%). FDG-PET of BCNU+Dex-treated animals were found to have percentage of standard uptake value reductions of -31.4% and -24.7% at days 3 and 7, respectively, following treatment. Activated macrophages were observed on day 7 in the BCNU treatment group with much fewer found in the BCNU+Dex group.
Results revealed that treatment-associated inflammatory response following tumor therapy resulted in the accentuation of tumor diffusion response along with a corresponding increase in tumor FDG uptake due to the presence of glucose-consuming activated macrophages. The dynamics and magnitude of potential inflammatory response should be considered when interpreting imaging biomarker results.
Clinical Cancer Research 02/2010; 16(5):1542-52. · 7.74 Impact Factor
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ABSTRACT: Positron emission tomography (PET) is actively investigated to aid in target volume definition for radiation therapy. The objectives of this study were to apply an automatic computer algorithm to compute target volumes and to validate the algorithm using histologic data from real human prostate cancer.
Various modalities for prostate imaging were performed. In vivo imaging included T2 3-T magnetic resonance imaging and (11)C-choline PET. Ex vivo imaging included 3-T magnetic resonance imaging, histology, and block face photos of the prostate specimen. A novel registration method based on mutual information and thin-plate splines was applied to all modalities. Once PET is registered with histology, a voxel-by-voxel comparison between PET and histology is possible. A thresholding technique based on various fractions of the maximum standardized uptake value in the tumor was applied, and the respective computed threshold volume on PET was compared with histologic truth.
Sixteen patients whose primary tumor volumes ranged from 1.2 to 12.6 cm(3) were tested. PET has low spatial resolution, so only tumors > 4 cm(3) were considered. Four cases met this criterion. A threshold value of 60% of the (11)C-choline maximum standardized uptake value resulted in the highest volume overlap between threshold volume on PET and histology. Medial axis distances between threshold volume on PET and histology showed a mean error of 7.7 +/- 5.2 mm.
This is a proof-of-concept study demonstrating for the first time that histology-guided thresholding on PET can delineate tumor volumes in real human prostate cancer.
Academic radiology 02/2010; 17(5):614-23. · 2.09 Impact Factor
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Thomas C Kwee,
Craig J Galbán,
Christina Tsien,
Larry Junck,
Pia C Sundgren,
Marko K Ivancevic,
Timothy D Johnson, Charles R Meyer,
Alnawaz Rehemtulla,
Brian D Ross,
Thomas L Chenevert
[show abstract]
[hide abstract]
ABSTRACT: To compare apparent diffusion coefficients (ADCs) with distributed diffusion coefficients (DDCs) in high-grade gliomas.
Twenty patients with high-grade gliomas prospectively underwent diffusion-weighted MRI. Traditional ADC maps were created using b-values of 0 and 1000 s/mm(2). In addition, DDC maps were created by applying the stretched-exponential model using b-values of 0, 1000, 2000, and 4000 s/mm(2). Whole-tumor ADCs and DDCs (in 10(-3) mm(2)/s) were measured and analyzed with a paired t-test, Pearson's correlation coefficient, and the Bland-Altman method.
Tumor ADCs (1.14 +/- 0.26) were significantly lower (P = 0.0001) than DDCs (1.64 +/- 0.71). Tumor ADCs and DDCs were strongly correlated (R = 0.9716; P < 0.0001), but mean bias +/- limits of agreement between tumor ADCs and DDCs was -0.50 +/- 0.90. There was a clear trend toward greater discordance between ADC and DDC at high ADC values.
Under the assumption that the stretched-exponential model provides a more accurate estimate of the average diffusion rate than the mono-exponential model, our results suggest that for a little diffusion attenuation the mono-exponential fit works rather well for quantifying diffusion in high-grade gliomas, whereas it works less well for a greater degree of diffusion attenuation.
Journal of Magnetic Resonance Imaging 02/2010; 31(3):531-7. · 2.70 Impact Factor
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IEICE Transactions. 01/2010; 93-D:2291-2301.
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Charles R Meyer,
Samuel G Armato,
Charles P Fenimore,
Geoffrey McLennan,
Luc M Bidaut,
Daniel P Barboriak,
Marios A Gavrielides,
Edward F Jackson,
Michael F McNitt-Gray,
Paul E Kinahan,
Nicholas Petrick,
Binsheng Zhao
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ABSTRACT: Early detection of tumor response to therapy is a key goal. Finding measurement algorithms capable of early detection of tumor response could individualize therapy treatment as well as reduce the cost of bringing new drugs to market. On an individual basis, the urgency arises from the desire to prevent continued treatment of the patient with a high-cost and/or high-risk regimen with no demonstrated individual benefit and rapidly switch the patient to an alternative efficacious therapy for that patient. In the context of bringing new drugs to market, such algorithms could demonstrate efficacy in much smaller populations, which would allow phase 3 trials to achieve statistically significant decisions with fewer subjects in shorter trials.
This consensus-based article describes multiple, image modality-independent means to assess the relative performance of algorithms for measuring tumor change in response to therapy. In this setting, we describe specifically the example of measurement of tumor volume change from anatomic imaging as well as provide an overview of other promising generic analytic methods that can be used to assess change in heterogeneous tumors. To support assessment of the relative performance of algorithms for measuring small tumor change, data sources of truth are required.
Very short interval clinical imaging examinations and phantom scans provide known truth for comparative evaluation of algorithms.
For a given category of measurement methods, the algorithm that has the smallest measurement noise and least bias on average will perform best in early detection of true tumor change.
Translational oncology 12/2009; 2(4):198-210. · 3.40 Impact Factor
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ABSTRACT: This article describes methods and issues that are specific to the assessment of change in tumor characteristics as measured using quantitative magnetic resonance (MR) techniques and how this relates to the establishment of quantitative MR imaging (MRI) biomarkers of patient response to therapy. The initial focus is on the various sources of bias and variance in the measurement of microvascular parameters and diffusion parameters as such parameters are being used relatively commonly as secondary or exploratory end points in current phase 1/2 clinical trails of conventional and targeted therapies. Several ongoing initiatives that seek to identify the magnitude of some of the sources of measurement variations are then discussed. Finally, resources being made available through the National Cancer Institute Reference Image Database to Evaluate Response (RIDER) project that might be of use in investigations of quantitative MRI biomarker change analysis are described. These resources include 1) data from phantom-based assessment of system response, including short-term (1 hour) and moderate-term (1 week) contrast response and relaxation time measurement, 2) data obtained from repeated dynamic contrast agent-enhanced MRI studies in intracranial tumors, and 3) data obtained from repeated diffusion MRI studies in both breast and brain. A concluding section briefly discusses issues that must be addressed to allow the transition of MR-based imaging biomarker measures from their current role as secondary/exploratory end points in clinical trials to primary/surrogate markers of response and, ultimately, in clinical application.
Translational oncology 12/2009; 2(4):211-5. · 3.40 Impact Factor
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Michael F McNitt-Gray,
Luc M Bidaut,
Samuel G Armato, Charles R Meyer,
Marios A Gavrielides,
Charles Fenimore,
Geoffrey McLennan,
Nicholas Petrick,
Binsheng Zhao,
Anthony P Reeves,
Reinhard Beichel,
Hyun-Jung Grace Kim,
Lisa Kinnard
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ABSTRACT: This article describes issues and methods that are specific to the measurement of change in tumor volume as measured from computed tomographic (CT) images and how these would relate to the establishment of CT tumor volumetrics as a biomarker of patient response to therapy. The primary focus is on the measurement of lung tumors, but the approach should be generalizable to other anatomic regions.
The first issues addressed are the various sources of bias and variance in the measurement of tumor volumes, which are discussed in the context of measurement variation and its impact on the early detection of response to therapy. RESULTS AND RESOURCES: Research that seeks to identify the magnitude of some of these sources of error is ongoing, and several of these efforts are described herein. In addition, several resources for these investigations are being made available through the National Institutes of Health-funded Reference Image Database to Evaluate Response to therapy in cancer project, and these are described as well. Other measures derived from CT image data that might be predictive of patient response are described briefly, as well as the additional issues that each of these metrics may encounter in real-life applications.
The article concludes with a brief discussion of moving from the assessment of measurement variation to the steps necessary to establish the efficacy of a metric as a biomarker for response.
Translational oncology 12/2009; 2(4):216-22. · 3.40 Impact Factor
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ABSTRACT: We describe methods and issues that are relevant to the measurement of change in tumor uptake of (18)F-fluorodeoxyglucose (FDG) or other radiotracers, as measured from positron emission tomography/computed tomography (PET/CT) images, and how this would relate to the establishment of PET/CT tumor imaging as a biomarker of patient response to therapy. The primary focus is on the uptake of FDG by lung tumors, but the approach can be applied to diseases other than lung cancer and to tracers other than FDG. The first issue addressed is the sources of bias and variance in the measurement of tumor uptake of FDG, and where there are still gaps in our knowledge. These are discussed in the context of measurement variation and how these would relate to the early detection of response to therapy. Some of the research efforts currently underway to identify the magnitude of some of these sources of error are described. In addition, we describe resources for these investigations that are being made available through the Reference Image Database for the Evaluation of Response project. Measures derived from PET image data that might be predictive of patient response as well as the additional issues that each of these metrics may encounter are described briefly. The relationship between individual patient response to therapy and utility for multicenter trials is discussed. We conclude with a discussion of moving from assessing measurement variation to the steps necessary to establish the efficacy of PET/CT imaging as a biomarker for response.
Translational oncology 12/2009; 2(4):223-30. · 3.40 Impact Factor
