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Tomography: a Journal for Imaging Research

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https://www.readbyqxmd.com/read/29124128/vascular-deformation-mapping-vdm-of-thoracic-aortic-enlargement-in-aneurysmal-disease-and-dissection
#1
Nicholas S Burris, Benjamin A Hoff, Ella A Kazerooni, Brian D Ross
Thoracic aortic aneurysm is a common and lethal disease that requires regular imaging surveillance to determine timing of surgical repair and prevent major complications such as rupture. Current cross-sectional imaging surveillance techniques, largely based on computed tomography angiography, are focused on measurement of maximal aortic diameter, although this approach is limited to fixed anatomic positions and is prone to significant measurement error. Here we present preliminary results showing the feasibility of a novel technique for assessing change in aortic dimensions, termed vascular deformation mapping (VDM)...
September 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28856247/quantitative-image-quality-comparison-of-reduced-and-standard-dose-dual-energy-multiphase-chest-abdomen-and-pelvis-ct
#2
Mario Buty, Ziyue Xu, Aaron Wu, Mingchen Gao, Chelyse Nelson, Georgios Z Papadakis, Uygar Teomete, Haydar Celik, Baris Turkbey, Peter Choyke, Daniel J Mollura, Ulas Bagci, Les R Folio
We present a new image quality assessment method for determining whether reducing radiation dose impairs the image quality of computed tomography (CT) in qualitative and quantitative clinical analyses tasks. In this Institutional Review Board-exempt study, we conducted a review of 50 patients (male, 22; female, 28) who underwent reduced-dose CT scanning on the first follow-up after standard-dose multiphase CT scanning. Scans were for surveillance of von Hippel-Lindau disease (N = 26) and renal cell carcinoma (N = 10)...
June 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28825039/characterizing-the-influence-of-preload-dosing-on-percent-signal-recovery-psr-and-cerebral-blood-volume-cbv-measurements-in-a-patient-population-with-high-grade-glioma-using-dynamic-susceptibility-contrast-mri
#3
Laura C Bell, Leland S Hu, Ashley M Stokes, Samuel C McGee, Leslie C Baxter, C Chad Quarles
With DSC-MRI, contrast agent leakage effects in brain tumors can either be leveraged for percent signal recovery (PSR) measurements or be adequately resolved for accurate relative cerebral blood volume (rCBV) measurements. Leakage effects can be dimished by administration of a preload dose before imaging and/or specific postprocessing steps. This study compares the consistency of both PSR and rCBV measurements as a function of varying preload doses in a retrospective analysis of 14 subjects with high-grade gliomas...
June 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28825038/dynamic-susceptibility-contrast-mri-at-7-t-tail-scaling-analysis-and-inferences-about-field-strength-dependence
#4
Linda Knutsson, Xiang Xu, Freddy Ståhlberg, Peter B Barker, Emelie Lind, Pia C Sundgren, Peter C M van Zijl, Ronnie Wirestam
Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) following bolus injection of gadolinium contrast agent (CA) is widely used for the estimation of brain perfusion parameters such as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) for both clinical and research purposes. Although it is predicted that DSC-MRI will have superior performance at high magnetic field strengths, to the best of our knowledge, there are no reports of 7 T DSC-MRI in the literature...
June 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28804779/language-mapping-using-t2-prepared-bold-functional-mri-in-the-presence-of-large-susceptibility-artifacts-initial-results-in-patients-with-brain-tumor-and-epilepsy
#5
Jun Hua, Xinyuan Miao, Shruti Agarwal, Chetan Bettegowda, Alfredo Quiñones-Hinojosa, John Laterra, Peter C M Van Zijl, James J Pekar, Jay J Pillai
At present, presurgical functional mapping is the most prevalent clinical application of functional magnetic resonance imaging (fMRI). Signal dropouts and distortions caused by susceptibility effects in the current standard echo planar imaging (EPI)-based fMRI images are well-known problems and pose a major hurdle for the application of fMRI in several brain regions, many of which are related to language mapping in presurgical planning. Such artifacts are particularly problematic in patients with previous surgical resection cavities, craniotomy hardware, hemorrhage, and vascular malformation...
June 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28691102/dce-mri-texture-features-for-early-prediction-of-breast-cancer-therapy-response
#6
Guillaume Thibault, Alina Tudorica, Aneela Afzal, Stephen Y-C Chui, Arpana Naik, Megan L Troxell, Kathleen A Kemmer, Karen Y Oh, Nicole Roy, Neda Jafarian, Megan L Holtorf, Wei Huang, Xubo Song
This study investigates the effectiveness of hundreds of texture features extracted from voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps for early prediction of breast cancer response to neoadjuvant chemotherapy (NAC). In total, 38 patients with breast cancer underwent DCE-MRI before (baseline) and after the first of the 6-8 NAC cycles. Quantitative pharmacokinetic (PK) parameters and semiquantitative metrics were estimated from DCE-MRI time-course data. The residual cancer burden (RCB) index value was computed based on pathological analysis of surgical specimens after NAC completion...
March 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28649664/quantitative-analysis-of-the-spatial-distribution-of-metastatic-brain-lesions
#7
Ted K Yanagihara, Albert Lee, Tony J C Wang
Brain metastases (BMs) are the most common intracranial malignancy and afflict ~10%-20% of patients with cancer. BMs tend to present at the boundaries of gray and white matter because of the distribution of small vessels. In addition, metastases may not be randomly distributed across gross anatomical regions of the brain, but this has not previously been quantified. We retrospectively analyzed a series of 28 patients with recurrent BMs with a total of 150 lesions. Each lesion was manually defined based on T1 gadolinium-enhanced imaging...
March 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28626797/intrathoracic-fat-measurements-using-multidetector-computed-tomography-mdct-feasibility-and-reproducibility
#8
Jadranka Stojanovska, El-Sayed H Ibrahim, Aamer R Chughtai, Elizabeth A Jackson, Barry H Gross, Jon A Jacobson, Alexander Tsodikov, Brian Daneshvar, Benjamin D Long, Thomas L Chenevert, Ella A Kazerooni
Intrathoracic fat volume, more specifically, epicardial fat volume, is an emerging imaging biomarker of adverse cardiovascular events. The purpose of this work is to show the feasibility and reproducibility of intrathoracic fat volume measurement applied to contrast-enhanced multidetector computed tomography images. A retrospective cohort study of 62 subjects free of cardiovascular disease (55% females, age = 49 ± 11 years) conducted from 2008 to 2011 formed the study group. Intrathoracic fat volume was defined as all fat voxels measuring -50 to -250 Hounsfield Unit within the intrathoracic cavity from the level of the pulmonary artery bifurcation to the heart apex...
March 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28584878/a-population-based-digital-reference-object-dro-for-optimizing-dynamic-susceptibility-contrast-dsc-mri-methods-for-clinical-trials
#9
Natenael B Semmineh, Ashley M Stokes, Laura C Bell, Jerrold L Boxerman, C Chad Quarles
The standardization and broad-scale integration of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, we developed a digital reference object (DRO), using physiological and kinetic parameters derived from in vivo data, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach, aimed at validating image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas...
March 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28553660/mri-guided-stereotactic-biopsy-of-murine-gbm-for-spatiotemporal-molecular-genomic-assessment
#10
Stefanie Galbán, Wajd N Al-Holou, Hanxiao Wang, Amanda R Welton, Kevin Heist, Xin Kathy Hu, Roeland Gw Verhaak, Yuan Zhu, Carlos Espinoza, Thomas L Chenevert, Ben A Hoff, Craig J Galbán, Brian D Ross
Brain tumor biopsies that are routinely performed in clinical settings significantly aid in diagnosis and staging. The aim of this study is to develop and evaluate a methodological image-guided approach that would allow for routine sampling of glioma tissue from orthotopic mouse brain tumor models. A magnetic resonance imaging-guided biopsy method is presented to allow for spatially precise stereotaxic sampling of a murine glioma coupled with genome-scale technology to provide unbiased characterization of intra- and intertumoral clonal heterogeneity...
March 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28798963/computational-challenges-and-collaborative-projects-in-the-nci-quantitative-imaging-network
#11
Keyvan Farahani, Jayashree Kalpathy-Cramer, Thomas L Chenevert, Daniel L Rubin, John J Sunderland, Robert J Nordstrom, John Buatti, Nola Hylton
The Quantitative Imaging Network (QIN) of the National Cancer Institute (NCI) conducts research in development and validation of imaging tools and methods for predicting and evaluating clinical response to cancer therapy. Members of the network are involved in examining various imaging and image assessment parameters through network-wide cooperative projects. To more effectively use the cooperative power of the network in conducting computational challenges in benchmarking of tools and methods and collaborative projects in analytical assessment of imaging technologies, the QIN Challenge Task Force has developed policies and procedures to enhance the value of these activities by developing guidelines and leveraging NCI resources to help their administration and manage dissemination of results...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28612050/a-rapid-segmentation-insensitive-digital-biopsy-method-for-radiomic-feature-extraction-method-and-pilot-study-using-ct-images-of-non-small-cell-lung-cancer
#12
Sebastian Echegaray, Viswam Nair, Michael Kadoch, Ann Leung, Daniel Rubin, Olivier Gevaert, Sandy Napel
Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts. We propose a new paradigm, called "digital biopsy," that allows for the collection of intensity- and texture-based features from these regions at least 1 order of magnitude faster than the current manual or semiautomated methods. A radiologist reviewed automated segmentations of lung nodules from 100 preoperative volume computed tomography scans of patients with non-small cell lung cancer, and manually adjusted the nodule boundaries in each section, to be used as a reference standard, requiring up to 45 minutes per nodule...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28480331/comparison-between-3-scan-trace-and-diagonal-body-diffusion-weighted-imaging-acquisitions-a-phantom-and-volunteer-study
#13
Stefanie J Hectors, Mathilde Wagner, Idoia Corcuera-Solano, Martin Kang, Alto Stemmer, Michael A Boss, Bachir Taouli
Diagonal diffusion-weighted imaging (dDWI) uses simultaneous maximized application of 3 orthogonal gradient systems as opposed to sequential acquisition in 3 directions in conventional 3-scan trace DWI (tDWI). Several theoretical advantages of dDWI vs. tDWI include reduced artifacts and increased sharpness. We compared apparent diffusion coefficient (ADC) quantification and image quality between monopolar dDWI and tDWI in a dedicated diffusion phantom (b = 0/500/900/2000 s/mm(2)) and in the abdomen (b = 50/400/800 s/mm(2)) and pelvis (b = 50/1000/1600 s/mm(2)) of 2 male volunteers at 1...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28286871/semiautomated-workflow-for-clinically-streamlined-glioma-parametric-response-mapping
#14
Lauren Keith, Brian D Ross, Craig J Galbán, Gary D Luker, Stefanie Galbán, Binsheng Zhao, Xiaotao Guo, Thomas L Chenevert, Benjamin A Hoff
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...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28149958/radiomics-of-lung-nodules-a-multi-institutional-study-of-robustness-and-agreement-of-quantitative-imaging-features
#15
Jayashree Kalpathy-Cramer, Artem Mamomov, Binsheng Zhao, Lin Lu, Dmitry Cherezov, Sandy Napel, Sebastian Echegaray, Daniel Rubin, Michael McNitt-Gray, Pechin Lo, Jessica C Sieren, Johanna Uthoff, Samantha K N Dilger, Brandan Driscoll, Ivan Yeung, Lubomir Hadjiiski, Kenny Cha, Yoganand Balagurunathan, Robert Gillies, Dmitry Goldgof
Radiomics is to provide quantitative descriptors of normal and abnormal tissues during classification and prediction tasks in radiology and oncology. Quantitative Imaging Network members are developing radiomic "feature" sets to characterize tumors, in general, the size, shape, texture, intensity, margin, and other aspects of the imaging features of nodules and lesions. Efforts are ongoing for developing an ontology to describe radiomic features for lung nodules, with the main classes consisting of size, local and global shape descriptors, margin, intensity, and texture-based features, which are based on wavelets, Laplacian of Gaussians, Law's features, gray-level co-occurrence matrices, and run-length features...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28127586/accrual-patterns-for-clinical-studies-involving-quantitative-imaging-results-of-an-nci-quantitative-imaging-network-qin-survey
#16
Brenda F Kurland, Sameer Aggarwal, Thomas E Yankeelov, Elizabeth R Gerstner, James M Mountz, Hannah M Linden, Ella F Jones, Kellie L Bodeker, John M Buatti
Patient accrual is essential for the success of oncology clinical trials. Recruitment for trials involving the development of quantitative imaging biomarkers may face different challenges than treatment trials. This study surveyed investigators and study personnel for evaluating accrual performance and perceived barriers to accrual and for soliciting solutions to these accrual challenges that are specific to quantitative imaging-based trials. Responses for 25 prospective studies were received from 12 sites...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28111634/temporal-feature-extraction-from-dce-mri-to-identify-poorly-perfused-subvolumes-of-tumors-related-to-outcomes-of-radiation-therapy-in-head-and-neck-cancer
#17
Daekeun You, Madhava Aryal, Stuart E Samuels, Avraham Eisbruch, Yue Cao
This study aimed to develop an automated model to extract temporal features from DCE-MRI in head-and-neck (HN) cancers to localize significant tumor subvolumes having low blood volume (LBV) for predicting local and regional failure after chemoradiation therapy. Temporal features were extracted from time-intensity curves to build classification model for differentiating voxels with LBV from those with high BV. Support vector machine (SVM) classification was trained on the extracted features for voxel classification...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28105470/bladder-cancer-segmentation-in-ct-for-treatment-response-assessment-application-of-deep-learning-convolution-neural-network-a-pilot-study
#18
COMMENT
Kenny H Cha, Lubomir M Hadjiiski, Ravi K Samala, Heang-Ping Chan, Richard H Cohan, Elaine M Caoili, Chintana Paramagul, Ajjai Alva, Alon Z Weizer
Assessing the response of bladder cancer to neoadjuvant chemotherapy is crucial for reducing morbidity and increasing quality of life of patients. Changes in tumor volume during treatment is generally used to predict treatment outcome. We are developing a method for bladder cancer segmentation in CT using a pilot data set of 62 cases. 65 000 regions of interests were extracted from pre-treatment CT images to train a deep-learning convolution neural network (DL-CNN) for tumor boundary detection using leave-one-case-out cross-validation...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28105469/qin-dawg-validation-of-gradient-nonlinearity-bias-correction-workflow-for-quantitative-diffusion-weighted-imaging-in-multicenter-trials
#19
Dariya I Malyarenko, Lisa J Wilmes, Lori R Arlinghaus, Michael A Jacobs, Wei Huang, Karl G Helmer, Bachir Taouli, Thomas E Yankeelov, David Newitt, Thomas L Chenevert
Previous research has shown that system-dependent gradient nonlinearity (GNL) introduces a significant spatial bias (nonuniformity) in apparent diffusion coefficient (ADC) maps. Here, the feasibility of centralized retrospective system-specific correction of GNL bias for quantitative diffusion-weighted imaging (DWI) in multisite clinical trials is demonstrated across diverse scanners independent of the scanned object. Using corrector maps generated from system characterization by ice-water phantom measurement completed in the previous project phase, GNL bias correction was performed for test ADC measurements from an independent DWI phantom (room temperature agar) at two offset locations in the bore...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28105468/simulating-the-effect-of-spectroscopic-mri-as-a-metric-for-radiation-therapy-planning-in-patients-with-glioblastoma
#20
J Scott Cordova, Shravan Kandula, Saumya Gurbani, Jim Zhong, Mital Tejani, Oluwatosin Kayode, Kirtesh Patel, Roshan Prabhu, Eduard Schreibmann, Ian Crocker, Chad A Holder, Hyunsuk Shim, Hui-Kuo Shu
Due to glioblastoma's infiltrative nature, an optimal radiation therapy (RT) plan requires targeting infiltration not identified by anatomical magnetic resonance imaging (MRI). Here, high-resolution, whole-brain spectroscopic MRI (sMRI) is used to describe tumor infiltration alongside anatomical MRI and simulate the degree to which it modifies RT target planning. In 11 patients with glioblastoma, data from preRT sMRI scans were processed to give high-resolution, whole-brain metabolite maps normalized by contralateral white matter...
December 2016: Tomography: a Journal for Imaging Research
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