2019 March - 27 articles
This issue of Tomography is a collection of articles derived from over 20 research teams which comprise the Quantitative Imaging Network (QIN) of the National Institutes of Health (NIH).[...]
The Quantitative Imaging Network of the National Cancer Institute is in its 10th year of operation, and research teams within the network are developing and validating clinical decision support software tools to measure or predict the response of can...
Noninvasive imaging methods are sought to objectively predict early response to therapy for high-grade glioma tumors. Quantitative metrics derived from diffusion-weighted imaging, such as apparent diffusion coefficient (ADC), have previously shown pr...
The aim of this study was to establish the repeatability measures of quantitative Gaussian and non-Gaussian diffusion metrics using diffusion-weighted imaging (DWI) data from phantoms and patients with head-and-neck and papillary thyroid cancers. The...
We assessed a priori aggressive features using quantitative diffusion-weighted imaging metrics to preclude an active surveillance management approach in patients with papillary thyroid cancer (PTC) with tumor size 1–2 cm. This prospective study enrol...
Quantitative kurtosis phantoms are sought by multicenter clinical trials to establish accuracy and precision of quantitative imaging biomarkers on the basis of diffusion kurtosis imaging (DKI) parameters. We designed and evaluated precision, reproduc...
Repeatability and reproducibility of magnetization transfer magnetic resonance imaging of the breast, and the ability of this technique to assess the response of locally advanced breast cancer to neoadjuvant therapy (NAT), are determined. Reproducibi...
Histone deacetylases regulate a wide variety of cellular functions and have been implicated in redifferentiation of various tumors. Histone deacetylase inhibitors (HDACi) are potential pharmacologic agents to improve outcomes for patients with glioma...
Accuracy and precision of quantitative imaging (QI) metrics should be assessed in real time in each patient during a clinical trial to support QI-based decision-making. We developed a framework for real-time quantitative assessment of QI metrics and...
Prostate cancer identification and assessment of clinical significance continues to be a challenge. Routine multiparametric magnetic resonance imaging has shown to be useful in assessing disease progression. Although dynamic contrast-enhanced imaging...
Accurate, patient-specific measurement of arterial input functions (AIF) may improve model-based analysis of vascular permeability. This study investigated factors affecting AIF measurements from magnetic resonance imaging (MRI) magnitude (AIFMAGN) a...
We aimed to determine whether multiresolution fractal analysis of voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps can provide early prediction of breast cancer response to neoadjuvant chemotherapy (NACT). In...
This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data...
The use of rCBV as a response metric in clinical trials has been hampered, in part, due to variations in the biomarker consistency and associated interpretation across sites, stemming from differences in image acquisition and post-processing methods....
Quantitative mapping of hyperperfused and hypercellular regions of glioblastoma has been proposed to improve definition of tumor regions at risk for local recurrence following conventional radiation therapy. As the processing of the multiparametric d...
Prostate cancer is the most common noncutaneous cancer in men in the United States. The current paradigm for screening and diagnosis is imperfect, with relatively low specificity, high cost, and high morbidity. This study aims to generate new image c...
Standard-of-care multiparameter magnetic resonance imaging (MRI) scans of the brain were used to objectively subdivide glioblastoma multiforme (GBM) tumors into regions that correspond to variations in blood flow, interstitial edema, and cellular den...
We identified computational imaging features on 18F-fluorodeoxyglucose positron emission tomography (PET) that predict recurrence/progression in non–small cell lung cancer (NSCLC). We retrospectively identified 291 patients with NSCLC from 2 prospect...
The use of computed tomography (CT) images to correct for photon attenuation in positron emission tomography (PET) produces unbiased patient images, but it is not optimal for synthetic materials. For test objects made from epoxy, image bias and artif...
Radiomics is an image analysis approach for extracting large amounts of quantitative information from medical images using a variety of computational methods. Our goal was to evaluate the utility of radiomic feature analysis from 18F-fluorothymidine...
Medical imaging is critical for assessing the response of patients to new cancer therapies. Quantitative lesion assessment on images is time-consuming, and adopting new promising quantitative imaging biomarkers of response in clinical trials is chall...
Glioblastoma has poor prognosis with inevitable local recurrence despite aggressive treatment with surgery and chemoradiation. Radiation therapy (RT) is typically guided by contrast-enhanced T1-weighted magnetic resonance imaging (MRI) for defining t...
Quantitative features are generated from a tumor phenotype by various data characterization, feature-extraction approaches and have been used successfully as a biomarker. These features give us information about a nodule, for example, nodule size, pi...
We compared the performance of different Deep learning-convolutional neural network (DL-CNN) models for bladder cancer treatment response assessment based on transfer learning by freezing different DL-CNN layers and varying the DL-CNN structure. Pre-...
Quantitative kinetic parameters derived from dynamic contrast-enhanced (DCE) data are dependent on signal measurement quality and choice of pharmacokinetic model. However, the fundamental optimization analysis method is equally important and its impa...
Quantitative imaging biomarkers are increasingly used in oncology clinical trials to assist the evaluation of tumor responses to novel therapies. To identify these biomarkers and ensure smooth clinical translation once they have been validated, it is...
We studied the reliability of radiomic features on abdominal computed tomography (CT) images reconstructed with multiple CT image acquisition settings using the ACR (American College of Radiology) CT Phantom. Twenty-four sets of CT images of the ACR...
Get Alerted
Add your email address to receive forthcoming issues of this journal.
