Computed tomographic (CT) colonography is a noninvasive option in screening for colorectal cancer. However, its accuracy as a screening tool in asymptomatic adults has not been well defined.
We ...recruited 2600 asymptomatic study participants, 50 years of age or older, at 15 study centers. CT colonographic images were acquired with the use of standard bowel preparation, stool and fluid tagging, mechanical insufflation, and multidetector-row CT scanners (with 16 or more rows). Radiologists trained in CT colonography reported all lesions measuring 5 mm or more in diameter. Optical colonoscopy and histologic review were performed according to established clinical protocols at each center and served as the reference standard. The primary end point was detection by CT colonography of histologically confirmed large adenomas and adenocarcinomas (10 mm in diameter or larger) that had been detected by colonoscopy; detection of smaller colorectal lesions (6 to 9 mm in diameter) was also evaluated.
Complete data were available for 2531 participants (97%). For large adenomas and cancers, the mean (+/-SE) per-patient estimates of the sensitivity, specificity, positive and negative predictive values, and area under the receiver-operating-characteristic curve for CT colonography were 0.90+/-0.03, 0.86+/-0.02, 0.23+/-0.02, 0.99+/-<0.01, and 0.89+/-0.02, respectively. The sensitivity of 0.90 (i.e., 90%) indicates that CT colonography failed to detect a lesion measuring 10 mm or more in diameter in 10% of patients. The per-polyp sensitivity for large adenomas or cancers was 0.84+/-0.04. The per-patient sensitivity for detecting adenomas that were 6 mm or more in diameter was 0.78.
In this study of asymptomatic adults, CT colonographic screening identified 90% of subjects with adenomas or cancers measuring 10 mm or more in diameter. These findings augment published data on the role of CT colonography in screening patients with an average risk of colorectal cancer. (ClinicalTrials.gov number, NCT00084929; American College of Radiology Imaging Network ACRIN number, 6664.)
With the rapid development of spaceborne imaging techniques, object detection in optical remote sensing imagery has drawn much attention in recent decades. While many advanced works have been ...developed with powerful learning algorithms, the incomplete feature representation still cannot meet the demand for effectively and efficiently handling image deformations, particularly objective scaling and rotation. To this end, we propose a novel object detection framework, called Optical Remote Sensing Imagery detector (ORSIm detector), integrating diverse channel features extraction, feature learning, fast image pyramid matching, and boosting strategy. An ORSIm detector adopts a novel spatial-frequency channel feature (SFCF) by jointly considering the rotation-invariant channel features constructed in the frequency domain and the original spatial channel features (e.g., color channel and gradient magnitude). Subsequently, we refine SFCF using learning-based strategy in order to obtain the high-level or semantically meaningful features. In the test phase, we achieve a fast and coarsely scaled channel computation by mathematically estimating a scaling factor in the image domain. Extensive experimental results conducted on the two different airborne data sets are performed to demonstrate the superiority and effectiveness in comparison with the previous state-of-the-art methods.
Manual palpation has been used for centuries to provide a relative indication of tissue health and disease. Engineers have sought to make these assessments increasingly quantitative and accessible ...within daily clinical practice. Since many of the developed techniques involve image-based quantification of tissue deformation in response to an applied force (i.e., “elastography”), such approaches fall squarely within the domain of the radiologist. While commercial elastography analysis software is becoming increasingly available for clinical use, the internal workings of these packages often remain a “black box,” with limited guidance on how to usefully apply the methods toward a meaningful diagnosis. The purpose of the present review article is to introduce some important approaches to elastography that have been developed for the most widely used clinical imaging modalities (e.g., ultrasound, MRI), to provide a basic sense of the underlying physical principles, and to discuss both current and potential (musculoskeletal) applications. The article also seeks to provide a perspective on emerging approaches that are rapidly developing in the research laboratory (e.g., optical coherence tomography, fibered confocal microscopy), and which may eventually gain a clinical foothold.
Objectives The purpose of this study was to compare the efficiency, cost, and safety of a diagnostic strategy employing early coronary computed tomographic angiography (CCTA) to a strategy employing ...rest-stress myocardial perfusion imaging (MPI) in the evaluation of acute low-risk chest pain. Background In the United States, >8 million patients require emergency department evaluation for acute chest pain annually at an estimated diagnostic cost of >$10 billion. Methods This multicenter, randomized clinical trial in 16 emergency departments ran between June 2007 and November 2008. Patients were randomly allocated to CCTA (n = 361) or MPI (n = 338) as the index noninvasive test. The primary outcome was time to diagnosis; the secondary outcomes were emergency department costs of care and safety, defined as freedom from major adverse cardiac events in patients with normal index tests, including 6-month follow-up. Results The CCTA resulted in a 54% reduction in time to diagnosis compared with MPI (median 2.9 h 25th to 75th percentile: 2.1 to 4.0 h vs. 6.3 h 25th to 75th percentile: 4.2 to 19.0 h, p < 0.0001). Costs of care were 38% lower compared with standard (median $2,137 25th to 75th percentile: $1,660 to $3,077 vs. $3,458 25th to 75th percentile: $2,900 to $4,297, p < 0.0001). The diagnostic strategies had no difference in major adverse cardiac events after normal index testing (0.8% in the CCTA arm vs. 0.4% in the MPI arm, p = 0.29). Conclusions In emergency department acute, low-risk chest pain patients, the use of CCTA results in more rapid and cost-efficient safe diagnosis than rest-stress MPI. Further studies comparing CCTA to other diagnostic strategies are needed to optimize evaluation of specific patient subsets. (Coronary Computed Tomographic Angiography for Systematic Triage of Acute Chest Pain Patients to Treatment CT-STAT; NCT00468325 )
•We compared meta-analyses of movement imagery, observation, and execution.•Subcortical structures were most commonly associated with imagery and execution.•Conjunctions identified a consistent ...premotor-parietal-somatosensory network.•These data inform basic and translational work using imagery and observation.
Several models propose Motor Imagery, Action Observation, and Movement Execution recruit the same brain regions. There is, however, no quantitative synthesis of the literature that directly compares their respective networks. Here we summarized data from neuroimaging experiments examining Motor Imagery (303 experiments, 4902 participants), Action Observation (595 experiments, 11,032 participants), and related control tasks involving Movement Execution (142 experiments, 2302 participants). Comparisons across these networks showed that Motor Imagery and Action Observation recruited similar premotor-parietal cortical networks. However, while Motor Imagery recruited a similar subcortical network to Movement Execution, Action Observation did not consistently recruit any subcortical areas. These data quantify and amend previous models of the similarities in the networks for Motor Imagery, Action Observation, and Movement Execution, while highlighting key differences in their recruitment of motor cortex, parietal cortex, and subcortical structures.
This article develops and examines methods for the production of real-world, very high-resolution imagery using a high-frequency drone-borne synthetic aperture radar (SAR) operating at short ranges. ...The significance of motion errors which lead to space-invariant/variant phase errors is discussed. Subsequently, an imaging algorithm capable of handling these errors is proposed and presented. The validity of the approach is tested through both simulation and experiment. We present novel short-range, fine-resolution imagery (less than 2 cm in cross-range) of an extended target area generated using a low-cost, drone-borne vehicular frequency-modulated continuous-wave (FMCW) radar operating at 77 GHz, without using a dedicated inertial navigation system (INS) or Global Positioning System (GPS).
Recent multi-voxel pattern classification (MVPC) studies have shown that in early visual cortex patterns of brain activity generated during mental imagery are similar to patterns of activity ...generated during perception. This finding implies that low-level visual features (e.g., space, spatial frequency, and orientation) are encoded during mental imagery. However, the specific hypothesis that low-level visual features are encoded during mental imagery is difficult to directly test using MVPC. The difficulty is especially acute when considering the representation of complex, multi-object scenes that can evoke multiple sources of variation that are distinct from low-level visual features. Therefore, we used a voxel-wise modeling and decoding approach to directly test the hypothesis that low-level visual features are encoded in activity generated during mental imagery of complex scenes. Using fMRI measurements of cortical activity evoked by viewing photographs, we constructed voxel-wise encoding models of tuning to low-level visual features. We also measured activity as subjects imagined previously memorized works of art. We then used the encoding models to determine if putative low-level visual features encoded in this activity could pick out the imagined artwork from among thousands of other randomly selected images. We show that mental images can be accurately identified in this way; moreover, mental image identification accuracy depends upon the degree of tuning to low-level visual features in the voxels selected for decoding. These results directly confirm the hypothesis that low-level visual features are encoded during mental imagery of complex scenes. Our work also points to novel forms of brain–machine interaction: we provide a proof-of-concept demonstration of an internet image search guided by mental imagery.
•A model of representation in early visual cortex decodes mental images of complex scenes.•Mental imagery depends directly upon the encoding of low-level visual features.•Low-level visual features of mental images are encoded by activity in early visual cortex.•Depictive theories of mental imagery are strongly supported by our results.•Brain activity evoked by mental imagery can be used to guide internet image search.
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