The Increasing Spectrum of Indications of Whole-Body MRI Beyond Oncology: Imaging Answers to Clinical Needs.

Whole-body coverage using MRI was developed almost 2 decades ago. The first applications focused on the investigation of the skeleton to detect neoplastic disease, mainly metastases from solid cancers, and involvement by multiple myeloma and lymphoma. But the extensive coverage of the whole musculoskeletal system, combined with the exquisite sensitivity of MRI to tissue alteration in relation to different pathologic conditions, mainly inflammation, has led to the identification of a growing number of indications outside oncology. Seronegative rheumatisms, systemic sclerosis, inflammatory diseases involving muscles or fascias, and multifocal osseous, vascular, or neurologic diseases represent currently validated or emerging indications of whole-body MRI (WB-MRI). We first illustrate the most valuable indications of WB-MRI in seronegative rheumatisms that include providing significant diagnostic information in patients with negative or ambiguous MRI of the sacroiliac joints and the lumbar spine, assessing disease activity in advanced (ankylosed) central disease, and evaluating the peripherally dominant forms of spondyloarthropathy. Then we review the increasing indications of WB-MRI in other rheumatologic and nonneoplastic disorders, underline the clinical needs, and illustrate the role of WB-MRI in the positive diagnosis and evaluation of disease burden, therapeutic decisions, and treatment monitoring.

Development of a systematic computer vision-based method to analyse and compare images of false identity documents for forensic intelligence purposes-Part I: acquisition, calibration and validation issues

Following their detection and seizure by police and border guard authorities, false identity and travel documents are usually scanned, producing digital images. This research investigates the potential of these images to classify false identity documents, highlight links between documents produced by a same modus operandi or same source, and thus support forensic intelligence efforts. Inspired by previous research work about digital images of Ecstasy tablets, a systematic and complete method has been developed to acquire, collect, process and compare images of false identity documents. This first part of the article highlights the critical steps of the method and the development of a prototype that processes regions of interest extracted from images. Acquisition conditions have been fine-tuned in order to optimise reproducibility and comparability of images. Different filters and comparison metrics have been evaluated and the performance of the method has been assessed using two calibration and validation sets of documents, made up of 101 Italian driving licenses and 96 Portuguese passports seized in Switzerland, among which some were known to come from common sources. Results indicate that the use of Hue and Edge filters or their combination to extract profiles from images, and then the comparison of profiles with a Canberra distance-based metric provides the most accurate classification of documents. The method appears also to be quick, efficient and inexpensive. It can be easily operated from remote locations and shared amongst different organisations, which makes it very convenient for future operational applications. The method could serve as a first fast triage method that may help target more resource-intensive profiling methods (based on a visual, physical or chemical examination of documents for instance). Its contribution to forensic intelligence and its application to several sets of false identity documents seized by police and border guards will be developed in a forthcoming article (part II).

Spinal cord injury affects the interplay between visual and sensorimotor representations of the body.

The brain integrates multiple sensory inputs, including somatosensory and visual inputs, to produce a representation of the body. Spinal cord injury (SCI) interrupts the communication between brain and body and the effects of this deafferentation on body representation are poorly understood. We investigated whether the relative weight of somatosensory and visual frames of reference for body representation is altered in individuals with incomplete or complete SCI (affecting lower limbs' somatosensation), with respect to controls. To study the influence of afferent somatosensory information on body representation, participants verbally judged the laterality of rotated images of feet, hands, and whole-bodies (mental rotation task) in two different postures (participants' body parts were hidden from view). We found that (i) complete SCI disrupts the influence of postural changes on the representation of the deafferented body parts (feet, but not hands) and (ii) regardless of posture, whole-body representation progressively deteriorates proportionally to SCI completeness. These results demonstrate that the cortical representation of the body is dynamic, responsive, and adaptable to contingent conditions, in that the role of somatosensation is altered and partially compensated with a change in the relative weight of somatosensory versus visual bodily representations.

Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

Connectivity analysis on diffusion MRI data of the whole- brain suffers from distortions caused by the standard echo- planar imaging acquisition strategies. These images show characteristic geometrical deformations and signal destruction that are an important drawback limiting the success of tractography algorithms. Several retrospective correction techniques are readily available. In this work, we use a digital phantom designed for the evaluation of connectivity pipelines. We subject the phantom to a âeurooetheoretically correctâeuro and plausible deformation that resembles the artifact under investigation. We correct data back, with three standard methodologies (namely fieldmap-based, reversed encoding-based, and registration- based). Finally, we rank the methods based on their geometrical accuracy, the dropout compensation, and their impact on the resulting connectivity matrices.