Radiology | EPFL Graph Search

Radiology (,reidI'Ql@dZi ) is the medical discipline that uses medical imaging to diagnose diseases and guide their treatment, within the bodies of humans and other animals. It began with radiography (which is why its name has a root referring to radiation), but today it includes all imaging modalities, including those that use no electromagnetic radiation (such as ultrasonography and magnetic resonance imaging), as well as others that do, such as computed tomography (CT), fluoroscopy, and nuclear medicine including positron emission tomography (PET). Interventional radiology is the performance of usually minimally invasive medical procedures with the guidance of imaging technologies such as those mentioned above. The modern practice of radiology involves several different healthcare professions working as a team. The radiologist is a medical doctor who has completed the appropriate post-graduate training and interprets medical images, communicates these findings to other physician

Using medical images acquired during routine clinical care for research purposes: a comprehensive medical informatics approach applied to the study of brain development from birth through 2 years of age as indexed by diffusion MRI

Vincent Alexis Roch

Biologic variability and dramatic changes of brain development in children aged 0 to 2 years make it challenging to accurately detect subtle abnormalities in single Magnetic Resonance Imaging (MRI) scans. Diffusion MRI (dMRI) indices such as Apparent Diffusion Coefficient (ADC) are reliable measures of water content in the brain and thus an excellent surrogate marker for brain development. Developing robust age-specific diffusion biomarkers for quantitative measurement of normative brain evolution would enhance our ability to detect subtle alterations due to tissue injuries or neuropathological disorders. Obtaining significant numbers of normative MRI scans for this age group means redirecting clinical data from hospital databases for research purposes. Therefore, this pilot project demonstrates the feasibility of identifying, retrieving and analyzing pediatric clinical dMRI data to investigate normal brain development from birth to 2 years. Research Patient Data Registry (RPDR) at Massachusetts General Hospital (MGH) was used to collect patient medical information and identify healthy children according to radiology reports. Corresponding MRI data were retrieved from MGH Picture Archiving and Communication System (PACS) using the prototype of Medical Imaging Informatics Bench to Bedside (mi2b2) software. A specific pipeline was created to handle the volume of studies and extract technical scan information used to identify comparable diffusion series; 193 studies were used for analysis. Two markers, whole brain average of ADC and Fractional Anisotropy (FA) values (WBAADC and WBAFA), were computed for each patient, their age-evolution across patients was investigated with different models. WBAADC and WBAFA seem to exhibit biexponential decay and increase respectively and might be gender-specific. These results have clinical implications for potentially determining the health status of an unknown individual, and research utility for continued development of these tools.

2011

Gray-matter-specific MR imaging improves the detection of epileptogenic zones in focal cortical dysplasia: A new sequence called fluid and white matter suppression (FLAWS)

Xin Chen, Nan Chen, Tobias Kober, Thomas Yu

Objectives: To evaluate the diagnostic value and characteristic features of FCD epileptogenic zones using a novel sequence called fluid and white matter suppression (FLAWS). Materials and methods: Thirty-nine patients with pathologically confirmed FCD and good surgery outcomes (class I or II, according to the Engel Epilepsy Surgery Outcome Scale) were retrospectively included in the study. All the patients underwent a preoperative whole-brain MRI examination that included conventional sequences (T2WI, T1WI, two-dimensional (2D) axial, coronal fluid-attenuated inversion recovery [FLAIR]) and FLAWS. An additional 3D-FLAIR MRI sequence was performed in 17 patients. To evaluate the sensitivity and specificity of FLAWS and investigate the cause of false-positives, 36 healthy volunteers were recruited as normal controls. Two radiologists evaluated all the image data. The detection rates of the FCD epileptogenic zone on different sequences were compared based on five criteria: abnormal cortical morphology (thickening, thinning, or abnormally deep sulcus); abnormal cortical signal intensity; blurred gray-white matter junction; abnormal signal intensity of the subcortical white matter, and the transmantle sign. The sensitivity and specificity of FLAWS for detecting the FCD lesions were calculated with the reviewers blinded to all the clinical information, i.e. to the patient identity and the location of the resected regions. To explore how many features were sufficient for the diagnosis of the epileptogenic zones, the frequency of each criterion in the resected regions and their combinations were assessed on FLAWS, according to the results of the assessment when the reviewers were aware of the location of the resected regions. Based on the findings of the 17 patients with an additional 3D-FLAIR scan when the reviewers were aware of the location of the resected regions, quantitative analysis of the regions of interest was used to compare the tissue contrast among 2D-axial FLAIR, 3D-FLAIR, and the FLAWS sequence. Visualization score analysis was used to evaluate the visualization of the five features on conventional, 3D-FLAIR, and FLAWS images. Finally, to explore the reason for false-positive results, a further evaluation of the whole brain FLAWS images was conducted for all the subjects. Results: The sensitivity and specificity for detecting the FCD lesions on the FLAWS sequence were 71.9% and 71.1%, respectively. When the reviewers were blinded to the location of the resected regions, the detection rate of the FLAWS sequence was significantly higher than that of the conventional sequences (P = 0.00). In the 17 patients who underwent an additional 3D FLAIR scan, no statistically significant difference was found between the FLAWS and the 3D-FLAIR (P = 0.25). All the patients had at least two imaging features, one of which was "the blurred junction of the gray-white matter." The transmantle sign, which is widely believed to be a specific feature of FCD type II, could also be observed in type I on the FLAWS sequence. The relative tissue contrast of FLAWS was higher than that of the 2D-FLAIR with respect to lesion/white matter (WM), deep gray matter (GM)/WM, and cortex/WM (P = 0.00 for all three measures) and higher than that of the 3D-FLAIR with respect to the lesion/WM (P = 0.01). The visualization score analysis showed that the visualization of FLAWS was more enhanced than that of the conventional and 3D-FLAIR images with respect to the blurred junction (P = 0.00 for both comparisons) and the abnormal signal intensity of the subcortical white matter (P = 0.01 for both comparisons). The thin-threadlike signal and individual FCD features outside the epileptogenic regions were considered the primary cause of the false-positive results of FLAWS. Conclusions: FLAWS can help in the detection of FCD epileptogenic zones. It is recommended that epileptogenic zone on FLAWS be diagnosed based on a combination of two features, one of which should be the "blurred junction of the gray-white matter" in types I and II. In type III, the combination of "the blurred junction of the gray-white matter" with "abnormal signal intensity of subcortical white matter" is recommended.

ELSEVIER SCI LTD2018

Vincent Alexis Roch

2011

Gray-matter-specific MR imaging improves the detection of epileptogenic zones in focal cortical dysplasia: A new sequence called fluid and white matter suppression (FLAWS)

Xin Chen, Nan Chen, Tobias Kober, Thomas Yu

ELSEVIER SCI LTD2018