Impact of Head-Down Position on Cerebral Blood Flow in Healthy Subjects: An Arterial Spin-Labeling MR Perfusion Study.

BACKGROUND: A head-down (HD) position is used in some stroke centers to maintain cerebral perfusion (CP) in stroke patients. PURPOSE: To assess CP in healthy volunteers in the supine and HD (-15°) positions. STUDY TYPE: Prospective. POPULATION: Eighteen healthy subjects of 53 (±8) years old. FIELD STRENGTH/SEQUENCE: 1.5T / arterial spin-labeling (ASL) in the supine position and after 4 minutes of HD position. ASSESSMENT: Regions of interest from reconstructed cerebral blood-flow (CBF) maps: subcortical nuclear gray matter (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus), cortical gray matter (cGM), and white matter (WM). We also monitored hemodynamic parameters. STATISTICAL TESTS: Shapiro-Wilk test, analysis of variance (ANOVA) tests, Student's t-tests, and Pearson correlation analysis. RESULTS: CBF was higher in women compared to men, whatever the position (mean difference of 17% in supine, and 13% in HD position). From supine to HD position, CBF was decreased in all regions (mean decrease of -7%). Simultaneously, mean arterial pressure and systolic blood pressure increased (respectively P = 0.004 and P < 0.001). DATA CONCLUSION: The CBF decrease, despite increased hemodynamic parameters, may indicate efficient cerebral autoregulation. Our results seem to reflect only early cerebral autoregulation stages but may open the way towards a more precise understanding of CP. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:218-224.

Measuring Cerebral Hypoperfusion Induced by Hyperventilation Challenge With Intravoxel Incoherent Motion Magnetic Resonance Imaging in Healthy Volunteers.

OBJECTIVES: The aim of this study was to demonstrate the feasibility to assess cerebral hypoperfusion with a hyperventilation (HV) challenge protocol using intravoxel incoherent motion (IVIM) magnetic resonance imaging. MATERIALS AND METHODS: Magnetic resonance imaging experiments were performed on 10 healthy volunteers at 1.5 T, with a diffusion IVIM magnetic resonance imaging protocol using a set of b-values optimized by Cramer-Rao Lower Bound analysis. Hypoperfusion was induced by an HV maneuver. Measurements were performed in normoventilation and HV conditions. Biexponential curve fitting was used to obtain the perfusion fraction (f), pseudodiffusion coefficient (D*), and the product fD* in gray matter (GM) regions of interest (ROIs). Regional cerebral blood flow in the same ROIs was also assessed with arterial spin labeling. RESULTS: The HV challenge led to a diminution of IVIM perfusion-related parameters, with a decrease of f and fD* in the cerebellum (P = 0.03 for f; P = 0.01 for fD*), thalamus GM (P = 0.09 for f; P = 0.01 for fD*), and lenticular nuclei (P = 0.03 for f; P = 0.02 for fD*). Mean GM cerebral blood flow (in mL/100 g tissue/min) measured with arterial spin labeling averaged over all ROIs also decreased (normoventilation: 42.7 ± 4.1 vs HV: 33.2 ± 2.2, P = 0.004) during the HV challenge. CONCLUSIONS: The optimized IVIM protocol proposed in the current study allows for measurements of cerebral hypoperfusion that might be of great interest for pathologies diagnosis such as ischemic stroke.

Diffusional kurtosis imaging (DKI) incorporation into an intravoxel incoherent motion (IVIM) MR model to measure cerebral hypoperfusion induced by hyperventilation challenge in healthy subjects.

OBJECTIVES: The objectives were to investigate the diffusional kurtosis imaging (DKI) incorporation into the intravoxel incoherent motion (IVIM) model for measurements of cerebral hypoperfusion in healthy subjects. MATERIALS AND METHODS: Eight healthy subjects underwent a hyperventilation challenge with a 4-min diffusion weighted imaging protocol, using 8 b values chosen with the Cramer-Rao Lower Bound optimization approach. Four regions of interest in gray matter (GM) were analyzed with the DKI-IVIM model and the bi-exponential IVIM model, for normoventilation and hyperventilation conditions. RESULTS: A significant reduction in the perfusion fraction (f) and in the product fD* of the perfusion fraction with the pseudodiffusion coefficient (D*) was found with the DKI-IVIM model, during the hyperventilation challenge. In the cerebellum GM, the percentage changes were f: -43.7 ± 40.1, p = 0.011 and fD*: -50.6 ± 32.1, p = 0.011; in thalamus GM, f: -47.7 ± 34.7, p = 0.012 and fD*: -47.2 ± 48.7, p = 0.040. In comparison, using the bi-exponential IVIM model, only a significant decrease in the parameter fD* was observed for the same regions of interest. In frontal-GM and posterior-GM, the reduction in f and fD* did not reach statistical significance, either with DKI-IVIM or the bi-exponential IVIM model. CONCLUSION: When compared to the bi-exponential IVIM model, the DKI-IVIM model displays a higher sensitivity to detect changes in perfusion induced by the hyperventilation condition.

MRI investigation of radiating pain in the lower limbs: value of an additional sequence dedicated to the lumbosacral plexus and pelvic girdle.

OBJECTIVE: In some cases, sciatica-like symptoms radiating through the buttock, anterior thigh, or leg result from spinal root compression in an extraspinal location or from injury to the pelvic girdle. It has been suggested that adding a coronal STIR sequence dedicated to the lumbosacral plexus and pelvis to the routine MRI protocol can provide a good depiction of disorders of this type. MATERIALS AND METHODS: Two hundred nine patients with sciatica-like symptoms of suspected lumbar origin were included in the study. Disorders responsible for symptoms involving extraspinal compression of the lumbosacral plexus or pelvic girdle were retrospectively noted and correlated with age, sex, location of pain, referring physician, presence of discoradicular impingement liable to explain symptoms, and history of neoplasia. RESULTS: An extraspinal cause of symptoms was depicted in 12 cases (5.7%), including three cases of extraspinal compression and nine differential diagnoses in the pelvic region. Prevalence of an extraspinal cause of pain was significantly correlated with the absence of discoradicular impingement in the spine (p=0.046). A higher prevalence of extraspinal compression of the lumbosacral plexus (p=0.029) was seen in patients 60 years old or older, whereas no other feature was statistically associated with an extraspinal cause of pain. CONCLUSION: Because of its short acquisition time and subsequent low cost, the additional coronal STIR sequence should be performed in the routine MRI investigation of sciatica-like symptoms when no discoradicular impingement is seen in the spine to depict an extraspinal cause of symptoms.

Snapping knee: imaging findings with an emphasis on dynamic sonography.

OBJECTIVE: The purpose of this article is to illustrate the causes of snapping knee. The value of imaging techniques is discussed with an emphasis on dynamic sonography in light of the available surgical and radiologic literature. CONCLUSION: Because of its dynamic capabilities, dynamic sonography provides real-time visualization of snapping knee syndrome and may be used as a first-line modality.

MRI image artifact ontology: a proposed method for improved recognition.

UNLABELLED: Magnetic Resonance Imaging is an essential diagnostic imaging technique. The complexity of interpreting MRI images is often compounded by the presence of a wide range of artifacts which are often challenging to identify and eliminate. Ontology permits the construction of a knowledge database with which users can interact given an appropriate interface. The goal of this work is to create an interactive tool for the ontology of MRI artifacts that will allow a radiologist to compare any given MRI artifact image with those contained in the ontology. MATERIAL AND METHOD: Using Protégé 4, we have constructed the ontology with input from an expert in MRI artifacts and utilizing images exemplifying such artifacts. The graphical user interface has been built in Java and the linkage with the ontology made with Owl API. RESULTS: Using the tool, users can compare imaging artifacts encountered in daily practice to those in the database. Once a user has identified the image the most similar to their own, they then have instantaneous access to the knowledge contained in the ontology about the artifact. Individual users can also submit images and have access to DICOM data.

Ontology driven decision support systems for medical diagnosis - an interactive form for consultation in patients with plasma cell disease.

Multiple myeloma (MM) is a malignant disorder characterized by the monoclonal proliferation of B cell derived plasma cells in the bone marrow. The diagnosis depends on the identification of abnormal monoclonal marrow plasma cells, monoclonal protein in the serum or urine, evidence of end-organ damage, and a clinical picture consistent with MM. The distinction between MM stages- monoclonal gammopathy of undetermined significance or indolent myeloma-is critical in guiding therapy. This paper describes how to produce ontology-driven semiological rules base (SRB) and a consultation form to aid in the diagnosis of plasma cells diseases. We have extracted the MM sub-ontology from the NCI Thesaurus. Using Protégé 3.4.2 and owl1, criteria in the literature for the diagnosis and staging of MM have been added to the ontology. All quantitative parameters have been transformed to a qualitative format. A formal description of MM variants and stages has been given. The obtained ontology has been checked by a reasoner and instantiated to obtain a SRB. The form created has been tested and evaluated utilizing 63 clinical medical reports. The likelihood for a disease being the correct diagnosis is determined by computing a ratio. The resulting tool is relevant for MM diagnosis and staging.

Texture analysis software: integration with a radiological workstation.

Image analysis is the daily task of radiologists. The texture of a structure or imaging finding can be more difficult to describe than other parameters. Image processing can help the radiologist in completing this difficult task. The aim of this article is to explain how we have developed texture analysis software and integrated it into a standard radiological workstation. The texture analysis method has been divided into three steps: definition of primitive elements, counting, and statistical analysis. The software was developed in C++ and integrated into a Siemens workstation with a graphical user interface. The results of analyses may be exported in Excel format. The software allows users to perform texture analyses on any type of radiological image without the need for image transfer by simply placing a region of interest. This tool has already been used to assess the trabecular network of vertebra. The integration of such software into PACS extends the applicability of texture analysis beyond that of a mere research tool and facilitates its use in routine clinical practice.

Creating an ontology driven rules base for an expert system for medical diagnosis.

Expert systems of the 1980s have failed on the difficulties of maintaining large rule bases. The current work proposes a method to achieve and maintain rule bases grounded on ontologies (like NCIT). The process described here for an expert system on plasma cell disorder encompasses extraction of a sub-ontology and automatic and comprehensive generation of production rules. The creation of rules is not based directly on classes, but on individuals (instances). Instances can be considered as prototypes of diseases formally defined by "destrictions" in the ontology. Thus, it is possible to use this process to make diagnoses of diseases. The perspectives of this work are considered: the process described with an ontology formalized in OWL1 can be extended by using an ontology in OWL2 and allow reasoning about numerical data in addition to symbolic data.

Creating a magnetic resonance imaging ontology.

The goal of this work is to build an ontology of Magnetic Resonance Imaging. The MRI domain has been analysed regarding MRI simulators and the DICOM standard. Tow MRI simulators have been analysed: JEMRIS, which is developed in XML and C++, has a hierarchical organisation and SIMRI, which is developed in C, has a good representation of MRI physical processes. To build the ontology we have used Protégé 4, owl2 that allows quantitative representations. The ontology has been validated by a reasoner (Fact++) and by a good representation of DICOM headers and of MRI processes. The MRI ontology would improved MRI simulators and eased semantic interoperability.

Automatic definition of the oncologic EHR data elements from NCIT in OWL.

UNLABELLED: Semantic interoperability based on ontologies allows systems to combine their information and process them automatically. The ability to extract meaningful fragments from ontology is a key for the ontology re-use and the construction of a subset will help to structure clinical data entries. The aim of this work is to provide a method for extracting a set of concepts for a specific domain, in order to help to define data elements of an oncologic EHR. METHOD: a generic extraction algorithm was developed to extract, from the NCIT and for a specific disease (i.e. prostate neoplasm), all the concepts of interest into a sub-ontology. We compared all the concepts extracted to the concepts encoded manually contained into the multi-disciplinary meeting report form (MDMRF). RESULTS: We extracted two sub-ontologies: sub-ontology 1 by using a single key concept and sub-ontology 2 by using 5 additional keywords. The coverage of sub-ontology 2 to the MDMRF concepts was 51%. The low rate of coverage is due to the lack of definition or mis-classification of the NCIT concepts. By providing a subset of concepts focused on a particular domain, this extraction method helps at optimizing the binding process of data elements and at maintaining and enriching a domain ontology.

Roogle: an information retrieval engine for clinical data warehouse.

High amount of relevant information is contained in reports stored in the electronic patient records and associated metadata. R-oogle is a project aiming at developing information retrieval engines adapted to these reports and designed for clinicians. The system consists in a data warehouse (full-text reports and structured data) imported from two different hospital information systems. Information retrieval is performed using metadata-based semantic and full-text search methods (as Google). Applications may be biomarkers identification in a translational approach, search of specific cases, and constitution of cohorts, professional practice evaluation, and quality control assessment.

Snapping biceps femoris tendon: a dynamic real-time sonographic evaluation.

Snapping of the distal arms of the biceps femoris tendon may explain pain and discomfort at the lateral aspect of the knee. We report two cases in which dynamic sonography was able to confirm the diagnosis and document which of the main arms was involved in the process.

Comparing the APGAR score representation in HL7 and OpenEHR formalisms.

Semantic interoperability, a prerequisite to eHealth projects, relies on sharing both information and knowledge models between information systems. Two of the standards of information models are HL7 v3 and the European norm, EN13606/OpenEHR. The paper compares both standards on a fragment of the prenatal medical record, the APGAR score. Two factors are compared: the formal representation of both information models, and the binding to knowledge models. The HL7v3 perinatality DMIM specification and the OpenEHR APGAR archetype were used. HL7v3 appears to be more formal than OpenEHR and able to represent in an easier way the clinical context. For both standards, the binding to reference terminologies such as LOINC is poor. We provide recommendations to improve the standards.

[Contribution of C.S. Peirce thought to the representation knowledge and medical reasoning]. / C.S. Peirce - Sa pensée pour une représentation des connaissances etdu raisonnement médical ?

Modelling knowledge and medical reasoning can be an epistemological project especially now, as medicine seems to reach a scientific status. Through his work on semiotics, abductive reasoning and pragmatism, CS Peirce (1839-1914) offers a series of original solutions. These solutions can give an account of (be considered as a theorical ground for) most of the medical activity in various fields such as the evaluation of the students, the knowledge bases and expert systems, the formal descriptions languages (ontologies), and the evidence-based medicine. By mean of this article, we aim at introducing the medical doctors to this complex but lighting thought on a profession which now uses all the most modern resources of knowledge engineering.

An ontological analysis of medical Bayesian indicators of performance.

BACKGROUND: Biomedical ontologies aim at providing the most exhaustive and rigorous representation of reality as described by biomedical sciences. A large part of medical reasoning deals with diagnosis and is essentially probabilistic. It would be an asset for biomedical ontologies to be able to support such a probabilistic reasoning and formalize Bayesian indicators of performance: sensitivity, specificity, positive predictive value and negative predictive value. In doing so, one has to consider that not only the positive and negative predictive values, but also sensitivity and specificity depend upon the group under consideration: this is the "spectrum effect". METHODS: The sensitivity value of an index test IT for a disease M in a group g is identified with the proportion of people in g who have M who would get a positive result to IT if the test IT was realized on them. This value can be estimated by selecting a reference test RT for M and a sample s of g, and measuring the proportion, among members of s having a positive result to RT, of those who got a positive result to IT. Similar approximation strategies hold for prevalence, specificity, PPV and NPV. Indicators of diagnostic performances and their estimations are formalized in the context of the OBO Foundry, built on the realist upper ontology Basic Formal Ontology (BFO). RESULTS: Entities and relations from the Ontology for Biomedical investigations (OBI) and the Information Artifact Ontology (IAO) are used and complemented to represent reference tests and index tests, tests executions, tests results and the relations involving those entities, as well as the values of indicators of performance and their estimates. The computations taking as input several estimates of an indicator of performance to produce a finer estimate are also represented. The value of e.g. sensitivity estimates should be dissociated from the real sensitivity value - which involves possible, non-actual conditions, namely the result a person would get if a medical test would be performed on her. Such conditions could not be directly represented in a realist ontology, but a representation is proposed that introduces only actual entities by considering a disposition whose probability value is the real sensitivity value. A sensitivity estimate is a data item which is about such a disposition. CONCLUSIONS: This model provides theoretical basis for the representation of entities supporting Bayesian reasoning in ontologies.

Ontology and medical diagnosis.

Ontology and associated generic tools are appropriate for knowledge modeling and reasoning, but most of the time, disease definitions in existing description logic (DL) ontology are not sufficient to classify patient's characteristics under a particular disease because they do not formalize operational definitions of diseases (association of signs and symptoms=diagnostic criteria). The main objective of this study is to propose an ontological representation which takes into account the diagnostic criteria on which specific patient conditions may be classified under a specific disease. This method needs as a prerequisite a clear list of necessary and sufficient diagnostic criteria as defined for lots of diseases by learned societies. It does not include probability/uncertainty which Web Ontology Language (OWL 2.0) cannot handle. We illustrate it with spondyloarthritis (SpA). Ontology has been designed in Protégé 4.1 OWL-DL2.0. Several kinds of criteria were formalized: (1) mandatory criteria, (2) picking two criteria among several diagnostic criteria, (3) numeric criteria. Thirty real patient cases were successfully classified with the reasoner. This study shows that it is possible to represent operational definitions of diseases with OWL and successfully classify real patient cases. Representing diagnostic criteria as descriptive knowledge (instead of rules in Semantic Web Rule Language or Prolog) allows us to take advantage of tools already available for OWL. While we focused on Assessment of SpondyloArthritis international Society SpA criteria, we believe that many of the representation issues addressed here are relevant to using OWL-DL for operational definition of other diseases in ontology.

A unified representation of findings in clinical radiology using the UMLS and DICOM.

PURPOSE: Collecting and analyzing findings constitute the basis of medical activity. Computer assisted medical activity raises the problem of modelling findings. We propose a unified representation of findings integrating the representations of findings in the GAMUTS in Radiology [M.M. Reeder, B. Felson, GAMUTS in radiology Comprehensive lists of roentgen differential diagnosis, fourth ed., 2003], the Unified Medical Language System (UMLS), and the Digital Imaging and Communication in Medicine Structured Report (DICOM-SR). MATERIALS AND METHODS: Starting from a corpus of findings in bone and joint radiology [M.M. Reeder, B. Felson, GAMUTS in Radiology comprehensive lists of roentgen differential diagnosis, fourth ed., 2003] (3481 words), an automated mapping to the UMLS was performed with the Metamap Program. The resulting UMLS terms and Semantic Types were analyzed in order to find a generic template in accordance with DICOM-SR structure. RESULTS: UMLS Concepts were missing for 45% of the GAMUTS findings. Three kinds of regularities were observed in the way the Semantic Types were combined: "pathological findings", "physiological findings" and "anatomical findings". A generic and original DICOM-SR template modelling finding was proposed. It was evaluated for representing GAMUTS jaws findings. 21% missing terms had to be picked up from Radlex (5%) or created (16%). DISCUSSION-CONCLUSION: This article shows that it is possible to represent findings using the UMLS and the DICOM SR formalism with a semi-automated method. The Metamap program helped to find a model to represent the semantic structure of free texts with standardized terms (UMLS Concepts). Nevertheless, the coverage of the UMLS is not comprehensive. This study shows that the UMLS should include more technical concepts and more concepts regarding findings, signs and symptoms to be suitable for radiology representation. The semi-automated translation of the whole GAMUTS using the UMLS concepts and the DICOM SR relations could help to create or supplement the DCMR Templates and Context Groups pertaining to the description of imaging findings.

The value of using verbs in Medline searches.

New findings are continuously identified thanks to novel diagnostic procedures, among others in medical imaging. It would be useful to retrieve these new findings from literature. The aim of this work is to investigate if using verbs in MEDLINE queries can improve the retrieval of findings. Verbs used in the field of findings were selected: 'to show' (an examination shows a finding) and 'to confirm' (a finding confirms a diagnosis). For each of these verbs, semantically close verbs were researched on the WordNet website. Then, the extent to which adding these verbs to a query about various radiological pathologies can improve findings retrieval in Medline citations was studied. This method has been tested on two sets of MEDLINE citations regarding the diagnostic imaging of musculo-skeletal disorders. Using appropriate verbs in Medline queries enhances the precision from 53% to 61% and from 53% to 74%, respectively, in our first and second test set. A recall of 74% and 83% was reached in our two experiments. Using relevant verbs can be a rather simple way to improve the retrieval of findings related to diseases and diagnostic procedures from Medline citations.

Toward a unified representation of findings in clinical radiology.

The representations of findings in clinical radiology are heterogeneous. Motivations for developing a unified representation include the semantic integration of medical reports based on DICOM-SR(Digital Image Communication in Medicine Structured Reporting), bibliographic databases in the context of evidence-based medicine, and teaching resources. In this work, we propose a unified representation integrating the representations of findings in the UMLS, the GAMUTS in Radiology and the DICOM-SR. We analyse the UMLS and the DCMR (DICOM Content Mapping Resource) of DICOM SR to figure out their own representation of findings. Then we set up a syntax between the UMLS concepts using DICOM-SR relations in order to rewrite the GAMUTS sentences. The translation of the whole GAMUTS using the UMLS concepts and the DICOM SR syntax could be a method to create or supplement the DCMR TIDs (Template ID : Identifier of a Template) and CIDs (Context ID : Identifier of a Context Group) in the field of description of findings in medical imaging. This method could also enable to give an ontologic dimension to the DICOM SR representation system of information. The meaning of the CIDs would then be enhanced far beyond the simple use of the SNOMED vocabulary.