ABSTRACT
Tinnitus is the perception of sound in the absence of an external source. It is a common symptom that can be related to hearing loss and other benign causes. However, tinnitus may be disabling and can be the only symptom in a patient with a central nervous system process disorder. History and physical examination are crucial first steps to determine the need for imaging. CT and MRI are useful in the setting of pulsatile tinnitus to evaluate for an underlying vascular anomaly or abnormality. If there is concomitant asymmetric hearing loss, neurologic deficit, or head trauma, imaging should be guided by those respective ACR Appropriateness Criteria® documents, rather than the presence of tinnitus. Imaging is not usually appropriate in the evaluation of subjective, nonpulsatile tinnitus that does not localize to one ear. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.
Subject(s)
Diagnostic Imaging/methods , Tinnitus/diagnostic imaging , Evidence-Based Medicine , Humans , Societies, Medical , United StatesABSTRACT
Purpose: Fluorine-18 fluorodeoxyglucose positron emission tomography with CT attenuation correction (18F-FDG PET/CT) is useful in the detection and enumeration of focal lesions and in semiquantitative characterization of metabolic activity (glycolytic phenotype) by calculation of glucose uptake. Total lesion glycolysis (TLG) and metabolic tumor volume (MTV) have the potential to improve the value of this approach and enhance the prognostic value of disease burden measures. This study aims to determine whether TLG and MTV are associated with progression-free survival (PFS) and overall survival (OS), and whether they improve risk assessments such as International Staging System (ISS) stage and GEP70 risk.Experimental Design: 192 patients underwent whole body PET/CT in the Total Therapy 3A (TT3A) trial and were evaluated using three-dimensional region-of-interest analysis with TLG, MTV, and standard measurement parameters derived for all focal lesions with peak SUV above the background red marrow signal.Results: In multivariate analysis, baseline TLG > 620 g and MTV > 210 cm3 remained a significant factor of poor PFS and OS after adjusting for baseline myeloma variables. Combined with the GEP70 risk score, TLG > 205 g identifies a high-risk-behaving subgroup with poor expected survival. In addition, TLG > 205 g accurately divides ISS stage II patients into two subgroups with similar outcomes to ISS stage I and ISS stage III, respectively.Conclusions: TLG and MTV have significant survival implications at baseline and offer a more precise quantitation of the glycolytic phenotype of active disease. These measures can be assessed more readily than before using FDA-approved software and should be standardized and incorporated into clinical trials moving forward. Clin Cancer Res; 23(8); 1981-7. ©2016 AACR.
Subject(s)
Multiple Myeloma/diagnostic imaging , Multiple Myeloma/pathology , Positron Emission Tomography Computed Tomography/methods , Aged , Disease-Free Survival , Female , Fluorodeoxyglucose F18 , Glycolysis , Humans , Image Interpretation, Computer-Assisted , Imaging, Three-Dimensional , Kaplan-Meier Estimate , Male , Middle Aged , Multiple Myeloma/metabolism , Prognosis , RadiopharmaceuticalsABSTRACT
Neuroimaging plays an important role in the management of head trauma. Several guidelines have been published for identifying which patients can avoid neuroimaging. Noncontrast head CT is the most appropriate initial examination in patients with minor or mild acute closed head injury who require neuroimaging as well as patients with moderate to severe acute closed head injury. In short-term follow-up neuroimaging of acute traumatic brain injury, CT and MRI may have complementary roles. In subacute to chronic traumatic brain injury, MRI is the most appropriate initial examination, though CT may have a complementary role in select circumstances. Advanced neuroimaging techniques are areas of active research but are not considered routine clinical practice at this time. In suspected intracranial vascular injury, CT angiography or venography or MR angiography or venography is the most appropriate imaging study. In suspected posttraumatic cerebrospinal fluid leak, high-resolution noncontrast skull base CT is the most appropriate initial imaging study to identify the source, with cisternography reserved for problem solving. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every three years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances in which evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.
Subject(s)
Craniocerebral Trauma/diagnostic imaging , Neuroimaging/standards , Evidence-Based Medicine , Glasgow Coma Scale , Humans , Magnetic Resonance Imaging/standards , Tomography, X-Ray Computed/standardsABSTRACT
Patients presenting with myelopathic symptoms may have a number of causative intradural and extradural etiologies, including disc degenerative diseases, spinal masses, infectious or inflammatory processes, vascular compromise, and vertebral fracture. Patients may present acutely or insidiously and may progress toward long-term paralysis if not treated promptly and effectively. Noncontrast CT is the most appropriate first examination in acute trauma cases to diagnose vertebral fracture as the cause of acute myelopathy. In most nontraumatic cases, MRI is the modality of choice to evaluate the location, severity, and causative etiology of spinal cord myelopathy, and predicts which patients may benefit from surgery. Myelopathy from spinal stenosis and spinal osteoarthritis is best confirmed without MRI intravenous contrast. Many other myelopathic conditions are more easily visualized after contrast administration. Imaging performed should be limited to the appropriate spinal levels, based on history, physical examination, and clinical judgment. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every three years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer-reviewed journals, and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances in which evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.
Subject(s)
Diagnostic Imaging/standards , Radiology/standards , Spinal Cord Diseases/diagnosis , Evidence-Based Medicine , HumansABSTRACT
Retrospective research is an import tool in radiology. Identifying imaging examinations appropriate for a given research question from the unstructured radiology reports is extremely useful, but labor-intensive. Using the machine learning text-mining methods implemented in LingPipe [1], we evaluated the performance of the dynamic language model (DLM) and the Naïve Bayesian (NB) classifiers in classifying radiology reports to facilitate identification of radiological examinations for research projects. The training dataset consisted of 14,325 sentences from 11,432 radiology reports randomly selected from a database of 5,104,594 reports in all disciplines of radiology. The training sentences were categorized manually into six categories (Positive, Differential, Post Treatment, Negative, Normal, and History). A 10-fold cross-validation [2] was used to evaluate the performance of the models, which were tested in classification of radiology reports for cases of sellar or suprasellar masses and colloid cysts. The average accuracies for the DLM and NB classifiers were 88.5% with 95% confidence interval (CI) of 1.9% and 85.9% with 95% CI of 2.0%, respectively. The DLM performed slightly better and was used to classify 1,397 radiology reports containing the keywords "sellar or suprasellar mass", or "colloid cyst". The DLM model produced an accuracy of 88.2% with 95% CI of 2.1% for 959 reports that contain "sellar or suprasellar mass" and an accuracy of 86.3% with 95% CI of 2.5% for 437 reports of "colloid cyst". We conclude that automated classification of radiology reports using machine learning techniques can effectively facilitate the identification of cases suitable for retrospective research.
Subject(s)
Natural Language Processing , Radiology Information Systems/classification , Radiology/classification , Research Report/standards , Databases, Factual/standards , Datasets as Topic/standards , Humans , Radiology/standards , Radiology Information Systems/standards , Reproducibility of Results , Retrospective Studies , Sensitivity and SpecificityABSTRACT
With increasing volumes of complex imaging cases and rising economic pressure on physician staffing, timely reporting will become progressively challenging. Current and planned iterations of PACS and electronic medical record systems do not offer workflow management tools to coordinate delivery of imaging interpretations with the needs of the patient and ordering physician. The adoption of a server-based enterprise collaboration software system by our Division of Nuclear Medicine has significantly improved our efficiency and quality of service.