Detection of Osteophytes and Subchondral Cysts in the Knee with Use of Tomosynthesis
ABSTRACT To evaluate the diagnostic performance of tomosynthesis in depicting osteophytes and subchondral cysts, with use of magnetic resonance (MR) imaging as the reference, and to test whether the lesions detected at radiography and tomosynthesis are associated with pain.
The study was approved by local institutional review board, and all subjects gave written informed consent. Forty subjects (80 knees) older than 40 years were recruited irrespective of knee pain or radiographic osteoarthritis. Knees were imaged with radiography, tomosynthesis, and MR imaging. Presence of osteophytes and subchondral cysts in four locations of tibiofemoral joint (medial and lateral femur and tibia) was recorded. Knee pain was assessed by using the Western Ontario and McMaster University pain subscale.
MR imaging depicted 171 osteophytes and 51 subchondral cysts. Tomosynthesis had a higher sensitivity for osteophyte detection in left and right lateral femur (0.96 vs 0.75, P = .025, and 1.00 vs 0.71, P = .008, respectively), right medial femur (0.94 vs 0.72, P = .046), and right lateral tibia (1.00 vs 0.83, P = .046). For subchondral cyst detection, the sensitivity of tomosynthesis was 0.14-1.00 and that of radiography was 0.00-0.56. Both modalities had similar specificity for both lesions. Subjects with tomosynthesis-depicted osteophytes (odds ratio, 4.2-6.4; P = .001-.011) and medially located subchondral cysts (odds ratio, 6.7-17.8; P = .004-.03) were more likely to feel pain than those without. However, radiography-depicted osteophytes were more strongly associated with pain than were tomosynthesis-depicted osteophytes.
Tomosynthesis depicted more osteophytes and subchondral cysts than did radiography. Subjects with tomosynthesis-depicted osteophytes and subchondral cysts were more likely to feel pain than those without such lesions.
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ABSTRACT: Osteoarthritis has grown to become a widely prevalent disease that has major implications in both individual and public health. Although originally considered to be a degenerative disease driven by "wear and tear" of the articular cartilage, recent evidence has led to a consensus that osteoarthritis pathophysiology should be perceived in the context of the entire joint and multiple tissues. MRI is becoming an increasingly more important modality for imaging osteoarthritis, due to its excellent soft tissue contrast and ability to acquire morphological and biochemical data. This review will describe the pathophysiology of osteoarthritis as it is associated with various tissue types, highlight several promising MR imaging techniques for osteoarthritis and illustrate the expected appearance of osteoarthritis with each technique.J. Magn. Reson. Imaging 2014. © 2014 Wiley Periodicals, Inc.Journal of Magnetic Resonance Imaging 06/2014; 39(6). DOI:10.1002/jmri.24562 · 2.79 Impact Factor
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ABSTRACT: Chest tomosynthesis is a relatively recently introduced technique in healthcare, which produces section images of the chest at a lower radiation dose than computed tomography (CT) and with better depth resolution than conventional chest radiography. The primary aims of the studies described in this dissertation were to compare chest tomosynthesis with conventional radiography, to evaluate the effects of clinical experience and learning with feedback on the performance of observers analyzing tomosynthesis images, and to investigate the effect of radiation dose level in tomosynthesis, in the detection of pulmonary nodules. Human observer studies were performed, in which radiologists were instructed to localize and rate pulmonary nodules in patient images. Chest CT was used as reference. The observers' performance regarding the detection of nodules was used as measure of detectability. The results of the studies indicate that the detection of pulmonary nodules is better in chest tomosynthesis than in conventional chest radiography, that experienced thoracic radiologists can quickly adapt to the new technique, that inexperienced observers may perform at a similar level to experienced radiologists after a learning session with feedback, and that a substantial reduction in the effective dose to the patient may be possible.05/2014, Degree: PhD, Supervisor: Magnus Båth, Lars Gunnar Månsson, Åse Allansdotter Johnsson
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ABSTRACT: Objective Plain radiography has been the mainstay of imaging assessment in osteoarthritis for over 50 years, but it does have limitations. Here we present the methodology and results of a new technique for identifying, grading, and mapping the severity and spatial distribution of osteoarthritic disease features at the hip in 3D with clinical computed tomography (CT). Design CT imaging of 456 hips from 230 adult female volunteers (mean age 66 ± 17 yrs) was reviewed using 3D multiplanar reformatting to identify bone-related radiological features of osteoarthritis, namely osteophytes, subchondral cysts and joint space narrowing. Scoresheets dividing up the femoral head, head-neck region and the joint space were used to register the location and severity of each feature (scored from 0 to 3). Novel 3D cumulative feature severity maps were then created to display where the most severe disease features from each individual were anatomically located across the cohort. Results Feature severity maps showed a propensity for osteophytes at the inferoposterior and superolateral femoral head-neck junction. Subchondral cysts were a less common and less localised phenomenon. Joint space narrowing <1.5mm was recorded in at least one sector of 83% of hips, but most frequently in the posterolateral joint space. Conclusions This is the first description of hip osteoarthritis using unenhanced clinical CT in which we describe the co-localisation of posterior osteophytes and joint space narrowing for the first time. We believe this technique can perform several important roles in future osteoarthritis research, including phenotyping and sensitive disease assessment in 3D.Osteoarthritis and Cartilage 10/2014; 22(10). DOI:10.1016/j.joca.2014.03.007 · 4.66 Impact Factor