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1.
Bull Menninger Clin ; 86(2): 91-112, 2022.
Article in English | MEDLINE | ID: mdl-34346726

ABSTRACT

Individuals with obsessive-compulsive disorder (OCD) have evidenced resilience against large-scale crises, although emerging research on the impact of COVID-19 is mixed. Little is known about the impact of COVID-19 on mental health providers. Items from an instrument evaluating the impact of the September 11, 2001, terrorist attack were adapted to measure the impact of COVID-19 on emotions, cognitions, and behaviors. Using a sample of 65 patients with primary OCD diagnoses and OCD treatment providers in intensive programs for OCD and anxiety, the authors found that COVID-19 evidenced a less significant overall impact on patients than providers. Specifically, providers reported more significant impact on the amount of time spent worrying about COVID-19, taking additional cleaning and sanitization precautions, and time spent socializing with loved ones. Findings support previous literature indicating that individuals with OCD demonstrate resilience to large-scale crises, and offer insights into the specific struggles of providers who treat OCD.


Subject(s)
COVID-19 , Obsessive-Compulsive Disorder , Anxiety Disorders , Humans , Mental Health , Obsessive-Compulsive Disorder/diagnosis , Pandemics
2.
Med Phys ; 38(12): 6672-82, 2011 Dec.
Article in English | MEDLINE | ID: mdl-22149849

ABSTRACT

PURPOSE: Digital x-ray tomosynthesis (DTS) has the potential to provide 3D information about the knee joint in a load-bearing posture, which may improve diagnosis and monitoring of knee osteoarthritis compared with projection radiography, the current standard of care. Manually quantifying and visualizing the joint space width (JSW) from 3D tomosynthesis datasets may be challenging. This work developed a semiautomated algorithm for quantifying the 3D tibiofemoral JSW from reconstructed DTS images. The algorithm was validated through anthropomorphic phantom experiments and applied to three clinical datasets. METHODS: A user-selected volume of interest within the reconstructed DTS volume was enhanced with 1D multiscale gradient kernels. The edge-enhanced volumes were divided by polarity into tibial and femoral edge maps and combined across kernel scales. A 2D connected components algorithm was performed to determine candidate tibial and femoral edges. A 2D joint space width map (JSW) was constructed to represent the 3D tibiofemoral joint space. To quantify the algorithm accuracy, an adjustable knee phantom was constructed, and eleven posterior-anterior (PA) and lateral DTS scans were acquired with the medial minimum JSW of the phantom set to 0-5 mm in 0.5 mm increments (VolumeRad™, GE Healthcare, Chalfont St. Giles, United Kingdom). The accuracy of the algorithm was quantified by comparing the minimum JSW in a region of interest in the medial compartment of the JSW map to the measured phantom setting for each trial. In addition, the algorithm was applied to DTS scans of a static knee phantom and the JSW map compared to values estimated from a manually segmented computed tomography (CT) dataset. The algorithm was also applied to three clinical DTS datasets of osteoarthritic patients. RESULTS: The algorithm segmented the JSW and generated a JSW map for all phantom and clinical datasets. For the adjustable phantom, the estimated minimum JSW values were plotted against the measured values for all trials. A linear fit estimated a slope of 0.887 (R² = 0.962) and a mean error across all trials of 0.34 mm for the PA phantom data. The estimated minimum JSW values for the lateral adjustable phantom acquisitions were found to have low correlation to the measured values (R² = 0.377), with a mean error of 2.13 mm. The error in the lateral adjustable-phantom datasets appeared to be caused by artifacts due to unrealistic features in the phantom bones. JSW maps generated by DTS and CT varied by a mean of 0.6 mm and 0.8 mm across the knee joint, for PA and lateral scans. The tibial and femoral edges were successfully segmented and JSW maps determined for PA and lateral clinical DTS datasets. CONCLUSIONS: A semiautomated method is presented for quantifying the 3D joint space in a 2D JSW map using tomosynthesis images. The proposed algorithm quantified the JSW across the knee joint to sub-millimeter accuracy for PA tomosynthesis acquisitions. Overall, the results suggest that x-ray tomosynthesis may be beneficial for diagnosing and monitoring disease progression or treatment of osteoarthritis by providing quantitative images of JSW in the load-bearing knee.


Subject(s)
Algorithms , Imaging, Three-Dimensional/methods , Knee Joint/diagnostic imaging , Pattern Recognition, Automated/methods , Radiographic Image Enhancement/methods , Radiographic Image Interpretation, Computer-Assisted/methods , Tomography, X-Ray Computed/methods , Femur/diagnostic imaging , Humans , Reproducibility of Results , Sensitivity and Specificity , Tibia/diagnostic imaging
3.
AJR Am J Roentgenol ; 186(4): 989-94, 2006 Apr.
Article in English | MEDLINE | ID: mdl-16554568

ABSTRACT

OBJECTIVE: The objective of our study was to evaluate repeatability and reproducibility of lung nodule volume measurements using volumetric nodule-sizing software. MATERIALS AND METHODS: Fifty nodules, less than 20 mm in diameter, in 29 patients were scanned with 1.25-mm collimation using MDCT (time 1 = T1). During the same session, two additional scans, using identical technique, were obtained through each nodule (T2, T3). Three observers working independently then obtained volumetric measurements using a semiautomated volumetric nodule-sizing software package. Qualitative nodule characterization was also performed. The Bland-Altman method for assessing measurement agreement was used to calculate the 95% limits for agreement for nodule volumes at T1, T2, and T3. RESULTS: Automated nodule segmentation was successful in 438 (97%) of 450 measurements. Forty-three nodules were available for final evaluation. Twenty-six nodules had well-defined edges, and 17 had irregular or spiculated margins. Seventeen were freestanding, 16 were juxtapleural, and 10 were juxtavascular in location. Average nodule volume was 345.5 mm(3) (range, 49.3-1,434 mm(3)). The mean interobserver variability (repeatability) was 0.018% (SD = 0.73%), and the SD of the mean for the three contemporaneous scans (reproducibility) was 13.1% (confidence limits, +/- 25.6%). SD and confidence limits narrowed as volumes increased. CONCLUSION: Volumetric measurements show minimal interobserver variability (0.018%) but an interscan SEM of 13.1% (confidence limits, +/- 25.6%). Repeatability and reproducibility of volumetric measurements are better than those of linear measurements reported in the literature.


Subject(s)
Lung Neoplasms/diagnostic imaging , Lung Neoplasms/pathology , Tomography, X-Ray Computed/statistics & numerical data , Adult , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Observer Variation , Reproducibility of Results
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