Impact of CT reconstruction algorithm on auto-segmentation performance

CT Image Features of the FBP Reconstruction Algorithm in the Evaluation of Fasting Blood Sugar Level of Diabetic Pulmonary Tuberculosis Patients and Early Diet Nursing

The study was aimed at exploring the application value of the CT image based on a filtered back projection (FBP) algorithm in the diagnosis of patients with diabetes complicated with tuberculosis and at analyzing the influence of dietary nursing on patients with diabetes complicated with tuberculosis. In this study, the FBP algorithm was used to optimize CT images to effectively obtain reconstructed ROI images. Then, the deviation from measurement values of reconstructed images at different pixel levels was analyzed. 138 patients with diabetes complicated with tuberculosis were selected as research subjects to compare the number of lung segments involved and the CT imaging manifestations at different fasting glucose levels. All patients were divided into the control group (routine drug treatment) and observation group (diet intervention on the basis of drug treatment) by random number table method, and the effect of different nursing methods on the improvement of patients' clinical symptoms was discussed. The results showed that the distance measurement value decreased with the increase in pixel level, there was no significant difference in the number of lung segments involved in patients with different fasting glucose levels (P > 0.05), and there were statistically significant differences in the incidence of segmental lobar shadow, bronchial air sign, wall-less cavity, thick-walled cavity, pulmonary multiple cavity, and bronchial tuberculosis in patients with different fasting glucose levels (P < 0.05). Compared with the control group, 2 h postprandial blood glucose level in the observation group was significantly improved (P < 0.05), there was a statistical significance in the number with reduced pleural effusion and the number with reduced tuberculosis foci in the two groups (P < 0.05), and the level of hemoglobin in the observation group was 7.1 ± 1.26, significantly lower than that in the control group (8.91 ± 2.03, P < 0.05). It suggested that the changes of CT images based on the FBP reconstruction algorithm were correlated with fasting blood glucose level. Personalized diet nursing intervention can improve the clinical symptoms of patients, which provides a reference for the clinical diagnosis and treatment of patients with diabetes complicated with tuberculosis.

3D reconstructions, 4D imaging and postprocessing with CT in musculoskeletal disorders: Past, present and future

Three-dimensional (3D) imaging and post processing are common tasks used daily in many disciplines. The purpose of this article is to review the new postprocessing tools available. Although 3D imaging can be applied to all anatomical regions and used with all imaging techniques, its most varied and relevant applications are found with computed tomography (CT) data in musculoskeletal imaging. These new applications include global illumination rendering (GIR), unfolded rib reformations, subtracted CT angiography for bone analysis, dynamic studies, temporal subtraction and image fusion. In all of these tasks, registration and segmentation are two basic processes that affect the quality of the results. GIR simulates the complete interaction of photons with the scanned object, providing photorealistic volume rendering. Reformations to unfold the rib cage allow more accurate and faster diagnosis of rib lesions. Dynamic CT can be applied to cinematic joint evaluations a well as to perfusion and angiographic studies. Finally, more traditional techniques, such as minimum intensity projection, might find new applications for bone evaluation with the advent of ultra-high-resolution CT scanners. These tools can be used synergistically to provide morphologic, topographic and functional information and increase the versatility of CT.

Adult patient-specific CT organ dose estimations using automated segmentations and Monte Carlo simulations

We aimed to determine feasibility in calculating patient-specific organ doses for abdominal computed tomography (CT) exams using an automated segmentation technique dedicated to abdominal organs combined with Monte Carlo simulation of a clinical CT scanner. We conducted the automated segmentation of five major abdominal organs (left and right kidneys, pancreas, spleen, and liver) for ten adult patients and calculated organ-specific doses for each patient. We observed significant variability (Coefficient of Variation up to 32%) in organ mass across the ten patients, which was up to two-fold greater or smaller than the reference organ mass for the ICRP reference adult male and female. Comparison of patient-specific organ dose per CTDI_vol with those from the ICRP reference phantoms confirmed that reference phantom-based dose reporting programs cannot capture inter-patient dose variability, and dosimetric errors can go up to nearly 40%. We demonstrated an automated method for patient-specific organ dose calculations, which took about 45 min per patient. When the automatic segmentation method is extended to more organs and faster Monte Carlo calculation technique is employed, our method should be useful for patient-specific dose monitoring at the organ level and for epidemiological investigations of health risks in CT patients.