A Feasibility Study of Extracting Tissue Textures From a Previous Full-Dose CT Database as Prior Knowledge for Bayesian Reconstruction of Current Low-Dose CT Images.

Markov random field (MRF) has been widely used to incorporate a priori knowledge as penalty or regularizer to preserve edge sharpness while smoothing the region enclosed by the edge for pieces-wise smooth image reconstruction. In our earlier study, we proposed a type of MRF reconstruction method for low-dose CT (LdCT) scans using tissue-specific textures extracted from the same patient's previous full-dose CT (FdCT) scans as prior knowledge. It showed advantages in clinical applications. This paper aims to remove the constraint of using previous data of the same patient. We investigated the feasibility of extracting the tissue-specific MRF textures from an FdCT database to reconstruct a LdCT image of another patient. This feasibility study was carried out by experiments designed as follows. We constructed a tissue-specific MRF-texture database from 3990 FdCT scan slices of 133 patients who were scheduled for lung nodule biopsy. Each patient had one FdCT scan (120 kVp/100 mAs) and one LdCT scan (120 kVp/20 mAs) prior to biopsy procedure. When reconstructing the LdCT image of one patient among the 133 patients, we ranked the closeness of the MRF-textures from the other 132 patients saved in the database and used them as the a prior knowledge. Then, we evaluated the reconstructed image quality using Haralick texture measures. For any patient within our database, we found more than eighteen patients' FdCT MRF texures can be used without noticeably changing the Haralick texture measures on the lung nodules (to be biopsied). These experimental outcomes indicate it is promising that a sizable FdCT texture database could be used to enhance Bayesian reconstructions of any incoming LdCT scans.

Prospective determination of candidates for thrombolysis in patients with acute proximal deep vein thrombosis.

PURPOSE: To prospectively determine the distribution, extent, and age of venous thrombosis in patients presenting with acute signs and symptoms of venous thromboembolism and identify candidates for thrombolysis. MATERIALS AND METHODS: Five hundred seventy-six consecutive patients (281 male, 295 female; mean age 58) referred for lower extremity deep vein thrombosis (DVT) assessment between November 2007 and April 2008 were included in the study. Documented cases of DVT were categorized by age (acute, chronic, and acute on chronic), anatomic location, and extent. Patients with iliofemoral and femoropopliteal DVT were evaluated for thrombolysis using standard criteria. RESULTS: DVT was found in 19% of patients (112/576). Of these, 31 patients (27.7%, 31/112) had isolated calf DVT, 61 patients (54.5%, 61/112) had proximal vein thrombosis extending into the femoropopliteal venous segments, and 20 patients (17.9%, 20/112) presented with iliofemoral DVT. Using standard criteria, 12 patients were selected as potential candidates for pharmacomechanical thrombolysis (PhMT). This equated to an incidence of 2% (12/576) in the population studied, 11% of patients (12/112) with DVT, 26.1% of patients (12/46) presenting with acute proximal DVT, and 20% of patients (4/20) with iliofemoral DVT. CONCLUSION: The incidence of potential candidates for thrombolysis is low. These data should be considered when recruiting centers to participate in ongoing clinical trials assessing the efficacy of these techniques.