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Biomedical subjects

David R Haynor

Publications and source records attributed to David R Haynor.

6 recordsLinked to original sources

Three-year incidence of low back pain in an initially asymptomatic cohort: clinical and imaging risk factors.

STUDY DESIGN: Prospective cohort study of randomly selected Veterans Affairs out-patients without baseline low back pain (LBP). OBJECTIVE: To determine predictors of new LBP as well as the 3-year incidence of magnetic resonance imaging (MRI) findings. SUMMARY OF BACKGROUND DATA: Few prospective studies have examined clinical and anatomic risk factors for the development of LBP, or the incidence of new imaging findings and their relationship to back pain onset. METHODS: We randomly selected 148 Veterans Affairs out-patients (aged 35 to 70) without LBP in the past 4 months. We compared baseline and 3-year lumbar spine MRI. Using data collected every 4 months, we developed a prediction model of back pain-free survival. RESULTS: After 3 years, 131 subjects were contacted, and 123 had repeat MRI. The 3-year incidence of pain was 67% (88 of 131). Depression had the largest hazard ratio (2.3, 95% CI = 1.2-4.4) of any baseline predictor of inci-dent back pain. Among baseline imaging findings, central spinal stenosis and nerve root contact had the highest, though nonsignificant, hazard ratios. We did not find an association between new LBP and type 1 endplate changes, disc degeneration, annular tears, or facet degeneration. The incidence of new MRI findings was low, with the most common new finding being disc signal loss in 11 (9%) subjects. All five subjects with new disc extrusions and all four subjects with new nerve root impingement had new pain. CONCLUSION: Depression is an important predictor of new LBP, with MRI findings likely less important. New imaging findings have a low incidence; disc extrusions and nerve root contact may be the most important of these findings.

Adult↗

Parametric shape modeling using deformable superellipses for prostate segmentation.

Automatic prostate segmentation in ultrasound images is a challenging task due to speckle noise, missing boundary segments, and complex prostate anatomy. One popular approach has been the use of deformable models. For such techniques, prior knowledge of the prostate shape plays an important role in automating model initialization and constraining model evolution. In this paper, we have modeled the prostate shape using deformable superellipses. This model was fitted to 594 manual prostate contours outlined by five experts. We found that the superellipse with simple parametric deformations can efficiently model the prostate shape with the Hausdorff distance error (model versus manual outline) of 1.32 +/- 0.62 mm and mean absolute distance error of 0.54 +/- 0.20 mm. The variability between the manual outlinings and their corresponding fitted deformable superellipses was significantly less than the variability between human experts with p-value being less than 0.0001. Based on this deformable superellipse model, we have developed an efficient and robust Bayesian segmentation algorithm. This algorithm was applied to 125 prostate ultrasound images collected from 16 patients. The mean error between the computer-generated boundaries and the manual outlinings was 1.36 +/- 0.58 mm, which is significantly less than the manual interobserver distances. The algorithm was also shown to be fairly insensitive to the choice of the initial curve.

Algorithms↗

PET-CT image registration in the chest using free-form deformations.

We have implemented and validated an algorithm for three-dimensional positron emission tomography transmission-to-computed tomography registration in the chest, using mutual information as a similarity criterion. Inherent differences in the two imaging protocols produce significant nonrigid motion between the two acquisitions. A rigid body deformation combined with localized cubic B-splines is used to capture this motion. The deformation is defined on a regular grid and is parameterized by potentially several thousand coefficients. Together with a spline-based continuous representation of images and Parzen histogram estimates, our deformation model allows closed-form expressions for the criterion and its gradient. A limited-memory quasi-Newton optimization algorithm is used in a hierarchical multiresolution framework to automatically align the images. To characterize the performance of the method, 27 scans from patients involved in routine lung cancer staging were used in a validation study. The registrations were assessed visually by two expert observers in specific anatomic locations using a split window validation technique. The visually reported errors are in the 0- to 6-mm range and the average computation time is 100 min on a moderate-performance workstation.

Algorithms↗

Ultrasonography and fluoroscopic fusion for prostate brachytherapy dosimetry.

PURPOSE: To investigate the feasibility of performing postimplant and intraoperative dosimetry for prostate brachytherapy by fusing transrectal ultrasound (TRUS) and fluoroscopic data. METHODS AND MATERIALS: Registration of ultrasound (prostate boundary) and fluoroscopic (seed) data requires spatial markers that are detectable by both imaging modalities. In this study, the needle tips were considered as such fiducials. Prostate phantoms were implanted with the seeds, and four localization needles were inserted. In the TRUS frame of reference, the longitudinal coordinate of the needle tip was determined by advancing the needle until the echo from its tip just registered at a known probe depth. The tip's transverse coordinates were determined from the associated TRUS slice. The three-dimensional needle tip positions were also calculated in the fluoroscopic coordinate system using a seed reconstruction method. The transformation between the TRUS and fluoroscopy coordinate systems was established by the least-squares solution using the singular value decomposition. RESULTS: With three of four needle tips as fiducials and the one remaining needle as a test target, the mean fiducial registration error was 0.8 mm and the test target registration error was 2.5 mm. When all four points were used for registration, the errors decreased to 1.1 mm. A comparison between the proposed method and CT-based dosimetry yielded a percentage of prostate volume receiving 100% and 150% of the prescribed minimal peripheral dose and minimal dose received by 90% of the prostate gland that agreed within 0.4%, 2.7%, and 4.2%, respectively. CONCLUSION: The combination of TRUS and fluoroscopy is a feasible alternative to the currently used CT-based postimplant dosimetry. Furthermore, because of online imaging capability, the method lends itself to real-time intraoperative applications.

Brachytherapy↗

Transcriptome analysis of Escherichia coli using high-density oligonucleotide probe arrays.

Microarrays traditionally have been used to analyze the expression behavior of large numbers of coding transcripts. Here we present a comprehensive approach for high-throughput transcript discovery in Escherichia coli focused mainly on intergenic regions which, together with analysis of coding transcripts, provides us with a more complete insight into the organism's transcriptome. Using a whole genome array, we detected expression for 4052 coding transcripts and identified 1102 additional transcripts in the intergenic regions of the E.coli genome. Further classification reveals 317 novel transcripts with unknown function. Our results show that, despite sophisticated approaches to genome annotation, many cellular transcripts remain unidentified. Through the experimental identification of all RNAs expressed under a specific condition, we gain a more thorough understanding of all cellular processes.

3' Untranslated Regions↗

Identifying operons and untranslated regions of transcripts using Escherichia coli RNA expression analysis.

Microarrays traditionally have been used to assay the transcript expression of coding regions of genes. Here, we use Escherichia coli oligonucleotide microarrays to assay transcript expression of both open reading frames (ORFs) and intergenic regions. We then use hidden Markov models to analyse this expression data and estimate transcription boundaries of genes. This approach allows us to identify 5' untranslated regions (5' UTRs) of transcripts as well as genes that are likely to be operon members. The operon elements we identify correspond to documented operons with 99% specificity and 63% sensitivity. Similarly we find that our 5' UTR results accurately coincide with experimentally verified promoter regions for most genes.

5' Untranslated Regions↗