Raghav Raman

Fully Automated System for Three-Dimensional Bronchial Morphology Analysis Using Volumetric Multidetector Computed Tomography of the Chest

Recent advancements in computed tomography (CT) have enabled quantitative assessment of severity and progression of large airway damage in chronic pulmonary disease. The advent of fast multidetector computed tomography scanning has allowed the acquisition of rapid, low-dose 3D volumetric pulmonary scans that depict the bronchial tree in great detail. Volumetric CT allows quantitative indices of bronchial airway morphology to be calculated, including airway diameters, wall thicknesses, wall area, airway segment lengths, airway taper indices, and airway branching patterns. However, the complexity and size of the bronchial tree render manual measurement methods impractical and inaccurate. We have developed an integrated software package utilizing a new measurement algorithm termed mirror-image Gaussian fit that enables the user to perform automated bronchial segmentation, measurement, and database archiving of the bronchial morphology in high resolution and volumetric CT scans and also allows 3D localization, visualization, and registration.

Opportunistic enteroviral meningoencephalitis: an unusual treatable complication of rituximab therapy.

Department of Oncology, Medical Services, Palo Alto Veterans Affairs Health Care System, Stanford University, Palo Alto, CA, USA, Department of Radiology, Palo Alto Veterans Affairs Health Care System, Stanford University, Palo Alto, CA, USA, and Department of Pathology, Palo Alto Veterans Affairs Health Care System, Stanford University School of Medicine and Laboratory Service, Palo Alto, CA, USA

Semiautomated Quantification of the Mass and Distribution of Vascular Calcification with Multidetector CT: Method and Evaluation

Institutional review board approval was obtained for this HIPAA-compliant study. Informed consent was obtained for prospective evaluation in 21 asymptomatic volunteers (10 women, 11 men; mean age, 60 years) but waived for retrospective (10 patients with and five patients without disease) evaluation. Prospective validation was in phantoms. Quantification of mass and calcium distribution was performed with fast semiautomated method, without calibration. For actual versus measured mass in phantoms, R(2) was 0.98; absolute and percentage errors were 1.2 mg and 9.1%, respectively. In asymptomatic volunteers, mean interscan variability for calcium mass quantification in extracoronary arteries was 24.9 mg; mean was 991 units for Agatston scoring. In coronary arteries, mean variability was 5.5 mg; mean Agatston variability was 27.7 units. At retrospective computed tomography, mean total calcified mass was 321.3 mg. Accurate quantification of mass and distribution of calcification in simulated arteries with this method can be applied in vivo, with low interscan variability.

Automated Quantification of Aortoaortic and Aortoiliac Angulation for Computed Tomographic Angiography of Abdominal Aortic Aneurysms before Endovascular Repair: Preliminary Study

The degree of angulation of abdominal aortic aneurysms (AAAs) has emerged as an important factor in assessing eligibility for endovascular aneurysm repair (EVAR). The authors developed an automatic algorithm that reduces variability of measurement of aortoiliac angulation. For highly structured manual methods, intraobserver variability was 8.2 degrees ± 5.0 (31% ± 20) and interobserver variability was 5.6 degrees ± 2.5 (20% ± 9.1) compared with 0.6 degrees ± 0.8 (2.2% ± 3.6) (intraobserver) and 0.4 degrees ± 0.4 (1.4% ± 1.9) (interobserver) for the automatic algorithm (P < .01). In phantoms, the automatically measured angles were equivalent to reference values (P < .05). This algorithm was also faster than manual methods and has the potential to enhance the clinical utility and reliability of computed tomographic angiography for preoperative assessment for EVAR.

An airway phantom to standardize CT acquisition in multicenter clinical trials.

RATIONALE AND OBJECTIVES The purpose of this study was to demonstrate the use of a phantom to standardize low-dose chest computed tomographic (CT) protocols in children with cystic fibrosis. MATERIALS AND METHODS Spiral chest CT scans of a Plexiglas phantom simulating airway sizes (internal diameter, 1.1-16.4 mm; wall thickness, 0.4-4.6 mm) in children with cystic fibrosis were obtained using two multidetector CT (MDCT) scanners (GE VCT and Siemens Sensation 64). Quantitative airway measurements from both scanners were compared with micro-CT airway measurements over a range of doses (0.2-1.8 mSv) to evaluate bias and variance of measurements. The effective doses for CT protocols were estimated using the ImPACT CT Patient Dosimetry Calculator. RESULTS Both MDCT scanners were able to accurately measure airway sizes down to 3 mm internal diameter and 1.3 mm airway wall thickness, with errors of <3.5%. ImPACT estimates of effective dose were different for the MDCT scanners for a given peak tube voltage and product of tube current and exposure time. Accuracy and precision were not found to be associated with dose parameters for either machine. Bias in all measurements was strongly associated with airway diameter (P values < .00001), but the magnitude of bias was small (mean, 0.07 mm; maximum, 0.21 mm). Differences between machines in error components were on the order of a few micrometers. CONCLUSIONS The use of a standard airway phantom confirms that different MDCT scanners have similar results within dose ranges planned for potential future clinical trials. Standardized protocols can be developed that adjust for differences in radiation exposure for different MDCT scanners.

Development and Validation of Automated 2D–3D Bronchial Airway Matching to Track Changes in Regional Bronchial Morphology Using Serial Low-Dose Chest CT Scans in Children with Chronic Lung Disease

To address potential concern for cumulative radiation exposure with serial spiral chest computed tomography (CT) scans in children with chronic lung disease, we developed an approach to match bronchial airways on low-dose spiral and low-dose high-resolution CT (HRCT) chest images to allow serial comparisons. An automated algorithm matches the position and orientation of bronchial airways obtained from HRCT slices with those in the spiral CT scan. To validate this algorithm, we compared manual matching vs automatic matching of bronchial airways in three pediatric patients. The mean absolute percentage difference between the manually matched spiral CT airway and the index HRCT airways were 9.4 ± 8.5% for the internal diameter measurements, 6.0 ± 4.1% for the outer diameter measurements, and 10.1 ± 9.3% for the wall thickness measurements. The mean absolute percentage difference between the automatically matched spiral CT airway measurements and index HRCT airway measurements were 9.2 ± 8.6% for the inner diameter, 5.8 ± 4.5% for the outer diameter, and 9.9 ± 9.5% for the wall thickness. The overall difference between manual and automated methods was 2.1 ± 1.2%, which was significantly less than the interuser variability of 5.1 ± 4.6% (p < 0.05). Tests of equivalence had p < 0.05, demonstrating no significant difference between the two methods. The time required for matching was significantly reduced in the automated method (p < 0.01) and was as accurate as manual matching, allowing efficient comparison of airways obtained on low-dose spiral CT imaging with low-dose HRCT scans.

Improved speed of bone removal in computed tomographic angiography using automated targeted morphological separation: method and evaluation in computed tomographic angiography of lower extremity occlusive disease.

We developed an automated algorithm for bone removal in computed tomographic angiographic images that identifies and deletes connections between bone and vessels. Our automated algorithm is significantly faster than manual methods (2.45 minutes vs 73 minutes) and only generates about 2 small artifactual deletions per patient, mostly in the region of the ankle. Image quality was equivalent to manual methods. It shows promise as a tool for fast and accurate postprocessing of computed tomographic angiograms.

Automated creation of radiology teaching modules: demonstration of PACS integration and distribution

The creation of radiology teaching modules has historically required manual offline authoring. Our system can integrate with commercial PACS to allow clinicians to author teaching modules at their clinical PACS workstations without further manual input. Our system provides a DICOM interface and an automated teaching file database. We tested our system with the PACS deployed at our institution (GE Medical Systems, Milwaukee, WI). We used a networked Windows workstation (Microsoft, Redmond, WA) running SQL Server 2000, registered on our PACS system as a DICOM receiver. Teaching files were created at clinical workstations and any desired annotation and cataloguing instructions were added using standard annotation tools. The files were pushed using DICOM network transfer. Anonymizing, annotation and cataloguing were done automatically using DICOM header information. Additional information from our HIS/RIS system was transmitted using private DICOM header fields. Teaching files were then added to the web - accessible teaching module database. We present a system that integrates the creation of teaching files into the daily clinical workflow, allowing clinicians to immediately publish interesting cases from their clinical workstation. Our system uses standard protocols and requires minimal configuration to integrate with existing PACS systems, enabling a low-cost, expandable and vendor independent solution.

Handheld Access to Radiology Teaching Files: An Automated System for Format Conversion and Content Creation

Current handheld Personal Digital Assistants (PDAs) can be used to view radiology teaching files. We have developed a toolkit that allows rapid creation of radiology teaching files in handheld formats from existing repositories. Our toolkit incorporated a desktop converter, a web conversion server and an application programming interface (API). Our API was integrated with an existing pilot teaching file database. We evaluated our system by obtaining test DICOM and JPEG images from our PACS system, our pilot database and from personal collections and converting them on a Windows workstation (Microsoft, Redmond, CA) and on other platforms using the web server. Our toolkit anonymized, annotated and categorized images using DICOM header information and data entered by the authors. Image processing was automatically customized for the target handheld device. We used freeware handheld image viewers as well as our custom applications that allowed window/level manipulation and viewing of additional textual information. Our toolkit provides desktop and web access to image conversion tools to produce organized handheld teaching file packages for most handheld devices and our API allows existing teaching file databases to incorporate handheld compatibility. The distribution of radiology teaching files on PDAs can increase the accessibility to radiology teaching.