• AI
  • Molecular Imaging
  • CT
  • X-Ray
  • Ultrasound
  • MRI
  • Facility Management
  • Mammography

Technology start-up plans to turn C-arms into volumetric CT scanners

Article

Conebeam software, CMOS chips lead R&D projectsExxim Computing is starting small. Very small. Its software runs on mouse scanners. Its prototype detectors are based on complementary metal-oxide semiconductor (CMOS) chips. But from

Conebeam software, CMOS chips lead R&D projects

Exxim Computing is starting small. Very small. Its software runs on mouse scanners. Its prototype detectors are based on complementary metal-oxide semiconductor (CMOS) chips. But from these modest beginnings, big things may grow.

The PC-based conebeam reconstruction software now driving mini-CTs is being groomed for premium-performance CT scanners with an embedded algorithm called SAMARA (streak and metal artifact reduction algorithm that cleans up the distortions on CT images from high-density metal objects. CMOS development efforts are being channeled into two project areas, one aimed at creating a low-dose fluoroscopy system; the other at coming up with smart "systems on chips" that will simplify system integration and reduce the cost of products. Near at hand is a C-arm retrofit package that promises to turn virtually any minimally functional C-arm fluoro system into a high-resolution, volumetric CT scanner.

The new technologies in this grab bag have a common thread: all address problems of fundamental importance to image quality, according to Horst Bruning, Ph.D., who founded the Pleasanton, CA, company in 2002. Exxim, whose name is derived from the term "extreme x-ray imaging," is taking simple steps first.

"We are engineers," Bruning said. "So our first objective is to try to get them to work."

The adaptation of conebeam algorithms for small-animal scanners was their first priority. It was chosen at the request of a manufacturer of these systems. Having succeeded at this task, Bruning and his staff now want to see the reconstruction software used in all small-animal scanners. They make a compelling argument.

Using a dual 2.6-GHz Pentium 4 PC with 256 MB of RAM running Windows NT, 2000, or XP, 2D projections are converted into 3D images of 512 cubed pixels in about 40 seconds. (The calculations can be run on a Pentium 3 system, but they will take longer.) The software, which is built around the Feldkamp algorithm, can be implemented as a stand-alone application or as part of a software developer's kit.

The firm is also developing CMOS chips that might be supplied to OEMs for use in solid-state x-ray detectors. The chips can be butted together on all four sides to create detectors useful in radiography and fluoroscopy. Early tests indicate that such detectors produce less noise and a higher dynamic range than amorphous silicon panels, with no ghosting.

A 16-bit radiography/fluoroscopy panel fashioned from these chips could deliver up to 60 frames per second at a resolution of 100 microns. Analog-to-digital converters are being built into each chip, enhancing system design and integration. The modular concept allows the custom assembly of detectors as large as 17 inches across.

Exxim might step up and become a device manufacturer, if plans to sell C-arm retrofits come through. Bruning envisions mobile C-arms in operating rooms, the ER, and small orthopedic clinics working as volumetric CTs. Data would be acquired during a single 30-second half-rotation, reconstructed into 3D data sets using conebeam CT algorithms, then displayed on PC-based 3D workstations.

The upgrade would be compatible with C-arms that provide at least eight frames per second in pulse mode. Little or no hardware modification would be needed. Consequently, the C-arm could be used as originally intended for applications that do not require 3D imaging.

The retrofit technology is in the final stages of development. Bruning expects to produce clinical images later this year. A retrofitted system will be best suited to conduct exams of the head, neck, and extremities. It will not, however, be much use in abdominal studies.

"The image intensifiers on these C-arms are not great detectors," he said. "They work for the wrist, ankle, and knee, but using an II to do the abdomen would be very hard."

Bruning hopes to develop the means to advance CT beyond multislice designs to what he describes as the "ultimate time-resolved volume scanner." SAMARA will play an important role in this evolution. This software gets rid of the streaks that appear across the reconstructed slices. These may occur from aliasing or undersampling, isolated measurement errors, or inconsistent data. SAMARA selectively filters and reconstructs the data to keep structures intact, while subtracting artifacts.

"You have to go back to the raw data," Bruning said. "You can't use postprocessing to get rid of the streaks."

Company strategists hope to build toward this future by providing advanced conebeam software to radiotherapy companies to reconstruct data obtained on CT simulators. The software, which would be used for online patient positioning control, could fill a critical gap created by the growing popularity of intensity-modulated radiotherapy.

"IMRT requires submillimeter precision," Bruning said. "We can provide that with a volumetric image of the patient moments before the therapy begins. Otherwise, you just hope the patient will be in the right position."

Related Videos
Can Fiber Optic RealShape (FORS) Technology Provide a Viable Alternative to X-Rays for Aortic Procedures?
Does Initial CCTA Provide the Best Assessment of Stable Chest Pain?
Making the Case for Intravascular Ultrasound Use in Peripheral Vascular Interventions
Can Diffusion Microstructural Imaging Provide Insights into Long Covid Beyond Conventional MRI?
Assessing the Impact of Radiology Workforce Shortages in Rural Communities
Emerging MRI and PET Research Reveals Link Between Visceral Abdominal Fat and Early Signs of Alzheimer’s Disease
Reimbursement Challenges in Radiology: An Interview with Richard Heller, MD
Nina Kottler, MD, MS
The Executive Order on AI: Promising Development for Radiology or ‘HIPAA for AI’?
Related Content
© 2024 MJH Life Sciences

All rights reserved.