Ability Of Imaging System Research Articles

Evaluation of Line-Scan Imaging System's Ability to Detect Internal Defects in Tissue Using Improved Monte Carlo Simulation and Optical Density Algorithm

Evaluation of Line-Scan Imaging System's Ability to Detect Internal Defects in Tissue Using Improved Monte Carlo Simulation and Optical Density Algorithm

Artificial Intelligence-enabled, Real-time Intraoperative Ultrasound Imaging of Neural Structures Within the Psoas: Validation in a Porcine Spine Model.

Experimental in-vivo animal study. The aim of this study was to evaluate an Artificial Intelligence (AI)-enabled ultrasound imaging system's ability to detect, segment, classify, and display neural and other structures during trans-psoas spine surgery. Current methodologies for intraoperatively localizing and visualizing neural structures within the psoas are limited and can impact the safety of lateral lumbar interbody fusion (LLIF). Ultrasound technology, enhanced with AI-derived neural detection algorithms, could prove useful for this task. The study was conducted using an in vivo porcine model (50 subjects). Image processing and machine learning algorithms were developed to detect neural and other anatomic structures within and adjacent to the psoas muscle while using an ultrasound imaging system during lateral lumbar spine surgery (SonoVision,™ Tissue Differentiation Intelligence, USA). The imaging system's ability to detect and classify the anatomic structures was assessed with subsequent tissue dissection. Dice coefficients were calculated to quantify the performance of the image segmentation. The AI-trained ultrasound system detected, segmented, classified, and displayed nerve, psoas muscle, and vertebral body surface with high sensitivity and specificity. The mean Dice coefficient score for each tissue type was >80%, indicating that the detected region and ground truth were >80% similar to each other. The mean specificity of nerve detection was 92%; for bone and muscle, it was >95%. The accuracy of nerve detection was >95%. This study demonstrates that a combination of AI-derived image processing and machine learning algorithms can be developed to enable real-time ultrasonic detection, segmentation, classification, and display of critical anatomic structures, including neural tissue, during spine surgery. AI-enhanced ultrasound imaging can provide a visual map of important anatomy in and adjacent to the psoas, thereby providing the surgeon with critical information intended to increase the safety of LLIF surgery.Level of Evidence: N/A.

SU-GG-I-22: Improving Skin-Surface Delineation in Truncated Cone-Beam CT Using Laser Profilometry

PURPOSE: Laser profilometry is a technique where three‐dimensional topographic surface profiles of an object are reconstructed using data acquired with a laser range‐finding system. Axial rotation of a laser range‐finding system around an object can provide enough surface data to allow for this reconstruction. In cone‐beam computed tomography(CBCT), a patient's imaging dose can be reduced by collimating the incident kilovoltage (kV) field; however this comes at the cost of reducing an imaging system's ability to accurately resolve a patient's skin surface. The study described herein is of the implementation of a laser‐profilometry‐based CBCT system which can enhance skin surface delineation while requiring narrower kV imaging beams. MATERIALS AND METHODS: The head‐and‐neck region of an anthropomorphic phantom was imaged using the CBCT feature of the Elekta XVI kV imaging system. During this imaging session, a three‐dimensional skin‐surface was reconstructed using an in‐house laser profilometry system attached to the collimator of the Elekta Axesse's MV treatment beam. This profilometry system is capable of measuring the distance to the surface of an object with an uncertainty of +/− 1.5mm. Skin‐surface reconstructions are then compared with CBCTreconstructions with emphasis placed on delineation of skin boundaries. RESULTS: Coregistration of the reconstructed laser‐defined skin surface with XVI‐generated CBCTreconstruction show strong spatial correlation. CONCLUSION: The detail provided by laser data allows for the narrowing of collimators in kV imaging beams without losing the ability to resolve boundary edges in the imaging subject. Research supported by NIH T32‐CA113267.

Laser-induced fluorescence imaging of subsurface tissue structures with a volume holographic spatial-spectral imaging system

A three-dimensional imaging system incorporating multiplexed holographic gratings to visualize fluorescence tissue structures is presented. Holographic gratings formed in volume recording materials such as a phenanthrenquinone poly(methyl methacrylate) photopolymer have narrowband angular and spectral transmittance filtering properties that enable obtaining spatial-spectral information within an object. We demonstrate this imaging system's ability to obtain multiple depth-resolved fluorescence images simultaneously.

Initial Clinical Experience with Microwave Breast Imaging in Women with Normal Mammography

We have developed a microwave tomography system for experimental breast imaging. In this article, we illustrate a strategy for optimizing the coupling liquid for the antenna array based on in vivo measurement data. We present representative phantom experiments to illustrate the imaging system's ability to recover accurate property distributions over the range of dielectric properties expected to be encountered clinically. To demonstrate clinical feasibility and assess the microwave properties of the normal breast in vivo, we summarize our initial experience with microwave breast exams of 43 women with negative mammography according to the Breast Imaging Reporting and Data System (BI-RADS 1). The clinical results show a high degree of bilateral symmetry in the whole breast average microwave properties. Focal assessments of microwave properties are associated with breast tissue composition evaluated through radiographic density categorization verified through magnetic resonance image correlation in selected cases. Specifically, both whole-breast average and local microwave properties increase with increasing radiographic density, in which the latter exhibits a more substantial rise. These findings support our hypothesis that water content variations in the breast play an influential role in dictating the overall dielectric property distributions and indicate that the microwave properties in the breast are more heterogeneous than previously believed based on ex vivo property measurements reported in the literature.

The future of medical imaging in the detection of early markers of disease.

Imaging techniques are a combination of a contrast mechanism, exogenous or endogenous, and an instrument to exploit that contrast. This final chapter of these two special issues of this journal points to possible ways to improve the ability of imaging systems to exploit markers of cancer in the early detection of that disease. The aim not only is to find cancer at an earlier, more treatable stage, but to determine whether the disease discovered is dangerous and to indicate the possibilities for successful treatment. These topics are explored for each imaging system, with an emphasis on directions for future improvements.

Dental xeroradiography as an adjunct in the evaluation of oral cancer: A preliminary report

This pilot study of an experimental dental xeroradiography imaging system involved twelve oral cancer clinic patients. Xeroradiographs were compared with conventional intraoral film radiographs, taken with similar x-ray projections. The new dental xeroradiographic system was judged superior for the imaging of both osseous and soft-tissue structures. Especially significant was the new imaging system's ability to portray early bone erosion not detectable with the conventional intraoral film technique. These results point to the need for controlled clinical evaluations of dental xeroradiography, in order to assess the full potential of this rapid, low-radiation imaging system in the evaluation of oral cancer.