An X-ray scatter system for material identification in cluttered objects: A Monte Carlo simulation study

Lakshmanan, Manu N.; Kapadia, Anuj J.; Sahbaee, Pooyan; Wolter, Scott D.; Harrawood, Brian P.; Brady, David J.; Samei, Ehsan

doi:10.1016/j.nimb.2014.05.021

Cited by 13 publications

(7 citation statements)

References 35 publications

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“…Kapadia et al 9 used a coded-aperture x-ray scatter imaging system and a GEANT4 simulation to study coherent scatter diffraction patterns. Similar results were found by Elshemey et al 10 Lakshmanan et al 11,12 described a tumor margin evaluation method based on x-ray coherent scatter computed tomography imaging using a Monte Carlo Geant4 code. The resulting images distinguish cancerous tumors embedded in complex distributions of adipose and fibroglandular tissue.…”

Section: Introductionsupporting

confidence: 80%

Coherent scatter imaging Monte Carlo simulation

Hassan

MacDonald

2016

J. Med. Imag

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Abstract. Conventional mammography can suffer from poor contrast between healthy and cancerous tissues due to the small difference in attenuation properties. Coherent scatter slot scan imaging is an imaging technique which provides additional information and is compatible with conventional mammography. A Monte Carlo simulation of coherent scatter slot scan imaging was performed to assess its performance and provide system optimization. Coherent scatter could be exploited using a system similar to conventional slot scan mammography system with antiscatter grids tilted at the characteristic angle of cancerous tissues. System optimization was performed across several parameters, including source voltage, tilt angle, grid distances, grid ratio, and shielding geometry. The simulated carcinomas were detectable for tumors as small as 5 mm in diameter, so coherent scatter analysis using a wide-slot setup could be promising as an enhancement for screening mammography. Employing coherent scatter information simultaneously with conventional mammography could yield a conventional high spatial resolution image with additional coherent scatter information.

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Section: Introductionsupporting

confidence: 80%

Coherent scatter imaging Monte Carlo simulation

Hassan

MacDonald

2016

J. Med. Imag

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“…Therefore, the simulation needed to be modified to more accurately model the angular distribution of coherent scattering in molecules and complex structures. In the Geant4 simulation, we modified the physics source code (Lakshmanan et al 2014) to incorporate experimentally measured differential coherent scatter cross sections corresponding to adipose, fibroglandular, normal and cancerous breast tissue. All other physics and tracking aspects of Geant4 were left unchanged (Kapadia et al 2013a).…”

Section: Simulation Of Coherent Scatter Physicsmentioning

confidence: 99%

Volumetric x-ray coherent scatter imaging of cancer in resected breast tissue: a Monte Carlo study using virtual anthropomorphic phantoms

Lakshmanan

Harrawood²,

Samei³

et al. 2015

Phys. Med. Biol.

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Breast cancer patients undergoing surgery often choose to have a breast conserving surgery (BCS) instead of mastectomy for removal of only the breast tumor. If post-surgical analysis such as histological assessment of the resected tumor reveals insufficient healthy tissue margins around the cancerous tumor, the patient must undergo another surgery to remove the missed tumor tissue. Such re-excisions are reported to occur in 20%-70% of BCS patients. A real-time surgical margin assessment technique that is fast and consistently accurate could greatly reduce the number of re-excisions performed in BCS. We describe here a tumor margin assessment method based on x-ray coherent scatter computed tomography (CSCT) imaging and demonstrate its utility in surgical margin assessment using Monte Carlo simulations. A CSCT system was simulated in GEANT4 and used to simulate two virtual anthropomorphic CSCT scans of phantoms resembling surgically resected tissue. The resulting images were volume-rendered and found to distinguish cancerous tumors embedded in complex distributions of adipose and fibroglandular breast tissue (as is expected in the breast). The images exhibited sufficient spatial and spectral (i.e. momentum transfer) resolution to classify the tissue in any given voxel as healthy or cancerous. ROC analysis of the classification accuracy revealed an area under the curve of up to 0.97. These results indicate that coherent scatter imaging is promising as a possible fast and accurate surgical margin assessment technique.

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“…Based on our other investigations using thicker objects, 29 the imaging system can be optimized to image thicker objects such as compressed breasts typically imaged through mammography. These findings suggest that coherent scatter imaging could potentially evolve as a standalone diagnostic tool or serve as a complementary tool to mammography for breast cancer detection.…”

Section: Accuracy Of Imaging System and Potential Medical Applicationsmentioning

confidence: 99%

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples

et al. 2016

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Abstract. A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice.

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An X-ray scatter system for material identification in cluttered objects: A Monte Carlo simulation study

Cited by 13 publications

References 35 publications

Coherent scatter imaging Monte Carlo simulation

Coherent scatter imaging Monte Carlo simulation

Volumetric x-ray coherent scatter imaging of cancer in resected breast tissue: a Monte Carlo study using virtual anthropomorphic phantoms

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples

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