Exploring advanced 2D acquisitions in breast tomosynthesis: T-shaped and Pentagon geometries.

In this study, we investigate the performance of advanced 2D acquisition geometries - Pentagon and T-shaped - in digital breast tomosynthesis (DBT) and compare them against the conventional 1D geometry. Unlike the conventional approach, our proposed 2D geometries also incorporate anterior projections away from the chest wall. Implemented on the Next-Generation Tomosynthesis (NGT) prototype developed by X-ray Physics Lab (XPL), UPenn, we utilized various phantoms to compare three geometries: a Defrise slab phantom with alternating plastic slabs to study low-frequency modulation; a Checkerboard breast phantom (a 2D adaptation of the Defrise phantom design) to study the ability to reconstruct the fine features of the checkerboard squares; and the 360° Star-pattern phantom to assess aliasing and compute the Fourier-spectral distortion (FSD) metric that assesses spectral leakage and the contrast transfer function.

Non-Isocentric Geometry for Next-Generation Tomosynthesis With Super-Resolution.

Our lab at the University of Pennsylvania (UPenn) is investigating novel designs for digital breast tomosynthesis. We built a next-generation tomosynthesis system with a non-isocentric geometry (superior-to-inferior detector motion). This paper examines four metrics of image quality affected by this design.

Impact of super-resolution and image acquisition on the detection of calcifications in digital breast tomosynthesis.

Objectives: A virtual clinical trial (VCT) method is proposed to determine the limit of calcification detection in tomosynthesis.

Methods: Breast anatomy, focal findings, image acquisition, and interpretation (n = 14 readers) were simulated using screening data (n = 660 patients). Calcifications (0.

Impact of Tomosynthesis Acquisition on 3D Segmentations of Breast Outline and Adipose/Dense Tissue with AI: A Simulation-Based Study.

Digital breast tomosynthesis (DBT) reconstructions introduce out-of-plane artifacts and false-tissue boundaries impacting the dense/adipose and breast outline (convex hull) segmentations. A virtual clinical trial method was proposed to segment both the breast tissues and the breast outline in DBT reconstructions. The DBT images of a representative population were simulated using three acquisition geometries: a left-right scan (conventional, I), a two-directional scan in the shape of a "T" (II), and an extra-wide range (XWR, III) left-right scan at a six-times higher dose than I.

Assessing satisfaction of search in virtual mammograms for experienced and novice searchers.

Purpose: Satisfaction of search (SOS) is a phenomenon where searchers are more likely to miss a lesion/target after detecting a first lesion/target. Here, we investigated SOS for masses and calcifications in virtual mammograms with experienced and novice searchers to determine the extent to which: (1) SOS affects breast lesion detection, (2) similarity between lesions impacts detection, and (3) experience impacts SOS rates.

Approach: The open virtual clinical trials framework was used to simulate the breast anatomy of patients, and up to two simulated masses and/or single-calcifications were inserted into the breast models.

Multiclass Segmentation of Breast Tissue and Suspicious Findings: A Simulation-Based Study for the Development of Self-Steering Tomosynthesis.

In breast tomosynthesis, multiple low-dose projections are acquired in a single scanning direction over a limited angular range to produce cross-sectional planes through the breast for three-dimensional imaging interpretation. We built a next-generation tomosynthesis system capable of multidirectional source motion with the intent to customize scanning motions around "suspicious findings". Customized acquisitions can improve the image quality in areas that require increased scrutiny, such as breast cancers, architectural distortions, and dense clusters.

Multiclass Segmentation of Suspicious Findings in Simulated Breast Tomosynthesis Images Using a U-Net.

Our lab has built a next-generation tomosynthesis (NGT) system utilizing scanning motions with more degrees of freedom than clinical digital breast tomosynthesis systems. We are working toward designing scanning motions that are customized around the locations of suspicious findings. The first step in this direction is to demonstrate that these findings can be detected with a single projection image, which can guide the remainder of the scan.

Spatial dependency of lesion detectability in digital breast tomosynthesis.

X-ray imaging results in inhomogeneous irradiation of the detector and distortion of structures in the periphery of the image; yet the spatial dependency of tomosynthesis image-quality metrics has not been extensively investigated. In this study, we use virtual clinical trials to quantify the spatial dependency of lesion detectability in our lab's next-generation tomosynthesis (NGT) system. Two geometries were analyzed: a conventional geometry with mediolateral source motion, and a NGT geometry with T-shaped motion.

MaasPenn Radiomics Reproducibility Score: A Novel Quantitative Measure for Evaluating the Reproducibility of CT-Based Handcrafted Radiomic Features.

The reproducibility of handcrafted radiomic features (HRFs) has been reported to be affected by variations in imaging parameters, which significantly affect the generalizability of developed signatures and translation to clinical practice. However, the collective effect of the variations in imaging parameters on the reproducibility of HRFs remains unclear, with no objective measure to assess it in the absence of reproducibility analysis. We assessed these effects of variations in a large number of scenarios and developed the first quantitative score to assess the reproducibility of CT-based HRFs without the need for phantom or reproducibility studies.

Computer simulations of case difficulty in digital breast tomosynthesis using virtual clinical trials.

Purpose: Virtual clinical trials (VCTs) require computer simulations of representative patients and images to evaluate and compare changes in performance of imaging technologies. The simulated images are usually interpreted by model observers whose performance depends upon the selection of imaging cases used in training evaluation models. This work proposes an efficient method to simulate and calibrate soft tissue lesions, which matches the detectability threshold of virtual and human readings.

Novel Perlin-based Phantoms Using 3D Models of Compressed Breast Shape and Fractal Noise.

Virtual clinical trials (VCTs) have been used widely to evaluate digital breast tomosynthesis (DBT) systems. VCTs require realistic simulations of the breast anatomy (phantoms) to characterize lesions and to estimate risk of masking cancers. This study introduces the use of Perlin-based phantoms to optimize the acquisition geometry of a novel DBT prototype.

Pre-clinical evaluation and optimization of image quality for a Next Generation Tomosynthesis prototype.

A next generation tomosynthesis (NGT) prototype has been developed to investigate alternative scanning geometries for digital breast tomosynthesis (DBT). The NGT system uses a 2D plane as an address space for the x-ray source to define an acquisition geometry. In previous work, tests of physics have been used as objective metrics to evaluate image quality for NGT.

Achieving Isotropic Super-Resolution with a Non-Isocentric Acquisition Geometry in a Next-Generation Tomosynthesis System.

We have constructed a prototype next-generation tomosynthesis (NGT) system that supports a non-isocentric acquisition geometry for digital breast tomosynthesis (DBT). In this geometry, the detector gradually descends in the superior-to-inferior direction. The aim of this work is to demonstrate that this geometry offers isotropic super-resolution (SR), unlike clinical DBT systems which are characterized by anisotropies in SR.

Reply to Orlhac, F.; Buvat, I. Comment on "Ibrahim et al. The Effects of In-Plane Spatial Resolution on CT-Based Radiomic Features' Stability with and without ComBat Harmonization. 2021, , 1848".

We would like to thank Orlhac and Buvat [...

VIRTUAL CLINICAL TRIALS IN MEDICAL IMAGING SYSTEM EVALUATION AND OPTIMISATION.

Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs of medical imaging, with a particular focus on breast imaging.

Computational Breast Anatomy Simulation Using Multi-Scale Perlin Noise.

Virtual clinical trials (VCTs) of medical imaging require realistic models of human anatomy. For VCTs in breast imaging, a multi-scale Perlin noise method is proposed to simulate anatomical structures of breast tissue in the context of an ongoing breast phantom development effort. Four Perlin noise distributions were used to replace voxels representing the tissue compartments and Cooper's ligaments in the breast phantoms.

The Effects of In-Plane Spatial Resolution on CT-Based Radiomic Features' Stability with and without ComBat Harmonization.

While handcrafted radiomic features (HRFs) have shown promise in the field of personalized medicine, many hurdles hinder its incorporation into clinical practice, including but not limited to their sensitivity to differences in acquisition and reconstruction parameters. In this study, we evaluated the effects of differences in in-plane spatial resolution (IPR) on HRFs, using a phantom dataset (n = 14) acquired on two scanner models. Furthermore, we assessed the effects of interpolation methods (IMs), the choice of a new unified in-plane resolution (NUIR), and ComBat harmonization on the reproducibility of HRFs.

Next generation tomosynthesis image acquisition optimization for dedicated PET-DBT attenuation corrections.

A next generation tomosynthesis (NGT) prototype is under development to investigate alternative acquisition geometries for digital breast tomosynthesis (DBT). A positron emission tomography (PET) device will be integrated into the NGT prototype to facilitate DBT acquisition followed immediately by PET acquisition (PET-DBT). The aim of this study was to identify custom acquisition geometries that (1) improve dense/adipose tissue classification and (2) improve breast outline segmentation.

Signal-to-Noise Ratio and Contrast-to-Noise Ratio Measurements for Next Generation Tomosynthesis.

It is standard for the x-ray source in conventional digital breast tomosynthesis (DBT) acquisitions to move strictly along the chest wall of the patient. A prototype, next-generation tomosynthesis (NGT) system has been developed that is capable of acquiring customized geometries with source motion parallel and perpendicular to the chest wall. One well-known consequence of acquiring projections with the x-ray source anterior to the chest wall is that a small volume of tissue adjacent to the chest wall is missed.

Under-exploration of Three-Dimensional Images Leads to Search Errors for Small Salient Targets.

Advances in 3D imaging technology are transforming how radiologists search for cancer and how security officers scrutinize baggage for dangerous objects. These new 3D technologies often improve search over 2D images but vastly increase the image data. Here, we investigate 3D search for targets of various sizes in filtered noise and digital breast phantoms.

Evaluating attenuation correction strategies in a dedicated, single-gantry breast PET-tomosynthesis scanner.

We are developing a dedicated, combined breast positron emission tomography (PET)-tomosynthesis scanner. Both the PET and digital breast tomosynthesis (DBT) scanners are integrated in a single gantry to provide spatially co-registered 3D PET-tomosynthesis images. The DBT image will be used to identify the breast boundary and breast density to improve the quantitative accuracy of the PET image.

Evaluation of Convolutional Neural Networks for Search in 1/f Filtered Noise and Digital Breast Tomosynthesis Phantoms.

With the advent of powerful convolutional neural networks (CNNs), recent studies have extended early applications of neural networks to imaging tasks thus making CNNs a potential new tool for assessing medical image quality. Here, we compare a CNN to model observers in a search task for two possible signals (a simulated mass and a smaller simulated micro-calcification) embedded in filtered noise and single slices of Digital Breast Tomosynthesis (DBT) virtual phantoms. For the case of the filtered noise, we show how a CNN can approximate the ideal observer for a search task, achieving a statistical efficiency of 0.

MRMC ROC Analysis of Calcification Detection in Tomosynthesis Using Computed Super Resolution and Virtual Clinical Trials.

Digital breast tomosynthesis (DBT) reduces breast tissue overlap, which is a major limitation of digital mammography. However, DBT does not show significant improvement in calcification detection, because of the limited angle and small number of projections used to reconstruct the 3D breast volume. Virtual clinical trials (VCTs) were used to evaluate the benefits of computed super resolution (SR) and the optimal combination of the acquisition parameters to improve calcification detection in DBT.