The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities.

Ultrasound image quality is often inherently limited by the physical dimensions of the imaging transducer. We hypothesize that, by collecting synthetic aperture data sets over a range of aperture positions while precisely tracking the position and orientation of the transducer, we can synthesize large effective apertures to produce images with improved resolution and target detectability. We analyze the two largest limiting factors for coherent signal summation: aberration and mechanical uncertainty. Using an excised canine abdominal wall as a model phase screen, we experimentally observed an effective arrival time error ranging from 18.3 ns to 58 ns (root-mean-square error) across the swept positions. Through this clutter-generating tissue, we observed a 72.9% improvement in resolution with only a 3.75 dB increase in side lobe amplitude compared to the control case. We present a simulation model to study the effect of calibration and mechanical jitter errors on the synthesized point spread function. The relative effects of these errors in each imaging dimension are explored, showing the importance of orientation relative to the point spread function. We present a prototype device for performing swept synthetic aperture imaging using a conventional 1-D array transducer and ultrasound research scanner. Point target reconstruction error for a 44.2 degree sweep shows a reconstruction precision of 82.8 μm and 17.8 μm in the lateral and axial dimensions respectively, within the acceptable performance bounds of the simulation model. Improvements in resolution, contrast and contrast-to-noise ratio are demonstrated in vivo and in a fetal phantom.

It has been demonstrated that short-lag spatial coherence (SLSC) ultrasound imaging can provide improved speckle SNR and lesion CNR compared to conventional B-mode images, especially in the presence of noise and clutter. Application of the van Cittert-Zernike theorem predicts that coherence among the ultrasound echoes received across an array is reduced significantly away from the transmit focal depth, leading to a limited axial depth of field in SLSC images. Transmit focus throughout the field of view can be achieved using synthetic aperture methods to combine multiple transmit events into a single final image. A synthetic aperture can be formed with either focused or diverging transmit beams. We explore the application of these methods to form synthetically focused channel data to create SLSC images with an extended axial depth of field. An analytical expression of SLSC image brightness through depth is derived for the dynamic receive focus case. Experimental results in a phantom and in vivo are presented and compared to dynamic receive focused SLSC images, demonstrating improved SNR and CNR away from the transmit focus and an axial depth of field four to five times longer.

Reliable assessment of image quality is an important but challenging task in complex imaging environments such as those encountered in vivo. To address this challenge, we propose a novel imaging metric, known as the lag-one coherence (LOC), which leverages the spatial coherence between nearest-neighbor array elements to provide a local measure of thermal and acoustic noise. In this paper, we derive the theory that relates LOC and the conventional image quality metrics of contrast and contrast-to-noise ratio (CNR) to channel noise. Simulation and phantom studies are performed to validate this theory and compare the variability of LOC to that of conventional metrics. We further evaluate the performance of LOC using matched measurements of contrast, CNR, and temporal correlation from in vivo liver images formed with varying mechanical index (MI) to assess the feasibility of adaptive acoustic output selection using LOC feedback. Simulation and phantom results reveal lower variability in LOC relative to contrast and CNR over a wide range of clinically-relevant noise levels. This improved stability is supported by in vivo measurements of LOC that show increased monotonicity with changes in MI compared to matched measurements of contrast and CNR (88.6% and 85.7% of acquisitions, respectively). The sensitivity of LOC to stationary acoustic noise is evidenced by positive correlations between LOC and contrast (r=0.74) and LOC and CNR (r=0.66) at high acoustic output levels in the absence of thermal noise. Results indicate that LOC provides repeatable characterization of patient-specific trends in image quality, demonstrating feasibility in the selection of acoustic output using LOC and its application for in vivo image quality assessment.