Delay-and-sum (DAS) beamforming is widely used for generation of B-mode images from echo signals obtained with an array probe composed of transducer elements. However, the resolution and contrast achieved with DAS beamforming are determined by the physical specifications of the array, e.g., size and pitch of elements. To overcome this limitation, adaptive imaging methods have recently been explored extensively thanks to the dissemination of digital and programmable ultrasound systems. On the other hand, it is also important to evaluate the performance of such adaptive imaging methods quantitatively to validate whether the modification of the image characteristics resulting from the developed method is appropriate. Since many adaptive imaging methods have been developed and they often alter image characteristics, attempts have also been made to update the methods for quantitative assessment of image quality. This article provides a review of recent developments in adaptive imaging and image quality assessment.

In the field of clinical ultrasound, the full digitalization of diagnostic equipment in the 2000s enabled the technological development of quantitative ultrasound (QUS), followed by multiple diagnostic technologies that have been put into practical use in recent years. In QUS, tissue characteristics are quantified and parameters are calculated by analyzing the radiofrequency (RF) echo signals returning to the transducer. However, the physical properties (and pathological level structure) of the biological tissues responsible for the imaging features and QUS parameters have not been sufficiently verified as there are various conditions for observing living tissue with ultrasound and inevitable discrepancies between theoretical and actual measurements. A major issue of QUS in clinical application is that the evaluation results depend on the acquisition conditions of the RF echo signal as the source of the image information, and also vary according to the model of the diagnostic device. In this paper, typical examples of QUS techniques for evaluating attenuation, speed of sound, amplitude envelope characteristics, and backscatter coefficient in living tissues are introduced. Exemplary basic research and clinical applications related to these technologies, and initiatives currently being undertaken to establish the QUS method as a true tissue characterization technology, are also discussed.

It has been recognized that tissue stiffness provides useful diagnostic information, as with palpation as a screening for diseases such as cancer. In recent years, shear wave elastography (SWE), a technique for evaluating and imaging tissue elasticity quantitatively and objectively in diagnostic imaging, has been put into practical use, and the amount of clinical knowledge about SWE has increased. In addition, some guidelines and review papers regarding technology and clinical applications have been published, and the status as a diagnostic technology is in the process of being established. However, there are still unclear points about the interpretation of shear wave speed (SWS) and converted elastic modulus in SWE. To clarify these, it is important to investigate the factors that affect the SWS and elastic modulus. Therefore, physical and engineering factors that potentially affect the SWS and elastic modulus are discussed in this review paper, based on the principles of SWE and a literature review. The physical factors include the propagation properties of shear waves, mechanical properties (viscoelasticity, nonlinearity, and anisotropy), and size and shape of target tissues. The engineering factors include the region of interest depth and signal processing. The aim of this review paper is not to provide an answer to the interpretation of SWS. It is to provide information for readers to formulate and verify the hypothesis for the interpretation. Therefore, methods to verify the hypothesis for the interpretation are also reviewed. Finally, studies on the safety of SWE are discussed.

Purpose: In coherence-based beamforming (CBB) using a generalized coherence factor (GCF), unnecessary signals caused by sidelobes are reduced, and an excellent contrast-to-noise ratio (CNR) is achieved in ultrasound imaging. However, the GCF computation is complex compared to the standard delay-and-sum (DAS) beamforming. In the present study, we propose a method that significantly reduces the number of GCF computations. Methods: In the previously proposed GCF_real, generation of the analytic signal for each element in the conventional GCF could be omitted. Furthermore, in GCF estimated from binarized signals (GCFB) proposed in the present study, the GCF value is calculated after the received signal of each element is binarized to reduce the computational complexity of the GCF. Results: The values of GCFB and GCF_real estimated from simulation and experimental data were compared. We also evaluated the image quality of B-mode images weighted by GCFB and GCF_real. Compared with GCF_real, GCFB was superior in reducing unnecessary signals but tended to reduce the brightness of the diffused scattering media. The CNR improvement was comparable for both methods. Conclusion: Generalized coherence factor estimated from binarized signals exhibits excellent CNR improvement compared to DAS. CNR improvements yielded by GCFB and GCF_real may depend on the observation target; however, under the conditions of the present study, comparable performances were obtained. Because GCFB can significantly reduce the computational complexity, it is potentially applicable in clinical diagnostic equipment.

Purpose: Ultrasound is commonly used to assess the degree of synovitis in patients with rheumatoid arthritis (RA); however, it is unclear which joints are optimal for evaluating and predicting recurrence and remission. Patients and methods: In 293 RA patients enrolled in the KURAMA cohort, 28 joints were assessed by ultrasound. Results: Results from patients in remission in both 2015 and 2017 (Group 1, n＝152) were compared with those from patients in remission in 2015 and non-remission in 2017 (Group 2, n＝60). The SMI scores for total (3.1 vs. 6.3, P＝0.004), MCP2-5 (1.1 vs. 2.4, P＝0.03), wrist (0.9 vs. 2.1, P＝0.0003), MTP2-5 (0.4 vs. 1.0, P＝0.03), and Lisfranc joints (0.07 vs. 0.25, P＝0.04) were significantly higher for Group 2. When those in non-remission in 2015 and remission in 2017 (Group 3, n＝27) were compared with those in remission in 2015 and non-remission in both 2015 and 2017 (Group 4, n＝54), the GS-SMI combined score (3.0 vs. 5.0, P＝0.04) and SMI score (1.5 vs. 2.9, P＝0.04) for MCP2-5 joints were significantly higher for Group 4. Multivariate logistic regression analysis identified “wrist SMI score ≧ 1” as an independent prognostic factor for recurrence (odds ratio 3.08, P＝0.001) and “MCP2-5 GS-SMI combined score ≦ 4” as an independent prognostic factor for remission (odds ratio 3.25, P＝0.048). Conclusion: We identified the optimal joint cut-off scores for predicting recurrence and remission in RA patients. Risk stratification therapy based on the ultrasound scores may improve outcome and quality of life for patients with RA.

Purpose: In recent years, small breast cancers have been increasingly detected using ultrasonography (US). According to the recall criteria established by the Japan Association of Breast and Thyroid Sonology (JABTS), a mass measuring ≤5 mm and lacking ultrasonographic findings of invasion does not require further examination, and only masses with irregular margins should undergo further examinations. However, the small size of these lesions makes it difficult to evaluate their morphology. Therefore, to contribute to future US judgement, this study aimed to examine how breast cancers identified as solid masses measuring ≤5 mm on US were detected and what type of breast cancer they constituted. Subjects and Methods: We retrospectively reviewed the histopathologic types, subtypes, patient backgrounds, detection opportunities, and US findings of breast cancer lesions measuring ≤5 mm with confirmation on US among consecutive cases operated on at our hospital from May 2016 to April 2021. Results and Discussion: Sixteen patients with 16 lesions were included: eight with invasive carcinoma and eight with ductal carcinoma in situ (DCIS). All patients were unaware of their status, and lesions were detected on screening or surveillance, or as incidental lesions during preoperative examinations for other breast cancers. Excluding patients with hereditary breast ovarian cancer syndrome, all patients had hormone receptor-positive low-grade breast cancer, indicating that these cancers might not have affected the patients’ prognosis whether they were detected at that time or at the next year’s screening. Conclusion: Invasive US findings can accurately determine invasive cancer, even for masses measuring ≤5 mm. In the JABTS diagnostic tree, masses measuring ≤5 mm without invasive findings are basically considered to not require a further examination. All of the average-risk cases were low-grade DCIS even in the present results. It is necessary to consider overdiagnosis and overtreatment in the future.