Assessing The Performance Characteristics of Handheld Ultrasound In A Rheumatic Heart Disease Screening Program

Background: Rheumatic heart disease affects 33 million people in low and middle income countries and is the leading cause of cardiovascular death among children and young adults. Penicillin prophylaxis has been shown to improve valvular function among patients with clinically silent or mild disease. Efforts to expand echocardiographic screening are focusing on simplified protocols, non-physician ultrasonographers, and portable ultrasound devices, including handheld ultrasound. Recent advances support the use of single-view screening protocols. With the increasing availability and low cost of handheld devices, prospective studies are needed to evaluate their performance in these settings. Methods: We conducted a cross-sectional pilot study among 19 at-risk school-children participating in a rheumatic heart disease screening program in Ethiopia comparing a handheld ultrasound device (Phillips Lumify) to a fully-equipped portable ultrasound machine (Sonosite M-Turbo). Results: Agreement between devices was similar for expert and non-expert review (84%). However, when reviewed by a non-expert the Lumify identified fewer screen-positive cases (p-value 0.083). We also compared non-expert to expert interpretation by device and found a significant difference in interpretation for the Lumify (p-value 0.025). There was a trend towards shorter jet length by color Doppler in the handheld ultrasound device for both expert and non-expert review. Conclusions: Our study highlights that screening echocardiograms for RHD may yield different results when a handheld ultrasound device is used.

Acoustic-Field Beamforming-Based Generalized Coherence Factor for Handheld Ultrasound

Handheld ultrasound devices have been widely used for diagnostic applications. The use of the acoustic-field beamforming (AFB) method has been proposed for handheld ultrasound to reduce electricity consumption and avoid battery and unwanted heat issues. However, the image quality, such as the contrast ratio and contrast-to-noise-ratio, are poorer with this technique than with the conventional delay-and-sum method. To address the problems associated with the worse image quality in AFB imaging, in this paper we propose the use of an AFB-based generalized coherence factor (GCF) technique, in which the GCF weighting developed for adaptive beamforming is extended to AFB. Simulation data, experimental results, and in vivo testing verified the efficacy of our proposed AFB-based GCF technique.

Handheld Versus Conventional Ultrasound for Assessing Carotid Artery in Routine Volunteers

Objective: The study aimed to estimate the feasibility and accuracy of carotid intima-media thickness (CIMT) and hemodynamic parameters measurement in a handheld ultrasound device.Methods: Utilizing an ex vivo pig carotid artery sample, CIMT was measured with a handheld ultrasound and compared with histopathology. Then we performed a carotid ultrasound on 25 volunteers using a handheld ultrasound device and a conventional ultrasound system. After a week, these volunteers were scanned again by the same observer. Assessments of the max IMT, mean IMT and hemodynamic parameters (PSV, EDV, PI, RI, S/D, ACCEL, AT, TAMEAN) were compared. Intraclass correlation coefficient (ICC) was used to assess inter-device agreement. Repeatability and correlation of mean IMT were analyzed by Bland–Altman Plots and linear correlation analysis. Results: The mean IMT measured from the common carotid artery by handheld ultrasound showed good agreement (ICC=0.79) with conventional ultrasound. Furthermore, we obtained good repeatability and a consistent trend in the mean value of IMT before and after (r = 0.680, P < 0.01). In addition, the max IMT and the hemodynamic parameters (PSV, EDV, S/D, ACCEL, TAMEAN) showed moderate agreement (ICC=0.73, 0.52, 0.58, 0.70, 0.61, 0.51, respectively). The PI, RI and HR values were excellent agreement with conventional ultrasound (ICC=0.80, 0.84, 0.94). Conclusion: About the basic assessment of carotid, the images and parameters obtained using handheld ultrasound showed a moderate to excellent agreement with conventional ultrasound. The handheld ultrasonic devices can be widely used as a diagnostic tool for carotid artery structure and hemodynamics examination.

Usefulness of combined handheld ultrasound and fluoroscopy-guided injection in adhesive capsulitis of the shoulder: A prospective, randomized single blind-pilot study

BACKGROUND: Ultrasound is increasingly being utilized in the diagnosis and treatment of adhesive capsulitis. OBJECTIVE: To compare the therapeutic effects and advantages of combined handheld ultrasound and fluoroscopy-guided intra-articular corticosteroid injection with those of conventional ultrasound-guided corticosteroid injection in adhesive capsulitis of the shoulder. METHODS: A total of 39 patients diagnosed with adhesive capsulitis of the shoulder were randomly assigned into two groups. Group A patients (n= 19) underwent combined handheld ultrasound and fluoroscopy-guided corticosteroid injection and group B patients (n= 20) underwent conventional ultrasound-guided corticosteroid injection to the intra-articular space of the shoulder twice. Treatment efficacy was assessed at 2 and 6 weeks after the final injection, based on the verbal numeric pain scale, Shoulder Pain and Disability Index, and range of motion. Secondary outcome measures were the accuracy and procedure time. RESULTS: Both injection methods were effective in the treatment of adhesive capsulitis. No significant differences in treatment efficacy and injection accuracy were observed between the two groups (p> 0.05). CONCLUSIONS: This study showed no statistical differences in treatment efficacy between 2 groups. However, the combined use of ultrasound and fluoroscopy can increase the accuracy of injection compared with conventional ultrasound alone.

The lesion detection efficacy of deep learning on automatic breast ultrasound and factors affecting its efficacy: a pilot study

Objectives: The aim of this study was to investigate the detection efficacy of deep learning (DL) for automatic breast ultrasound (ABUS) and factors affecting its efficacy. Methods: Women who underwent ABUS and handheld ultrasound from May 2016 to June 2017 (N = 397) were enrolled and divided into training (n = 163 patients with breast cancer and 33 with benign lesions), test (n = 57) and control (n = 144) groups. A convolutional neural network was optimised to detect lesions in ABUS. The sensitivity and false positives (FPs) were evaluated and compared for different breast tissue compositions, lesion sizes, morphologies and echo patterns. Results: In the training set, with 688 lesion regions (LRs), the network achieved sensitivities of 93.8%, 97.2 and 100%, based on volume, lesion and patient, respectively, with 1.9 FPs per volume. In the test group with 247 LRs, the sensitivities were 92.7%, 94.5 and 96.5%, respectively, with 2.4 FPs per volume. The control group, with 900 volumes, showed 0.24 FPs per volume. The sensitivity was 98% for lesions > 1 cm3, but 87% for those ≤1 cm3 (p < 0.05). Similar sensitivities and FPs were observed for different breast tissue compositions (homogeneous, 97.5%, 2.1; heterogeneous, 93.6%, 2.1), lesion morphologies (mass, 96.3%, 2.1; non-mass, 95.8%, 2.0) and echo patterns (homogeneous, 96.1%, 2.1; heterogeneous 96.8%, 2.1). Conclusions: DL had high detection sensitivity with a low FP but was affected by lesion size. Advances in knowledge: DL is technically feasible for the automatic detection of lesions in ABUS.