Global Ultrasound Elastography Using Convolutional Neural Network

Displacement estimation is very important in ultrasound elastography and failing to estimate displacement correctly results in failure in generating strain images. As conventional ultrasound elastography techniques suffer from decorrelation noise, they are prone to fail in estimating displacement between echo signals obtained during tissue distortions. This study proposes a novel elastography technique which addresses the decorrelation in estimating displacement field. We call our method GLUENet (GLobal Ultrasound Elastography Network) which uses deep Convolutional Neural Network (CNN) to get a coarse time-delay estimation between two ultrasound images. This displacement is later used for formulating a nonlinear cost function which incorporates similarity of RF data intensity and prior information of estimated displacement. By optimizing this cost function, we calculate the finer displacement by exploiting all the information of all the samples of RF data simultaneously. The Contrast to Noise Ratio (CNR) and Signal to Noise Ratio (SNR) of the strain images from our technique is very much close to that of strain images from GLUE. While most elastography algorithms are sensitive to parameter tuning, our robust algorithm is substantially less sensitive to parameter tuning.Comment: 4 pages, 4 figures; added acknowledgment section, submission type late

Automatic Frame Selection Using MLP Neural Network in Ultrasound Elastography

Ultrasound elastography estimates the mechanical properties of the tissue from two Radio-Frequency (RF) frames collected before and after tissue deformation due to an external or internal force. This work focuses on strain imaging in quasi-static elastography, where the tissue undergoes slow deformations and strain images are estimated as a surrogate for elasticity modulus. The quality of the strain image depends heavily on the underlying deformation, and even the best strain estimation algorithms cannot estimate a good strain image if the underlying deformation is not suitable. Herein, we introduce a new method for tracking the RF frames and selecting automatically the best possible pair. We achieve this by decomposing the axial displacement image into a linear combination of principal components (which are calculated offline) multiplied by their corresponding weights. We then use the calculated weights as the input feature vector to a multi-layer perceptron (MLP) classifier. The output is a binary decision, either 1 which refers to good frames, or 0 which refers to bad frames. Our MLP model is trained on in-vivo dataset and tested on different datasets of both in-vivo and phantom data. Results show that by using our technique, we would be able to achieve higher quality strain images compared to the traditional methods of picking up pairs that are 1, 2 or 3 frames apart. The training phase of our algorithm is computationally expensive and takes few hours, but it is only done once. The testing phase chooses the optimal pair of frames in only 1.9 ms

Disaster experiences, associated problems and lessons in southwestern coastal Bangladesh: exploring through participatory rural appraisal to enhance resilience

The southwestern coastal part of Bangladesh is highly vulnerable to different kinds of disasters due to the changing climatic conditions. With the lenses of rural communities here an approach to examine how were the different disasters experiences, what lesson they learnt and what are their present disaster associated problems and stakeholder’s networks they rely on to enhance their resilience. Qualitative data were collected through participatory rapid rural appraisal (100–150 persons), field observation, 12 focus group discussions (25–40 people/FGD), and key informant interviews (25 people) in four southwestern coastal districts and nine coastal villages of Bangladesh. Results showed that since long back to date drinking water crisis, poor roads, poverty, poor sanitation, and health problems are the main identified disaster-associated problems. After learning lessons from previous disaster experiences, the community people have improved and changed their practices mainly by storing emergency foods, house construction, and increasing disaster awareness. However, the coastal communities are combating with the problems that have both direct and indirect association with poor infrastructures. Therefore, the coastal communities urge and sketched for a better stakeholders’ supports and networks to minimize their problems and thus to enhance communities’ disaster resilience

Primaquine radical cure in patients with Plasmodium falciparum malaria in areas co-endemic for P falciparum and Plasmodium vivax (PRIMA): a multicentre, open-label, superiority randomised controlled trial

Background In areas co-endemic for Plasmodium vivax and Plasmodium falciparum there is an increased risk of P vivax parasitaemia following P falciparum malaria. Radical cure is currently only recommended for patients presenting with P vivax malaria. Expanding the indication for radical cure to patients presenting with P falciparum malaria could reduce their risk of subsequent P vivax parasitaemia. Methods We did a multicentre, open-label, superiority randomised controlled trial in five health clinics in Bangladesh, Indonesia, and Ethiopia. In Bangladesh and Indonesia, patients were excluded if they were younger than 1 year, whereas in Ethiopia patients were excluded if they were younger than 18 years. Patients with uncomplicated P falciparum monoinfection who had fever or a history of fever in the 48 h preceding clinic visit were eligible for enrolment and were required to have a glucose-6-dehydrogenase (G6PD) activity of 70% or greater. Patients received blood schizontocidal treatment (artemether–lumefantrine in Ethiopia and Bangladesh and dihydroartemisinin–piperaquine in Indonesia) and were randomly assigned (1:1) to receive either high-dose short-course oral primaquine (intervention arm; total dose 7 mg/kg over 7 days) or standard care (standard care arm; single dose oral primaquine of 0·25 mg/kg). Random assignment was done by an independent statistician in blocks of eight by use of sealed envelopes. All randomly assigned and eligible patients were included in the primary and safety analyses. The per-protocol analysis excluded those who did not complete treatment or had substantial protocol violations. The primary endpoint was the incidence risk of P vivax parasitaemia on day 63. This trial is registered at ClinicalTrials.gov, NCT03916003. Findings Between Aug 18, 2019, and March 14, 2022, a total of 500 patients were enrolled and randomly assigned, and 495 eligible patients were included in the intention-to-treat analysis (246 intervention and 249 control). The incidence risk of P vivax parasitaemia at day 63 was 11·0% (95% CI 7·5–15·9) in the standard care arm compared with 2·5% (1·0–5·9) in the intervention arm (hazard ratio 0·20, 95% CI 0·08–0·51; p=0·0009). The effect size differed with blood schizontocidal treatment and site. Routine symptom reporting on day 2 and day 7 were similar between groups. In the first 42 days, there were a total of four primaquine-related adverse events reported in the standard care arm and 26 in the intervention arm; 132 (92%) of all 143 adverse events were mild. There were two serious adverse events in the intervention arm, which were considered unrelated to the study drug. None of the patients developed severe anaemia (defined as haemoglobin <5 g/dL). Interpretation In patients with a G6PD activity of 70% or greater, high-dose short-course primaquine was safe and relatively well tolerated and reduced the risk of subsequent P vivax parasitaemia within 63 days by five fold. Universal radical cure therefore potentially offers substantial clinical, public health, and operational benefits, but these benefits will vary with endemic setting. Funding Australian Academy of Science Regional Collaborations Program, Bill & Melinda Gates Foundation, and National Health and Medical Research Council

Spectrophotometry assays to determine G6PD activity from Trinity Biotech and Pointe Scientific G6PD show good correlation

Objectives Spectrophotometry kits from Pointe Scientific (PS; USA) were compared to kits from Trinity Biotech (Trinity; Ireland) in 50 venous blood samples from purposively selected individuals in Bangladesh. Repeatability and inter-assay variability were assessed by Students t-test, Bland-Altman plot and Pearson correlation coefficient (r). The median glucose-6-phosphate dehydrogenase (G6PD) activity of all G6PD normal participants was calculated per assay and defined as 100% activity. Performance was calculated considering 30% and 70% cut off activities and Trinity as reference. Results The intra-assay correlation of Trinity (r = 0.9841, p &lt; 0.001) and PS (r = 0.9833, p &lt; 0.001) did not differ significantly (p = 0.904). Both assays were closely correlated (r = 0.9799, p &lt; 0.001), with a mean difference of 0.1 U/gHb (95% limit of agreement: − 1.32 to 1.57). At 30% cut off PS had a sensitivity of 100% (95% confidence interval (95 CI) 59.0–100.0) and specificity of 100% (95% CI 91.8 to 100.0), at 70% cut-off of 100% (95% CI 79.4–100.0) and 97.1% (95% CI 84.7–99.9) respectively. The G6PD assay from PS is a reliable alternative to the assay from Trinity