Global Health Partnerships During the COVID-19 Pandemic: Perspectives and Insights from International Partners

Global health partnerships (GHPs) have encountered many challenges during the coronavirus disease 2019 (COVID-19) pandemic. New perspectives and insights are needed to guide GHPs when navigating current and future collaborations. This study aimed to understand perspectives and insights of international partners regarding how the COVID-19 pandemic impacted their GHPs with institutions in the United States. We performed a cross-sectional qualitative study conducted through virtual semi-structured interviews performed between June 12, 2020 and July 22, 2020. We queried academic institutions based in the United States to refer individuals from their corresponding international GHP organizations. We invited these individuals to participate in virtual interviews that were audio-recorded and transcribed. We analyzed data qualitatively to identify themes. Eighty-four United States partners provided e-mail addresses for international partners. Ten individuals from these GHPs completed the interview. Participants reported overall positive experiences with their United States-based partners during the pandemic. The following themes emerged: imbalanced decision-making; worry about partnership continuity; opportunity to optimize communication within partnerships; interest in incorporating technology to facilitate engagement; and a desire for increased bilateral exchanges. Several challenges appeared to exist before COVID-19 and were highlighted by the pandemic. Most respondents were optimistic regarding the future of their GHPs. However, concerns were expressed regarding the implications of fewer in-person international experiences with United States trainees and the desire for stronger communication. Although our results do not represent the perspectives and insights of all GHPs, they provide considerations for the future. We urge institutions in the United States to re-examine and strive for equitable relationships with their international partners

Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL.

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype

When Helping Babies Breathe Is Not Enough: Designing a Novel, Mid-Level Neonatal Resuscitation Algorithm for M\ue9decins Sans Fronti\ue8res Field Teams Working in Low-Resource Hospital Settings

Neonatal resuscitation (NR) combines a set of life-saving interventions in order to stabilize compromised newborns at birth or when critically ill. Médecins Sans Frontières/Doctors Without Borders (MSF), as an international medical-humanitarian organization working particularly in low-resource settings (LRS), assisted over 250,000 births in obstetric and newborn care aid projects in 2016 and provides thousands of newborn resuscitations annually. The Helping Babies Breathe (HBB) program has been used as formal guidance for basic resuscitation since 2012. However, in some MSF projects with the capacity to provide more advanced NR interventions but a lack of adapted guidance, staff have felt prompted to create their own advanced algorithms, which runs counter to the organization's aim for standardized protocols in all aspects of its care

Testâ retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149339/1/jmri26539.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149339/2/jmri26539_am.pd

Test–retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial

BackgroundQuantitative diffusion-weighted imaging (DWI) MRI is a promising technique for cancer characterization and treatment monitoring. Knowledge of the reproducibility of DWI metrics in breast tumors is necessary to apply DWI as a clinical biomarker.PurposeTo evaluate the repeatability and reproducibility of breast tumor apparent diffusion coefficient (ADC) in a multi-institution clinical trial setting, using standardized DWI protocols and quality assurance (QA) procedures.Study typeProspective.SubjectsIn all, 89 women from nine institutions undergoing neoadjuvant chemotherapy for invasive breast cancer.Field strength/sequenceDWI was acquired before and after patient repositioning using a four b-value, single-shot echo-planar sequence at 1.5T or 3.0T.AssessmentA QA procedure by trained operators assessed artifacts, fat suppression, and signal-to-noise ratio, and determine study analyzability. Mean tumor ADC was measured via manual segmentation of the multislice tumor region referencing DWI and contrast-enhanced images. Twenty cases were evaluated multiple times to assess intra- and interoperator variability. Segmentation similarity was assessed via the Sørenson-Dice similarity coefficient.Statistical testsRepeatability and reproducibility were evaluated using within-subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), agreement index (AI), and repeatability coefficient (RC). Correlations were measured by Pearson's correlation coefficients.ResultsIn all, 71 cases (80%) passed QA evaluation: 44 at 1.5T, 27 at 3.0T; 60 pretreatment, 11 after 3 weeks of taxane-based treatment. ADC repeatability was excellent: wCV = 4.8% (95% confidence interval [CI] 4.0, 5.7%), ICC = 0.97 (95% CI 0.95, 0.98), AI = 0.83 (95% CI 0.76, 0.87), and RC = 0.16 * 10-3 mm2 /sec (95% CI 0.13, 0.19). The results were similar across field strengths and timepoint subgroups. Reproducibility was excellent: interreader ICC = 0.92 (95% CI 0.80, 0.97) and intrareader ICC = 0.91 (95% CI 0.78, 0.96).Data conclusionBreast tumor ADC can be measured with excellent repeatability and reproducibility in a multi-institution setting using a standardized protocol and QA procedure. Improvements to DWI image quality could reduce loss of data in clinical trials.Level of evidence2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1617-1628