Spiral GRAPPA enabled 4-fold accelerated real-time MRI of speech with a low reconstruction latency. This approach is applicable to wide range of speech RT-MRI experiments that benefit from real-time feedback while visualizing rapid articulator movement. Magn Reson Med 78:2275-2282, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

The basic model of SCD physiology states that vaso‐occlusion occurs when hemoglobin S‐containing red blood cells (RBC) undergo sickling before they escape the capillary into a larger vessel. We have shown that mental stress, pain and cold, and events reported by patients to trigger SCD vaso‐occlusive crisis (VOC), cause rapid and significant decrease in blood flow, reducing the likelihood that RBC could transit the microvasculature before sickling occurs. However, the critical link between decrease in microvascular blood flow and the incidence of future sickle VOC has never been established experimentally in humans. Using data from centrally adjudicated, overnight polysomnograms (PSG), previously collected in a prospective multi‐center cohort sleep study, we analyzed the beat‐to‐beat amplitudes of vasoconstriction reported by the fingertip photoplethysmogram in 212 children and adolescents with SCD and developed an algorithm that detects vasoconstriction events and quantifies the magnitude (Mvasoc), duration, and frequency of vasoconstriction that reflect the individual's inherent peripheral vasoreactivity. The propensity to vasoconstrict, quantified by median Mvasoc, predicted the incidence rate of post‐PSG severe acute vaso‐occlusive pain events (P = .006) after accounting for age and hemoglobin. Indices of sleep‐disordered breathing contributed to median Mvasoc but did not predict future pain rate. Median Mvasoc was not associated with vaso‐occlusive pain events that occurred prior to each PSG. These results show that SCD individuals with high inherent propensity to vasoconstrict have more frequent severe acute pain events. Our empirical findings are consistent with the fundamental SCD hypothesis that decreased microvascular flow promotes microvascular occlusion.

Transient increases in peripheral vasoconstriction frequently occur in obstructive sleep apnea and periodic leg movement disorder, both of which are common in sickle cell disease (SCD). These events reduce microvascular blood flow and increase the likelihood of triggering painful vaso-occlusive crises (VOC) that are the hallmark of SCD. We recently reported a significant association between the magnitude of vasoconstriction, inferred from the finger photoplethysmogram (PPG) during sleep, and the frequency of future VOC in 212 children with SCD. In this study, we present an improved predictive model of VOC frequency by employing a two-level stacking machine learning (ML) model that incorporates detailed features extracted from the PPG signals in the same database. The first level contains seven different base ML algorithms predicting each subject's pain category based on the input PPG characteristics and other clinical information, while the second level is a meta model which uses the inputs to the first-level model along with the outputs of the base models to produce the final prediction. Model performance in predicting future VOC was significantly higher than in predicting VOC prior to each sleep study (F1-score of 0.43 vs. 0.35, p-value <0.0001), consistent with our hypothesis of a causal relationship between vasoconstriction and future pain incidence, rather than past pain leading to greater propensity for vasoconstriction. The model also performed much better than our previous conventional statistical model (F1 = 0.33), as well as all other algorithms that used only the base-models for predicting VOC without the second tier meta model. The modest F1 score of the present predictive model was due in part to the relatively small database with substantial imbalance (176:36) between low-pain and high-pain subjects, as well as other factors not captured by the sleep data alone. This report represents the first attempt ever to use non-invasive finger PPG measurements during sleep and a ML-based approach to predict increased propensity for VOC crises in SCD. The promising results suggest the future possibility of embedding an improved version of this model in a low-cost wearable system to assist clinicians in managing long-term therapy for SCD patients.

Sickle cell anemia (SCA) is genetic disease associated with chronic hemolysis and severe vaso-occlusive pain. Triggers for vaso-occlusive pain include both extreme temperatures (hot and cold), and stress. Our prior work demonstrates that anticipatory pain, experimental pain, experimental mental stress, and cold exposure cause significant global vasoconstriction in SCA and vasoconstriction responses differ among subjects.Anything that decreases microvascular flow will increase the likelihood that the red blood cells will not escape the microvasculature before deoxyhemoglobin S (HbS) polymerizes, leading to vaso-occlusion. However, this theoretical model has not been proven at a macro scale in patients. We showed that hypoxia induced in SCA subjects causes loss of parasympathetic modulation of heart rate but not decreased microvascular flow. Consistent with this, a prospective cohort study of SCA subjects showed no significant association between low mean nocturnal SpO2 and the incidence of VOC. However, surges in sympathetic activity accompany transient arousals and respiratory events during sleep, and lead to varying levels of peripheral vasoconstriction. In a prospective NIH funded cohort study of children with SCA, we tested the hypothesis that children with SCA and high levels when compared to low levels of intrinsic microvascular vasoreactivity (based on vasoconstriction events detected by polysomnography (PSG)) have a higher incidence rate of severe vaso-occlusive pain that requires hospitalization within 6 months of the PSG. We analyzed the time-series of R-R intervals (RRI) derived from the electrocardiogram and beat-to-beat amplitudes of finger photoplethysmography reflecting peripheral blood flow (PPGa) derived from the scored PSGs and clinical records of 212 children, who participated in the multi-center prospective SCA cohort study reported by Willen et al. (Am J Hematol 2018; 93:478-485). Vasoconstriction events were detected by applying an algorithm that found reductions in PPGa from local baseline that exceeded a threshold level of change. The changes in RRI from the pre-vasoconstriction baseline were also computed (Fig 1). The duration, average magnitude (Mvasoc) and area under the curve of PPGa were extracted from each significant vasoconstriction. The median values of these compact descriptors were taken to represent the nocturnal vasoconstriction characteristics of each participant. A participant was classified to be in the high- or low-pain event category if they were hospitalized for severe pain at least two times or less than 2 times within a 1-year window from 6 months before to 6 months after the PSG, respectively. Multiple logistic regression analysis was applied, using pain category as the outcome variable, and vasoconstriction descriptors, arousal index, obstructive apnea-hypopnea index, age, sex and hemoglobin level as predictor variables. Pain category was strongly associated with magnitude of vasoconstriction (Mvasoc; p=0.0058), with larger Mvasoc predicting high-pain, after accounting for age, sex and hemoglobin level (Hgb). Figure 2 displays the adjusted Mvasoc (mean ± SE) in the high-pain and low/no-pain groups. Mvasoc was strongly correlated with arousal index (p=0.0073). However, none of the traditional measures of sleep-disordered breathing, including arousal index, were associated with pain category. Age was the only other predictor of severe pain. These findings, showing that propensity for a high degree of microvascular vasoconstriction is associated with the temporal relationship of severe pain requiring hospitalization, validate on a macro scale the model that increased microvascular transit time promotes entrapment of sickled red blood cells, elevating the risk of severe vaso-occlusive pain. Our data reveals for the first time, a mechanistic link between the patient's symptoms and the triggering of transition from steady state to acute severe pain. The fact that individuals have intrinsic vasoreactivity phenotypes, that can be identified by analysis of the photoplethysmogram, provides yet another factor in acute vaso-occlusive pain. Autonomic balance and vasoreactivity likely contribute to known variability of the incidence rate of severe pain and represent another plausible target for therapeutic intervention. Disclosures Coates: apo pharma: Consultancy, Honoraria, Speakers Bureau; vifor: Consultancy, Honoraria; agios pharma: Consultancy, Honoraria; celgene: Consultancy, Honoraria, Other: steering committee of clinical study.