Background

Current guidelines suggest a "door-in-door-out" (DIDO) time of 30 minutes or shorter for patients with ST-segment elevation myocardial infarction (STEMI) who arrive at a STEMI referral hospital and are transferred to a STEMI-receiving center for primary percutaneous coronary intervention. Experts previously identified 18 system practices as critical for reducing DIDO times. The objective of this study was to describe how frequently these critical practices are used and to determine whether their use was associated with shorter DIDO times.

Methods

We surveyed 18 STEMI referral hospitals for 4 STEMI-receiving centers regarding their use of these 18 practices. The median number used was 14 practices (interquartile range 12-15). We then evaluated their association with DIDO times in all patients (n = 93) transferred from these STEMI referral hospitals to the 4 STEMI-receiving centers for primary percutaneous coronary intervention.

Results

In univariate linear regression analyses, system-wide quality improvement programs with leaders in the emergency medical services agencies and STEMI referral hospitals were associated with shorter DIDO times (P < 0.001 for all). Overall use of system practices was not associated with DIDO times (P = 0.143). The majority (76%, 95% confidence interval: 66%-85%) of DIDO times did not meet the 30-minute goal.

Conclusions

These findings highlight the difficulty in achieving the 30-minute DIDO goal and the need for continued focus on strategies for reducing DIDO time, including system-wide quality improvement programs.

Purpose

Year-to-year decreases in smoking in the US have been observed only sporadically in recent years, which suggest a need for intensified efforts to identify those at risk for persistent smoking. To address this need, we examined the association between a variety of psychosocial stressors and smoking persistence, cessation, and relapse over 9-10 years among adults in the United States (n = 4,938, ages 25-74).

Methods

Using information provided at baseline and follow-up, participants were categorized as non-smokers, persistent smokers, ex-smokers, and relapsed smokers. Stressors related to relationships, finances, work-family conflict, perceived inequality, neighborhood, discrimination, and past-year family problems were assessed at baseline and follow-up.

Results

High stress at both assessments was associated with greater odds of persistent smoking for stressors related to relationships, finances, work, perceived inequality, past-year family problems, and a summary score. Among respondents who were smokers at baseline, high stress at both time points for relationship stress, perceived inequality, and past-year family problems was associated with nearly double the odds of failure to quit.

Conclusions

Interventions to address psychosocial stress may be important components within smoking cessation efforts.

Background

Current guidelines recommend ≤90 minutes from first medical contact to percutaneous coronary intervention (FMC2B) for ST-segment-elevation myocardial infarction (STEMI) patients. We evaluated the relationship between patient home distance from a percutaneous coronary intervention (PCI) center, prehospital electrocardiogram (ECG) use, and FMC2B time among patients with STEMI.

Methods

We performed a retrospective cohort study including all STEMI patients in the ACTION-Get With The Guidelines registry from July 1, 2008, to September 30, 2012, who were transported by ambulance to a PCI center. Patient home distance was defined as the driving distance from the patient's home zip code to the PCI center address. Distance was classified into tertiles, and linear regression was used to characterize the interaction between prehospital ECG use and patient home distance with respect to FMC2B time.

Results

Of the 29,506 STEMI patients, 19,690 (67%) received a prehospital ECG. The median patient home distance to the PCI center was 11.0 miles among patients with and 9.9 miles among those without a prehospital ECG. Prehospital ECGs were associated with a 10-minute reduction in the FMC2B time (P < .0001), which was consistent across distance tertiles (11 vs 11 vs 10 minutes). The association between prehospital ECGs and shorter FMC2B was attenuated by 0.8 minute for every 10-mile increase in distance (interaction P = .0002).

Conclusions

Prehospital ECGs are associated with a 10-minute reduction in the FMC2B time. However, patient home distance from a PCI center does not substantially change this association.

We analyzed DCE-MR images from 132 women with locally advanced breast cancer from the I-SPY1 trial to evaluate changes of intra-tumor heterogeneity for augmenting early prediction of pathologic complete response (pCR) and recurrence-free survival (RFS) after neoadjuvant chemotherapy (NAC). Utilizing image registration, voxel-wise changes including tumor deformations and changes in DCE-MRI kinetic features were computed to characterize heterogeneous changes within the tumor. Using five-fold cross-validation, logistic regression and Cox regression were performed to model pCR and RFS, respectively. The extracted imaging features were evaluated in augmenting established predictors, including functional tumor volume (FTV) and histopathologic and demographic factors, using the area under the curve (AUC) and the C-statistic as performance measures. The extracted voxel-wise features were also compared to analogous conventional aggregated features to evaluate the potential advantage of voxel-wise analysis. Voxel-wise features improved prediction of pCR (AUC = 0.78 (±0.03) vs 0.71 (±0.04), p < 0.05 and RFS (C-statistic = 0.76 ( ± 0.05), vs 0.63 ( ± 0.01)), p < 0.05, while models based on analogous aggregate imaging features did not show appreciable performance changes (p > 0.05). Furthermore, all selected voxel-wise features demonstrated significant association with outcome (p < 0.05). Thus, precise measures of voxel-wise changes in tumor heterogeneity extracted from registered DCE-MRI scans can improve early prediction of neoadjuvant treatment outcomes in locally advanced breast cancer.

Purpose

Image registration plays a vital role in spatially aligning multiple MRI scans for better longitudinal assessment of tumor morphological features. The objective was to evaluate the effect of registration accuracy of six established deformable registration methods(ANTs, DRAMMS, ART, NiftyReg, SSD-FFD, and NMI-FFD) on the predictive value of extracted radiomic features when modeling recurrence-free-survival(RFS) for women after neoadjuvant chemotherapy(NAC) for locally advanced breast cancer.

Methods

130 women had DCE-MRI scans available from the first two visits in the ISPY1/ACRIN-6657 cohort. We calculated the transformation field from each of the different deformable registration methods, and used it to compute voxel-wise parametric-response-maps(PRM) for established four kinetic features.104-radiomic features were computed from each PRM map to characterize intra-tumor heterogeneity. We evaluated performance for RFS using Cox-regression, C-statistic, and Kaplan-Meier(KM) plots.

Results

A baseline model(F1:Age, Race, and Hormone-receptor-status) had a 0.54 C-statistic, and model F2(baseline + functional-tumor-volume at early treatment visit(FTV₂)) had 0.63. The F2+ANTs had the highest C-statistic(0.72) with the smallest landmark differences(5.40±4.40mm) as compared to other models. The KM curve for model F2 gave p=0.004 for separation between women above and below the median hazard compared to the model F1(p=0.31). A models augmented with radiomic features, also achieved significant KM curve separation(p<0.001) except the F2+ART model.

Conclusion

Incorporating image registration in quantifying changes in tumor heterogeneity during NAC can improve prediction of RFS. Radiomic features of PRM maps derived from warping the DCE-MRI kinetic maps using ANTs registration method further improved the early prediction of RFS as compared to other methods.

CONTEXT: The King-Devick (K-D) test is used to identify oculomotor impairment after concussion. However, the diagnostic accuracy of the K-D test over time has not been evaluated. OBJECTIVES: To (1) examine the sensitivity and specificity of the K-D test at 0 to 6 hours postinjury, 24 to 48 hours postinjury, the beginning of a return-to-play (RTP) protocol (asymptomatic), unrestricted RTP, and 6 months postconcussion and (2) compare outcomes between athletes with and those without concussion across confounding factors (sex, age, sport contact level, academic year, learning disorder, attention-deficit/hyperactivity disorder, migraine history, concussion history, and test administration mode). DESIGN: Retrospective, cross-sectional design. SETTING: Multiple institutions in the Concussion Assessment, Research and Education Consortium. PATIENTS OR OTHER PARTICIPANTS: A total of 320 athletes with a concussion (162 men, 158 women; age = 19.80 ± 1.41 years) were compared with 1239 total collegiate athletes without a concussion (646 men, 593 women; age = 20.31 ± 1.18 years). MAIN OUTCOME MEASURE(S): We calculated the K-D test time difference (in seconds) by subtracting the baseline from the most recent time. Receiver operator characteristic (ROC) curve and area under the curve (AUC) analyses were used to determine the diagnostic accuracy across time points. We identified cutoff scores and corresponding specificity at both the 80% and 70% sensitivity levels. We repeated ROC with AUC analyses using confounding factors. RESULTS: The K-D test predicted positive results at the 0- to 6-hour (AUC = 0.724, P < .001), 24- to 48-hour (AUC = 0.701, P < .001), RTP (AUC = 0.640, P < .001), and 6-month postconcussion (AUC = 0.615, P < .001) tim points but not at the asymptomatic time point (AUC = 0.513, P = .497). The 0- to 6-hour and 24- to 48-hour time points yielded 80% sensitivity cutoff scores of -2.6 and -3.2 seconds (ie, faster), respectively, but 46% and 41% specificity, respectively. The K-D test had a better AUC when administered using an iPad (AUC = 0.800, 95% CI = 0.747, 0.854) compared with the spiral-bound card system (AUC = 0.646, 95% CI = 0.600, 0.692; P < .001). CONCLUSIONS: The diagnostic accuracy of the K-D test was greatest at 0 to 6 hours and 24 to 48 hours postconcussion but declined across subsequent postconcussion time points. The AUCs did not differentiate between groups across confounding factors. Our negative cutoff scores indicated that practice effects contributed to improved performance, requiring athletes to outperform their baseline scores.

Breast cancer is one of the most pervasive forms of cancer and its inherent intra- and inter-tumor heterogeneity contributes towards its poor prognosis. Multiple studies have reported results from either private institutional data or publicly available datasets. However, current public datasets are limited in terms of having consistency in: a) data quality, b) quality of expert annotation of pathology, and c) availability of baseline results from computational algorithms. To address these limitations, here we propose the enhancement of the I-SPY1 data collection, with uniformly curated data, tumor annotations, and quantitative imaging features. Specifically, the proposed dataset includes a) uniformly processed scans that are harmonized to match intensity and spatial characteristics, facilitating immediate use in computational studies, b) computationally-generated and manually-revised expert annotations of tumor regions, as well as c) a comprehensive set of quantitative imaging (also known as radiomic) features corresponding to the tumor regions. This collection describes our contribution towards repeatable, reproducible, and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments.

Background

Early changes in breast intratumor heterogeneity during neoadjuvant chemotherapy may reflect the tumor's ability to adapt and evade treatment. We investigated the combination of precision medicine predictors of genomic and MRI data towards improved prediction of recurrence free survival (RFS).

Methods

A total of 100 women from the ACRIN 6657/I-SPY 1 trial were retrospectively analyzed. We estimated MammaPrint, PAM50 ROR-S, and p53 mutation scores from publicly available gene expression data and generated four, voxel-wise 3-D radiomic kinetic maps from DCE-MR images at both pre- and early-treatment time points. Within the primary lesion from each kinetic map, features of change in radiomic heterogeneity were summarized into 6 principal components.

Results

We identify two imaging phenotypes of change in intratumor heterogeneity (p < 0.01) demonstrating significant Kaplan-Meier curve separation (p < 0.001). Adding phenotypes to established prognostic factors, functional tumor volume (FTV), MammaPrint, PAM50, and p53 scores in a Cox regression model improves the concordance statistic for predicting RFS from 0.73 to 0.79 (p = 0.002).

Conclusions

These results demonstrate an important step in combining personalized molecular signatures and longitudinal imaging data towards improved prognosis.