Comput Inform Nurs. 2024 Jun 1;42(6):405-409. doi: 10.1097/CIN.0000000000001135.
NO ABSTRACT
PMID:38830135 | DOI:10.1097/CIN.0000000000001135
Tag: pubmed
Med Phys. 2024 Jun 3. doi: 10.1002/mp.17238. Online ahead of print.
ABSTRACT
BACKGROUND: Direction Modulated Brachytherapy (DMBT) enables conformal dose distributions. However, clinicians may face challenges in creating viable treatment plans within a fast-paced clinical setting, especially for a novel technology like DMBT, where cumulative clinical experience is limited. Deep learning-based dose prediction methods have emerged as effective tools for enhancing efficiency.
PURPOSE: To develop a voxel-wise dose prediction model using an attention-gating mechanism and a 3D UNET for cervical cancer high-dose-rate (HDR) brachytherapy treatment planning with DMBT six-groove tandems with ovoids or ring applicators.
METHODS: A multi-institutional cohort of 122 retrospective clinical HDR brachytherapy plans treated to a prescription dose in the range of 4.8-7.0 Gy/fraction was used. A DMBT tandem model was constructed and incorporated onto a research version of BrachyVision Treatment Planning System (BV-TPS) as a 3D solid model applicator and retrospectively re-planned all cases by seasoned experts. Those plans were randomly divided into 64:16:20 as training, validating, and testing cohorts, respectively. Data augmentation was applied to the training and validation sets to increase the size by a factor of 4. An attention-gated 3D UNET architecture model was developed to predict full 3D dose distributions based on high-risk clinical target volume (CTVHR) and organs at risk (OARs) contour information. The model was trained using the mean absolute error loss function, Adam optimization algorithm, a learning rate of 0.001, 250 epochs, and a batch size of eight. In addition, a baseline UNET model was trained similarly for comparison. The model performance was evaluated on the testing dataset by analyzing the outcomes in terms of mean dose values and derived dose-volume-histogram indices from 3D dose distributions and comparing the generated dose distributions against the ground-truth dose distributions using dose statistics and clinically meaningful dosimetric indices.
RESULTS: The proposed attention-gated 3D UNET model showed competitive accuracy in predicting 3D dose distributions that closely resemble the ground-truth dose distributions. The average values of the mean absolute errors were 1.82 ± 29.09 Gy (vs. 6.41 ± 20.16 Gy for a baseline UNET) in CTVHR, 0.89 ± 1.25 Gy (vs. 0.94 ± 3.96 Gy for a baseline UNET) in the bladder, 0.33 ± 0.67 Gy (vs. 0.53 ± 1.66 Gy for a baseline UNET) in the rectum, and 0.55 ± 1.57 Gy (vs. 0.76 ± 2.89 Gy for a baseline UNET) in the sigmoid. The results showed that the mean absolute error (MAE) for the bladder, rectum, and sigmoid were 0.22 ± 1.22 Gy (3.62%) (p = 0.015), 0.21 ± 1.06 Gy (2.20%) (p = 0.172), and -0.03 ± 0.54 Gy (1.13%) (p = 0.774), respectively. The MAE for D90, V100%, and V150% of the CTVHR were 0.46 ± 2.44 Gy (8.14%) (p = 0.018), 0.57 ± 11.25% (5.23%) (p = 0.283), and -0.43 ± 19.36% (4.62%) (p = 0.190), respectively. The proposed model needs less than 5 s to predict a full 3D dose distribution of 64 × 64 × 64 voxels for any new patient plan, thus making it sufficient for near real-time applications and aiding with decision-making in the clinic.
CONCLUSIONS: Attention gated 3D-UNET model demonstrated a capability in predicting voxel-wise dose prediction, in comparison to 3D UNET, for DMBT intracavitary brachytherapy planning. The proposed model could be used to obtain dose distributions for near real-time decision-making before DMBT planning and quality assurance. This will guide future automated planning, making the workflow more efficient and clinically viable.
PMID:38830129 | DOI:10.1002/mp.17238
Proc Natl Acad Sci U S A. 2024 Jun 11;121(24):e2317707121. doi: 10.1073/pnas.2317707121. Epub 2024 Jun 3.
ABSTRACT
Human pose, defined as the spatial relationships between body parts, carries instrumental information supporting the understanding of motion and action of a person. A substantial body of previous work has identified cortical areas responsive to images of bodies and different body parts. However, the neural basis underlying the visual perception of body part relationships has received less attention. To broaden our understanding of body perception, we analyzed high-resolution fMRI responses to a wide range of poses from over 4,000 complex natural scenes. Using ground-truth annotations and an application of three-dimensional (3D) pose reconstruction algorithms, we compared similarity patterns of cortical activity with similarity patterns built from human pose models with different levels of depth availability and viewpoint dependency. Targeting the challenge of explaining variance in complex natural image responses with interpretable models, we achieved statistically significant correlations between pose models and cortical activity patterns (though performance levels are substantially lower than the noise ceiling). We found that the 3D view-independent pose model, compared with two-dimensional models, better captures the activation from distinct cortical areas, including the right posterior superior temporal sulcus (pSTS). These areas, together with other pose-selective regions in the LOTC, form a broader, distributed cortical network with greater view-tolerance in more anterior patches. We interpret these findings in light of the computational complexity of natural body images, the wide range of visual tasks supported by pose structures, and possible shared principles for view-invariant processing between articulated objects and ordinary, rigid objects.
PMID:38830105 | DOI:10.1073/pnas.2317707121
Proc Natl Acad Sci U S A. 2024 Jun 11;121(24):e2315700121. doi: 10.1073/pnas.2315700121. Epub 2024 Jun 3.
ABSTRACT
Given the importance of climate in shaping species’ geographic distributions, climate change poses an existential threat to biodiversity. Climate envelope modeling, the predominant approach used to quantify this threat, presumes that individuals in populations respond to climate variability and change according to species-level responses inferred from spatial occurrence data-such that individuals at the cool edge of a species’ distribution should benefit from warming (the “leading edge”), whereas individuals at the warm edge should suffer (the “trailing edge”). Using 1,558 tree-ring time series of an aridland pine (Pinus edulis) collected at 977 locations across the species’ distribution, we found that trees everywhere grow less in warmer-than-average and drier-than-average years. Ubiquitous negative temperature sensitivity indicates that individuals across the entire distribution should suffer with warming-the entire distribution is a trailing edge. Species-level responses to spatial climate variation are opposite in sign to individual-scale responses to time-varying climate for approximately half the species’ distribution with respect to temperature and the majority of the species’ distribution with respect to precipitation. These findings, added to evidence from the literature for scale-dependent climate responses in hundreds of species, suggest that correlative, equilibrium-based range forecasts may fail to accurately represent how individuals in populations will be impacted by changing climate. A scale-dependent view of the impact of climate change on biodiversity highlights the transient risk of extinction hidden inside climate envelope forecasts and the importance of evolution in rescuing species from extinction whenever local climate variability and change exceeds individual-scale climate tolerances.
PMID:38830099 | DOI:10.1073/pnas.2315700121
Proc Natl Acad Sci U S A. 2024 Jun 11;121(24):e2402375121. doi: 10.1073/pnas.2402375121. Epub 2024 Jun 3.
ABSTRACT
Recent work has emphasized the disproportionate bias faced by minorities when interacting with law enforcement. However, research on the topic has been hampered by biased sampling in administrative data, namely that records of police interactions with citizens only reflect information on the civilians that police elect to investigate, and not civilians that police observe but do not investigate. In this work, we address a related bias in administrative police data which has received less empirical attention, namely reporting biases around investigations that have taken place. Further, we investigate whether digital monitoring tools help mitigate this reporting bias. To do so, we examine changes in reports of interactions between law enforcement and citizens in the wake of the New York City Police Department’s replacement of analog memo books with mobile smartphones. Results from a staggered difference in differences estimation indicate a significant increase in reports of citizen stops once the new smartphones are deployed. Importantly, we observe that the rise is driven by increased reports of “unproductive” stops, stops involving non-White citizens, and stops occurring in areas characterized by a greater concentration of crime and non-White residents. These results reinforce the recent observation that prior work has likely underestimated the extent of racial bias in policing. Further, they highlight that the implementation of digital monitoring tools can mitigate the issue to some extent.
PMID:38830090 | DOI:10.1073/pnas.2402375121
Continuum (Minneap Minn). 2024 Jun 1;30(3):878-903. doi: 10.1212/CON.0000000000001433.
ABSTRACT
OBJECTIVE: This article synthesizes the current literature on prognostication in neurocritical care, identifies existing challenges, and proposes future research directions to reduce variability and enhance scientific and patient-centered approaches to neuroprognostication.
LATEST DEVELOPMENTS: Patients with severe acute brain injury often lack the capacity to make their own medical decisions, leaving surrogate decision makers responsible for life-or-death choices. These decisions heavily rely on clinicians’ prognostication, which is still considered an art because of the previous lack of specific guidelines. Consequently, there is significant variability in neuroprognostication practices. This article examines various aspects of neuroprognostication. It explores the cognitive approach to prognostication, highlights the use of statistical modeling such as Bayesian models and machine learning, emphasizes the importance of clinician-family communication during prognostic disclosures, and proposes shared decision making for more patient-centered care.
ESSENTIAL POINTS: This article identifies ongoing challenges in the field and emphasizes the need for future research to ameliorate variability in neuroprognostication. By focusing on scientific methodologies and patient-centered approaches, this research aims to provide guidance and tools that may enhance neuroprognostication in neurocritical care.
PMID:38830074 | DOI:10.1212/CON.0000000000001433
J Craniofac Surg. 2024 Jun 3. doi: 10.1097/SCS.0000000000010385. Online ahead of print.
ABSTRACT
The purpose of this study was to compare speech outcomes in patients with submucous cleft palate (SMCP) between speech therapy alone and double-opposing Z-plasty (DOZ) combined with speech therapy. The subjects were 67 patients with SMCP (overt type, 45 males, 22 females), who were divided into the observation group (n=18), the speech therapy group (n=24; duration, 17.8 mo), and the DOZ and speech therapy (DOZ-speech therapy) group (n=25; median age at DOZ, 5.3 years, duration, 18.6 mo). The median age at initial and final speech assessments were 3 and 5 years. After age, sex, syndromic status, duration of speech therapy, surgery timing, and speech outcomes were investigated, statistical analysis was performed. After tailored interventions, both isolated and non-isolated SMCP patients experienced significant improvements in speech outcomes, including nasal emission, hypernasality, compensatory articulation, and unintelligible speech. Since comparable improvements were observed, there were no significant differences in the final assessments regardless of initial speech issues between the speech therapy group and the DOZ-speech therapy group (all P>0.05). In the DOZ-speech therapy group, the rate of achieving “socially acceptable” speech was 92.3% in isolated cases and 90% in non-isolated cases. Multivariate analysis revealed that DOZ showed a tendency to reduce hypernasality, compensatory articulation, and “unintelligible” speech; syndromic or developmental conditions influenced outcomes in nasal emission and hypernasality; and initial hypernasality and compensatory articulation were correlated with outcomes. Therefore, DOZ surgery could be recommended to resolve hypernasality and compensatory articulation in SMCP patients before speech issues worsen.
PMID:38830053 | DOI:10.1097/SCS.0000000000010385
Ann Med. 2024 Dec;56(1):2362880. doi: 10.1080/07853890.2024.2362880. Epub 2024 Jun 3.
ABSTRACT
BACKGROUND: Nocturnal blood pressure (BP) is correlated with an increased risk of cardiovascular events and is an important predictor of cardiovascular death in hypertensive patients.
OBJECTIVE: Nocturnal BP control is of great importance for cardiovascular risk reduction. This systematic review and meta-analysis aimed to explore the efficacy of angiotensin receptor blockers (ARBs) for nocturnal BP reduction in patients with mild to moderate hypertension.
METHODS: PICOS design structure was used to formulate the data extraction. All statistical calculations and analyses were performed with R.
RESULTS: Seventy-seven studies with 13,314 participants were included. The overall analysis indicated that nocturnal BP drop varied considerably among different ARBs. Allisartan (13.04 [95% CI (-18.41, -7.68)] mmHg), olmesartan (11.67 [95% CI (-14.12, -9.21)] mmHg), telmisartan (11.11 [95% CI (-12.12, -10.11)] mmHg) were associated with greater reduction in nocturnal systolic BP. In the aspect of the nocturnal-diurnal BP drop ratio, only allisartan was greater than 1. While, the variation tendency of last 4-6 h ambulatory BP was basically consistent with nocturnal BP. Additionally, allisartan showed improvement effect in the proportion of patients with dipping BP pattern.
CONCLUSIONS: This study demonstrates that for patients with mild to moderate hypertension, allisartan, olmesartan and telmisartan have more advantages in nocturnal BP reduction among the ARBs, while allisartan can reduce nighttime BP more than daytime BP and improve the dipping pattern.
PMID:38830046 | DOI:10.1080/07853890.2024.2362880
JNCI Cancer Spectr. 2024 Jun 3:pkae043. doi: 10.1093/jncics/pkae043. Online ahead of print.
ABSTRACT
BACKGROUND: Socioeconomic inequalities in the uptake of colorectal cancer screening are well documented, but the implications on health inequity remain unclear.
METHODS: Sixty-year-olds were randomly recruited from the Swedish population between March, 2014, and March, 2020, and invited to either fecal immunochemical testing (FIT) 2 years apart (n = 60,137) or once-only primary colonoscopy (PCOL; n = 30,400). By linkage to Statistics Sweden’s registries, we obtained socioeconomic data. In each defined socioeconomic group, we estimated the cumulative yield of advanced neoplasia (AN) in each screening arm (intention-to-screen analysis). We predicted the probability of exceeding the yield in the PCOL arm after a third round of FIT: Pr{AN_FIT3>AN_PCOL}.
RESULTS: In the lowest income group, the yield of AN was 1.63% (95% confidence interval [CI] = 1.35% to 1.93%) after two rounds of FIT, in relation to 1.93% (95% CI = 1.49% to 2.40%) in the PCOL arm. We predicted Pr{AN_FIT3>AN_PCOL} = 0.86. In the highest income group, we found a more pronounced yield gap between the two screening strategies, 2.32% (95% CI = 2.15% to 2.49%) vs 3.71% (95% CI = 3.41% to 4.02%), and a very low Pr{AN_FIT3>AN_PCOL} (= 0.02).
CONCLUSIONS: Yields of AN from FIT 2 years apart and PCOL, respectively, were poorer, but differed lesser, in lower socioeconomic groups. The results are valuable for evaluations of health equity in organized screening for colorectal cancer.
CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov number NCT02078804.
PMID:38830030 | DOI:10.1093/jncics/pkae043
J Pediatr Endocrinol Metab. 2024 Jun 4. doi: 10.1515/jpem-2024-0144. Online ahead of print.
ABSTRACT
OBJECTIVES: This study is aimed to explore the correlation between bisphenol A (BPA) and phthalates, including diethylhexylphthalate (DEHP) and dibutylphthalate (DBP), and precocious puberty (PP).
METHODS: A case-control study was conducted in Ho Chi Minh City, Vietnam, from November 2021 to April 2022, involving 250 children, with 124 of them diagnosed with PP and 126 serving as controls. We assessed the levels of urinary BPA, DEHP, and DBP in all participants and examined their association with the risk of PP.
RESULTS: BPA was detected in 11.3 % of PP cases but was not found in any individuals in the control group (p<0.001). Diethylhexylphthalate metabolite (MEHP) was not detected in any of the samples. Positive urinary results for dibutylphthalate metabolite (MBP) were observed in 8.1 % of PP cases and 2.4 % in the control group, with an odds ratio of 3.6 (95 % confidence interval: 0.97-13.4, p=0.03).
CONCLUSIONS: The PP group exhibited a higher prevalence of positive urinary BPA and DBP levels compared to the control group.
PMID:38829694 | DOI:10.1515/jpem-2024-0144