Nevin Manimala

Pediatr Radiol. 2022 Sep 19. doi: 10.1007/s00247-022-05499-0. Online ahead of print.

ABSTRACT

BACKGROUND: Leg length discrepancy (LLD) is a common problem that can cause long-term musculoskeletal problems. However, measuring LLD on radiography is time-consuming and labor intensive, despite being a simple task.

OBJECTIVE: To develop and evaluate a deep-learning algorithm for measurement of LLD on radiographs.

MATERIALS AND METHODS: In this Health Insurance Portability and Accountability Act (HIPAA)-compliant retrospective study, radiographs were obtained to develop a deep-learning algorithm. The algorithm developed with two U-Net models measures LLD using the difference between the bilateral iliac crest heights. For performance evaluation of the algorithm, 300 different radiographs were collected and LLD was measured by two radiologists, the algorithm alone and the model-assisting method. Statistical analysis was performed to compare the measurement differences with the measurement results of an experienced radiologist considered as the ground truth. The time spent on each measurement was then compared.

RESULTS: Of the 300 cases, the deep-learning model successfully delineated both iliac crests in 284. All human measurements, the deep-learning model and the model-assisting method, showed a significant correlation with ground truth measurements, while Pearson correlation coefficients and interclass correlations (ICCs) decreased in the order listed. (Pearson correlation coefficients ranged from 0.880 to 0.996 and ICCs ranged from 0.914 to 0.997.) The mean absolute errors of the human measurement, deep-learning-assisting model and deep-learning-alone model were 0.7 ± 0.6 mm, 1.1 ± 1.1 mm and 2.3 ± 5.2 mm, respectively. The reading time was 7 h and 12 min on average for human reading, while the deep-learning measurement took 7 min and 26 s. The radiologist took 74 min to complete measurements in the deep-learning mode.

CONCLUSION: A deep-learning U-Net model measuring the iliac crest height difference was possible on teleroentgenograms in children. LLD measurements assisted by the deep-learning algorithm saved time and labor while producing comparable results with human measurements.

PMID:36121497 | DOI:10.1007/s00247-022-05499-0

J Adolesc. 2022 Sep 19. doi: 10.1002/jad.12091. Online ahead of print.

ABSTRACT

INTRODUCTION: This study examined the moderating role of adaptive and maladaptive emotion regulation in the relationship between general perceived stress and depressive symptoms during the first coronavirus disease 2019 (COVID-19) lockdown in March-April 2020 in Belgium, while controlling for past depressive symptoms in 2016.

METHODS: Participants were 110 adolescents (55% female; Mage = 16, SDage = 1.80) who filled out different questionnaires assessing maladaptive and adaptive emotion regulation strategies (ERS), perceived stress, and depressive symptoms.

RESULTS: Results revealed that only maladaptive ERS statistically significantly moderated the relationship between perceived stress and depressive symptoms. More specifically, the amount of perceived stress is positively associated with the level of depressive symptoms, especially in adolescents who use more maladaptive ERS.

CONCLUSION: The repertoire of adaptive ERS might not be sufficient for adolescents to flexibly cope with a highly stressful situation such as the COVID-19 pandemic and lockdown. Study findings highlight the need to support youth, particularly those who use more maladaptive ERS, in adaptively coping with intense stressful life events.

PMID:36120954 | DOI:10.1002/jad.12091

Stat Methods Med Res. 2022 Sep 18:9622802221122383. doi: 10.1177/09622802221122383. Online ahead of print.

ABSTRACT

In sequential testing with binary data, sample size and time to detect a signal are the key performance measures to optimize. While the former should be optimized in Phase III clinical trials, minimizing the latter is of major importance in post-market drug and vaccine safety surveillance of adverse events. The precision of the relative risk estimator on termination of the analysis is a meaningful design criterion as well. This paper presents a linear programming framework to find the optimal alpha spending that minimizes expected time to signal, or expected sample size as needed. The solution enables (a) to bound the width of the confidence interval following the end of the analysis, (b) designs with outer signaling thresholds and inner non-signaling thresholds, and (c) sequential designs with variable Bernoulli probabilities. To illustrate, we use real data on the monitoring of adverse events following the H1N1 vaccination. The numerical results are obtained using the R Sequential package.

PMID:36120901 | DOI:10.1177/09622802221122383

Ear Nose Throat J. 2022 Sep 18:1455613221126327. doi: 10.1177/01455613221126327. Online ahead of print.

ABSTRACT

BACKGROUND: Cutaneous malignant melanoma (CMM) is one of the most aggressive skin tumors. Sentinel lymph node biopsy (SLNB) is an important test before thorough treatment of melanoma. The aim of this study was to investigate cancer-specific survival (CSS) in patients with head and neck CMM after negative SLNB and to analyze predictors of decreased survival.

METHODS: Based on the Surveillance, Epidemiology and End Results (SEER) database, a study was conducted using data from patients with head and neck CMM after negative SLNB. The demographic, clinical, and pathological characteristics of the case population were analyzed. Cox univariate, Kaplan-Meier analysis, and multivariate Cox regression models were used to explore predictors of decreased survival; propensity score matching (PSM) analysis was used to reduce confounding bias, and outcomes were compared between the wide margin excision and narrow margin excision groups.

RESULTS: A total of 1597 confirmed head and neck CMM patients with SLNB-negative were found. A Breslow>4.0 mm was the highest independent risk predictor for patients (HR 3.82, 95% CI 2.04-7.16, P < .001), and significant risk independent predictors also included a high mitotic rate >4 (HR 1.54, 95% CI 1.06-2.25, P = .023). Age< 60 years old was a significant survival predictor (HR 0.56, 95% CI .37-.85, P = .007), and not scalp and neck CMM were also important factors for longer survival (auricle skin: HR .51, 95% CI .29-.90, P = .02; unspecified parts of face: HR .59, 95% CI .40-.87, P = .007). After harmonizing baseline data by PSM, it was found that the extent of surgical resection did not affect patient survival.

CONCLUSION: This study analyzed the risk factors affecting CSS in patients with CMM of the head and neck region with SLNB-negative and observed a statistically significant difference in the prognosis of patients with CMM in different aesthetic subunits of the head and neck region. Close clinical follow-up for this population is necessary, and periodic medical examinations should be carried out.

PMID:36120895 | DOI:10.1177/01455613221126327

Stat Methods Med Res. 2022 Sep 18:9622802221122410. doi: 10.1177/09622802221122410. Online ahead of print.

ABSTRACT

The few existing statistical models of breast cancer recurrence and progression to distant metastasis are predominantly based on multi-state modelling. While useful for summarising the risk of recurrence, these provide limited insight into the underlying biological mechanisms and have limited use for understanding the implications of population-level interventions. We develop an alternative, novel, and parsimonious approach for modelling latent tumour growth and spread to local and distant metastasis, based on a natural history model with biologically inspired components. We include marginal sub-models for local and distant breast cancer metastasis, jointly modelled using a copula function. Different formulations (and correlation shapes) are allowed, thus we can incorporate and directly model the correlation between local and distant metastasis flexibly and efficiently. Submodels for the latent cancer growth, the detection process, and screening sensitivity, together with random effects to account for between-patients heterogeneity, are included. Although relying on several parametric assumptions, the joint copula model can be useful for understanding – potentially latent – disease dynamics, obtaining patient-specific, model-based predictions, and studying interventions at a population level, for example, using microsimulation. We illustrate this approach using data from a Swedish population-based case-control study of postmenopausal breast cancer, including examples of useful model-based predictions.

PMID:36120891 | DOI:10.1177/09622802221122410

J Pastoral Care Counsel. 2022 Sep 18:15423050221124025. doi: 10.1177/15423050221124025. Online ahead of print.

ABSTRACT

Describes the nature of performance anxiety that can appear in students doing their first clinical placement in Supervised Pastoral Education¹ in the Canadian Association of Spiritual Care. Explores origins of performance anxiety drawing on research, the Diagnostic and statistical manual of mental disorders-5, theology of Paul Tillich and supervisory experiences of authors. Examines Canadian contextual factors like COVID-19, culture and multi-faith. Offers ways students might manage anxiety with help from supervisors and peers.

PMID:36120890 | DOI:10.1177/15423050221124025

Acta Ophthalmol. 2022 Sep 19. doi: 10.1111/aos.15260. Online ahead of print.

ABSTRACT

PURPOSE: The aim of the present study was to determine whether microperimetric parameters could predict the progression of an eye at high risk of age-related macular degeneration (AMD) at 24 months.

METHODS: We conducted a multicentric prospective non-comparative open-label study including patients with one eye in stage 4 of the Age-Related Eye Disease Study Group (AREDS) classification, and the other eye in AREDS stage 3 (study eye). A microperimetry examination (MAIA™, CenterVue, Padova, Italy) was performed at baseline and every 6 months during the 2-year follow-up. At the end of the follow-up, each study eye was classified as ‘progressive’ (i.e. AREDS stage 4) or ‘non-progressive’ (i.e. AREDS stage 3).

RESULTS: A total of 147 patients were analysed, of which 30.6% progressed from AREDS stage 3 to stage 4. The microperimetry criterion ‘mean retinal sensitivity’ was significantly different at baseline between non-progressive and progressive eyes (p = 0.022), with lower values for the latter. With a threshold for mean retinal sensitivity set at 24.7 dB, diagnostic sensitivity was 80% [95%CI (65.4-90.4)], specificity was 30.4% [95%CI (21.7-40.3)], positive predictive value was 33.6% [95%CI (24.8-43.4)], and negative predictive value was 77.5% [95%CI (61.5-89.2)]. In the multivariate analysis including microperimetric parameters and other routine ophthalmologic examinations, mean retinal sensitivity was the only predictive parameter statistically associated with progression (p = 0.0004).

CONCLUSIONS: Our findings are encouraging as regards the use of microperimetry, and mean retinal sensitivity value in particular, to predict the 2-year risk of progression to AREDS stage 4 eye.

PMID:36120870 | DOI:10.1111/aos.15260

Leuk Lymphoma. 2022 Sep 18:1-11. doi: 10.1080/10428194.2022.2123222. Online ahead of print.

ABSTRACT

We conducted a single-center retrospective study to assess cardiovascular (CV) toxicity and treatment discontinuation for CV toxicity in diffuse large B-cell lymphoma (DLBCL) or follicular lymphoma (FL) patients treated with immunochemotherapy (R-CHOP-like). Between 2006 and 2017, 433 patients were included (DLBCL: n = 345, FL: n = 88). The median age was 63 years (50-73). We defined three types of CV toxicity: early-onset cardiovascular toxicity (the event occurred within 6 months following treatment start); subacute toxicity (the event occurred between 6 months and 1 year after treatment start) and late toxicity (the event occurred 1 year or more after treatment start). Forty-eight (11.1%) patients experienced at least one anthracycline-related CV event. Seven patients experienced treatment discontinuation due to CV toxicity. Early-onset and subacute cardiac events were primarily acute heart failure (34.3%) and atrial fibrillation (28.6%). History of ischemic heart disease (p = 0.02) and valvular heart disease (p = 0.03) were associated with a higher risk of anthracycline-related CV event occurrence.

PMID:36120853 | DOI:10.1080/10428194.2022.2123222

Acta Radiol. 2022 Sep 18:2841851221124461. doi: 10.1177/02841851221124461. Online ahead of print.

ABSTRACT

BACKGROUND: Ultrasound examination of the medial side of the hip joint has been rarely used to evaluate the status of developmental dysplasia of the hip (DDH) in Pavlik harness treatment according to the literature.

PURPOSE: To analyze the effects of cartilaginous acetabulum, hip joint labrum, and acetabular tissue on the reduction of DDH.

MATERIAL AND METHODS: A total of 50 cases (100 hips) were detected by the Graf method with a high-frequency linear transducer (L 5-12), and there were 59 dislocated hips and 41 non-dislocated hips. Patients were treated with a Pavlik harness. Ultrasound examination of the medial side of the hip joint was performed for follow-up. The hip joints were divided into three groups: the non-dislocated group; the reducible group; and the non-reducible group.

RESULTS: The success rate of reduction was significantly higher when the acetabulum cartilage was located on the cephalic side (chi-square = 28.12, P < 0.001). The success rate was also significantly higher when the hip joint labrum was located on the cephalic side (chi-square = 17.21, P < 0.001). Type III and D had a higher success rate of reduction than type IV (P < 0.001). The pairwise comparison of the measurements of acetabular tissue between the non-dislocated group, the reducible group, and the non-reducible group showed statistical differences (P < 0.001).

CONCLUSION: The present study confirmed that the location of acetabulum cartilage and hip joint labrum affected the outcome of treatment. The degree of dislocation and the amount of acetabular tissue were correlated with the success rate of treatment.

PMID:36120851 | DOI:10.1177/02841851221124461

Acta Radiol. 2022 Sep 18:2841851221126596. doi: 10.1177/02841851221126596. Online ahead of print.

ABSTRACT

BACKGROUND: An abundance of CD8+ tumor infiltrating lymphocytes (TILs) in the center of solid tumors is a reliable predictive biomarker for patients eligible for immunotherapy.

PURPOSE: To develop a computed tomography (CT)-based radiomics signature for a preoperative prediction of an abundance of CD8+ TILs in non-small-cell lung cancer (NSCLC).

MATERIAL AND METHODS: In this retrospective study, 117 consecutive patients with pathologically confirmed NSCLC were included and randomly divided into training (n = 77) and test sets (n = 40). A total of 107 radiomics features were extracted from the three-dimensional volumes of interest of each patient. Least absolute shrinkage and selection operator (LASSO) regression was used to select the strongest features for abundance of CD8+ TILs in NSCLC, and the radiomics score was constructed through a linear combination of these selected features. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive performance of the radiomics score.

RESULTS: The radiomics score was associated with an abundance of CD8+ TILs in NSCLC, which achieved an area under the curve (AUC) of 0.83 (95% CI=0.73-0.92) and 0.68 (95% CI=0.54-0.87) in the training and test sets, respectively. The difference was not statistically significant (P = 0.20). The tumors with high CD8+ TILs tended to have heterogeneous dependences (high value of Dependence Non-Uniformity Normalized) and complicated texture (high value of Informational Measure of Correlation 1).

CONCLUSION: CT-based radiomics features have the ability to predict CD8+ TILs expression levels of an abundance of CD8+ TILs in NSCLC, which was shown to be a potential imaging biomarker for stratifying patients who may benefit from immunotherapy.

PMID:36120843 | DOI:10.1177/02841851221126596