57 research outputs found
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“Barriers to” and “Recommendations for” providing care and support for children living as AIDS orphans in township communities in the Eastern Cape South Africa: A cluster analysis
Background: Orphan-hood is a major consequence of the Acquired Immune Deficiency Syndrome (AIDS) pandemic globally. In South Africa most children who are AIDS orphans live in township communities. They are often uncared for and unsupported by the community, and experience recurrent psychological trauma and much personal suffering. Identifying the “barriers to” and “recommendations for” providing care and support to these vulnerable children is vital to enable the development of comprehensive implementations to meet these children's unique care and support needs. Objective: Using empirical data from health and social care professionals and cluster analysis to identify “barriers to” and “recommendations for” providing care and support to children living as AIDS orphans in township communities in Nelson Mandela Bay South Africa. Design: Data was collected using a descriptive phenomenology research design incorporated an exploratory, contextual and descriptive approach. In-depth unstructured interviews were used to collect data from participants. Participants: The primary health care nurses (PN) (n = 10) and social workers (SW) (n = 8) were selected using criterion-based purposive sampling, whilst snowball sampling was used to select psychologists (Psy) (n = 6). Participants are referred to as health and social care professionals. Setting: Participants were selected using purposive sampling (nurses and social workers) and snowball sampling (psychologists) from four primary health care clinics and twelve satellite health care clinics, all located in township communities in Nelson Mandela Bay, South Africa. The participants were all caring for and supporting children who are AIDS orphans living in these communities. Methods: In-depth individual interviews occurred between April and Nov 2013 which were recorded and transcribed verbatim. All data was then analysed using cluster analysis to identify “barriers to” and “recommendations for” providing care and support to these vulnerable children as identified by these research participants. Results: All “barriers to” and “recommendation for” are represented in this cluster analysis. There were six identified clusters illustrating “Barriers to” and four visualised clusters illustrating “Recommendations for”. The barriers can be identified using the following broad themes; B1, fundamental barriers; B2, primarily related to legislative and policy frameworks, B3, lack of human and financial resources also included stigma and communication. B4, grief, high risk behaviours and cumbersome bureaucratic processes and included loss of trust in adults; B5, barriers related to poverty B6, barriers related to poverty also included non-disclosure of HIV status. Regarding the “recommendations for” these can be identified using the following broad themes; R1, developing the resilience of health and social care professionals. R2, developing interventions, to meet the unique needs of these AIDS orphans. R3, developing, empowering and capacitating professionals and R4, facilitating an empowering working environment for professionals. Conclusions: Significant clusters emerged and the “barriers to” and “recommendations for” were identified in this research which could be used to inform the development of an intervention to provide “best practice” care and support to these vulnerable children living in these township communities
Photoresist patterned thick-film piezoelectric elements on silicon
A fundamental limitation of screen printing is the achievable alignment accuracy and resolution. This paper presents details of a thick-resist process that improves both of these factors. The technique involves exposing/developing a thick resist to form the desired pattern and then filling the features with thick film material using a doctor blading process. Registration accuracy comparable with standard photolithographic processes has been achieved resulting in minimum feature sizes of <50 ?m and a film thickness of 100 ?m. Piezoelectric elements have been successfully poled on a platinised silicon wafer with a measured d 33 value of 60 pCN?1
Bronchial Artery Embolisation for Massive Haemoptysis: Immediate and Long-Term Outcomes-A Retrospective Study.
INTRODUCTION: Bronchial artery embolisation (BAE) is an established treatment method for massive haemoptysis. The aim of this study is to evaluate the impact of BAE on in-hospital outcomes and long-term survival in patients with massive haemoptysis. METHODS: Retrospective review of all cases of acute massive haemoptysis treated by BAE between April 2000 and April 2012 with at least a 5 year follow up of each patient. Targeted BAE was performed in cases with lateralising symptoms, bronchoscopic sites of bleeding or angiographic unilateral abnormal vasculature. In the absence of lateralising symptoms or signs, bilateral BAE was performed. RESULTS: 96 BAEs were performed in 68 patients. The majority (64 cases, 67%) underwent unilateral procedures. 83 (86.5%) procedures resulted in immediate/short term control of haemoptysis which lasted for longer than a month. The mean duration of haemoptysis free period after embolisation was 96 months. There were three major complications (cardio-pulmonary arrest, paraparesis and stroke). 38 (56%) patients were still alive at least 5 years following their BAE. Benign causes were associated with significantly longer haemoptysis free periods, mean survival 108 months compared to 32 months in patients with an underlying malignant cause (p = 0.005). An episode of haemoptysis within a month of the initial embolisation was associated reduced overall survival (p = 0.033). CONCLUSION: BAE is effective in controlling massive haemoptysis. Long-term survival depends on the underlying pulmonary pathology. Strategies are required to avoid incomplete initial embolisation, which is associated with ongoing haemoptysis and high mortality despite further BAE
Prediction of Patient Outcomes in Locally Advanced Cervical Carcinoma Following Chemoradiotherapy—Comparative Effectiveness of Magnetic Resonance Imaging and 2-Deoxy-2-[18F]fluoro-D-glucose Imaging
Purpose: To evaluate the utility and comparative effectiveness of three five-point qualitative scoring systems for assessing response on PET-CT and MRI imaging individually and in combination, following curative-intent chemoradiotherapy (CRT) in locally advanced cervical cancer (LACC). Their performance in the prediction of subsequent patient outcomes was also assessed; Methods: Ninety-seven patients with histologically confirmed LACC treated with CRT using standard institutional protocols at a single centre who underwent PET-CT and MRI at staging and post treatment were identified retrospectively from an institutional database. The post-CRT imaging studies were independently reviewed, and response assessed using five-point scoring tools for T2WI, DWI, and FDG PET-CT. Patient characteristics, staging, treatment, and follow-up details including progression-free survival (PFS) and overall survival (OS) outcomes were collected. To compare diagnostic performance metrics, a two-proportion z-test was employed. A Kaplan–Meier analysis (Mantel–Cox log-rank) was performed. Results: The T2WI (p < 0.00001, p < 0.00001) and DWI response scores (p < 0.00001, p = 0.0002) had higher specificity and accuracy than the PET-CT. The T2WI score had the highest positive predictive value (PPV), while the negative predictive value (NPV) was consistent across modalities. The combined MR scores maintained high NPV, PPV, specificity, and sensitivity, and the PET/MR consensus scores showed superior diagnostic accuracy and specificity compared to the PET-CT score alone (p = 0.02926, p = 0.0083). The Kaplan–Meier analysis revealed significant differences in the PFS based on the T2WI (p < 0.001), DWI (p < 0.001), combined MR (p = 0.003), and PET-CT/MR consensus scores (p < 0.001) and in the OS for the T2WI (p < 0.001), DWI (p < 0.001), and combined MR scores (p = 0.031) between responders and non-responders. Conclusion: Post-CRT response assessment using qualitative MR scoring and/or consensus PET-CT and MRI scoring was a better predictor of outcome compared to PET-CT assessment alone. This requires validation in a larger prospective study but offers the potential to help stratify patient follow-up in the future
Can MR textural analysis improve the prediction of extracapsular nodal spread in patients with oral cavity cancer?
Objective: To explore the utility of MR texture analysis (MRTA) for detection of nodal extracapsular spread (ECS) in oral cavity squamous cell carcinoma (SCC).
Methods: 115 patients with oral cavity SCC treated with surgery and adjuvant (chemo)radiotherapy were identified retrospectively. First-order texture parameters (entropy, skewness and kurtosis) were extracted from tumour and nodal regions of interest (ROIs) using proprietary software (TexRAD). Nodal MR features associated with ECS (flare sign, irregular capsular contour; local infiltration; nodal necrosis) were reviewed and agreed in consensus by two experienced radiologists. Diagnostic performance characteristics of MR features of ECS were compared with primary tumour and nodal MRTA prediction using histology as the gold standard. Receiver operating characteristic (ROC) and regression analyses were also performed.
Results: Nodal entropy derived from contrast-enhanced T1-weighted images was significant in predicting ECS (p = 0.018). MR features had varying accuracy: flare sign (70%); irregular contour (71%); local infiltration (66%); and nodal necrosis (64%). Nodal entropy combined with irregular contour was the best predictor of ECS (p = 0.004, accuracy 79%).
Conclusion: First-order nodal MRTA combined with imaging features may improve ECS prediction in oral cavity SCC
Accuracy of Response Assessment FDG PET-CT Post (Chemo)Radiotherapy in HPV Negative Oropharynx Squamous Cell Carcinoma
Background: Data on the accuracy of response assessment 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography-computed tomography (PET-CT) following (chemo)radiotherapy in patients with oropharynx squamous cell carcinoma (OPSCC) is predominantly based on HPV-positive disease. There is a paucity of data for HPV-negative disease, which has a less favourable prognosis. Methods: 96 patients treated with (chemo)radiotherapy for HPV-negative OPSCC with baseline and response assessment FDG PET-CT between 2013–2020, were analysed. PET-CT response was classified as negative, equivocal, or positive based on qualitative reporting. PET-CT response categories were analysed with reference to clinicopathological outcomes. Test characteristics were evaluated, comparing negative results to equivocal and positive results together. Post-test probabilities were calculated separately for positive and equivocal or negative results. Results: Median follow-up was 26 months. The negative predictive value of a negative scan was 93.7 and 93.2%, respectively, for primary tumour and nodal disease. For a negative scan, the post-test probability was 0.06 for primary and 0.07 for nodal disease. The post-test probability of an equivocal scan was 0.51 and 0.72 for primary and lymph node, respectively. The post-test probability of a positive scan approached 1. For patients with/without a negative scan, two-year overall survival and progression-free survival were 83% versus 30% and 79% versus 17% (p < 0.001), respectively. Conclusion: The NPV of a negative response assessment PET-CT in HPV-negative OPSCC is high, supporting a strategy of clinical monitoring. Contrasting with the published literature for HPV-positive OPSCC, an equivocal response scan was associated with a moderate rate of residual disease
Harmonisation of scanner-dependent contrast variations in magnetic resonance imaging for radiation oncology, using style-blind auto-encoders.
Background and purpose
Magnetic Resonance Imaging (MRI) exhibits scanner dependent contrast, which limits generalisability of radiomics and machine-learning for radiation oncology. Current deep-learning harmonisation requires paired data, retraining for new scanners and often suffers from geometry-shift which alters anatomical information. The aim of this study was to investigate style-blind auto-encoders for MRI harmonisation to accommodate unpaired training data, avoid geometry-shift and harmonise data from previously unseen scanners.
Materials and methods
A style-blind auto-encoder, using adversarial classification on the latent-space, was designed for MRI harmonisation. The public CC359 T1-w MRI brain dataset includes six scanners (three manufacturers, two field strengths), of which five were used for training. MRI from all six (including one unseen) scanner were harmonised to common contrast. Harmonisation extent was quantified via Kolmogorov-Smirnov testing of residual scanner dependence of 3D radiomic features, and compared to WhiteStripe normalisation. Anatomical content preservation was measured through change in structural similarity index on contrast-cycling (δSSIM).
Results
The percentage of radiomics features showing statistically significant scanner-dependence was reduced from 41% (WhiteStripe) to 16% for white matter and from 39% to 27% for grey matter. δSSIM < 0.0025 on harmonisation and de-harmonisation indicated excellent anatomical content preservation.
Conclusions
Our method harmonised MRI contrast effectively, preserved critical anatomical details at high fidelity, trained on unpaired data and allowed zero-shot harmonisation. Robust and clinically translatable harmonisation of MRI will enable generalisable radiomic and deep-learning models for a range of applications, including radiation oncology treatment stratification, planning and response monitoring
Prediction of outcome in anal squamous cell carcinoma using radiomic feature analysis of pre-treatment FDG PET-CT
Purpose: Incidence of anal squamous cell carcinoma (ASCC) is increasing, with curative chemoradiotherapy (CRT) as the primary treatment of non-metastatic disease. A significant proportion of patients have locoregional treatment failure (LRF), but distant relapse is uncommon. Accurate prognostication of progression-free survival (PFS) would help personalisation of CRT regimens. The study aim was to evaluate novel imaging pre-treatment features, to prognosticate for PFS in ASCC.
Methods: Consecutive patients with ASCC treated with curative intent at a large tertiary referral centre who underwent pre-treatment FDG-PET/CT were included. Radiomic feature extraction was performed using LIFEx software on baseline FDG-PET/CT. Outcome data (PFS) was collated from electronic patient records. Elastic net regularisation and feature selection were used for logistic regression model generation on a randomly selected training cohort and applied to a validation cohort using TRIPOD guidelines. ROC-AUC analysis was used to compare performance of a regression model encompassing standard clinical prognostic factors (age, sex, tumour and nodal stage—model A), a radiomic feature model (model B) and a combined radiomic/clinical model (model C).
Results: A total of 189 patients were included in the study, with 145 in the training cohort and 44 in the validation cohort. Median follow-up was 35.1 and 37. 9 months, respectively for each cohort, with 70.3% and 68.2% reaching this time-point with PFS. GLCM entropy (a measure of randomness of distribution of co-occurring pixel grey-levels), NGLDM busyness (a measure of spatial frequency of changes in intensity between nearby voxels of different grey-level), minimum CT value (lowest HU within the lesion) and SMTV (a standardized version of MTV) were selected for inclusion in the prognostic model, alongside tumour and nodal stage. AUCs for performance of model A (clinical), B (radiomic) and C (radiomic/clinical) were 0.6355, 0.7403, 0.7412 in the training cohort and 0.6024, 0.6595, 0.7381 in the validation cohort.
Conclusion: Radiomic features extracted from pre-treatment FDG-PET/CT in patients with ASCC may provide better PFS prognosis than conventional staging parameters. With external validation, this might be useful to help personalise CRT regimens in the future
Evaluation of Locoregional Recurrence Patterns Following Adjuvant (Chemo)Radiotherapy for Oral Cavity Carcinoma
Aims: To evaluate patterns of locoregional recurrence following adjuvant (chemo)radiotherapy for oral cavity squamous cell carcinomas.
Materials and methods: One hundred and one patients who received adjuvant radiotherapy ± chemotherapy for oral cavity squamous cell carcinoma between 2013 and 2016 were analysed. For documented locoregional recurrence, recurrence imaging was deformably co-registered to the planning computed tomography scan. The volume of recurrence was delineated (Vrec). Vrec coverage by 95% of the corresponding planning target volume prescription dose was determined and the location compared with planning target volumes. Sites of recurrence were classified using a combined volume and centroid-based method: (A) central high dose, (B) peripheral high dose, (C) central low dose, (D) central peripheral dose, (E) extraneous.
Results: The median follow-up was 36 months. Forty-three per cent and 53% of patients received radiotherapy to the ipsilateral neck only and bilateral neck, respectively. Three-year overall survival, disease-free survival, local control, regional control and distant metastases-free survival were 63.0, 65.6, 88.0, 85.1 and 85.3%, respectively. Of 10 episodes of primary site recurrences, five were type A, four type B and one was type E. Of 14 episodes of regional recurrence, five were type A, two type C, two type D and five type E. Five of 21 (24%) patients with oral tongue carcinoma with an undissected/unirradiated contralateral neck had a type E contralateral neck recurrence, including 2/11 with pN0, 1/4 with pN1 and 2/6 with pN2 disease.
Conclusions: Marginal and out-of-field recurrences remain a significant pattern of failure. We advocate generous target delineation postoperatively and, for oral tongue carcinomas, a comprehensive approach with bilateral neck irradiation
Prediction of prostate tumour hypoxia using pre-treatment MRI-derived radiomics: preliminary findings
Purpose
To develop a machine learning (ML) model based on radiomic features (RF) extracted from whole prostate gland magnetic resonance imaging (MRI) for prediction of tumour hypoxia pre-radiotherapy.
Material and methods
Consecutive patients with high-grade prostate cancer and pre-treatment MRI treated with radiotherapy between 01/12/2007 and 1/08/2013 at two cancer centres were included. Cancers were dichotomised as normoxic or hypoxic using a biopsy-based 32-gene hypoxia signature (Ragnum signature). Prostate segmentation was performed on axial T2-weighted (T2w) sequences using RayStation (v9.1). Histogram standardisation was applied prior to RF extraction. PyRadiomics (v3.0.1) was used to extract RFs for analysis. The cohort was split 80:20 into training and test sets. Six different ML classifiers for distinguishing hypoxia were trained and tuned using five different feature selection models and fivefold cross-validation with 20 repeats. The model with the highest mean validation area under the curve (AUC) receiver operating characteristic (ROC) curve was tested on the unseen set, and AUCs were compared via DeLong test with 95% confidence interval (CI).
Results
195 patients were included with 97 (49.7%) having hypoxic tumours. The hypoxia prediction model with best performance was derived using ridge regression and had a test AUC of 0.69 (95% CI: 0.14). The test AUC for the clinical-only model was lower (0.57), but this was not statistically significant (p = 0.35). The five selected RFs included textural and wavelet-transformed features.
Conclusion
Whole prostate MRI-radiomics has the potential to non-invasively predict tumour hypoxia prior to radiotherapy which may be helpful for individualised treatment optimisation
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