A decision tool for radiographer-led abdominal image-guided stereotactic ablative body radiotherapy – Experience from a single institution

A decision tool for radiographer-led image-guided radiotherapy (IGRT) using cone-beam CT (CBCT) for abdominal stereotactic radiotherapy was developed and successfully implemented in a single department. The confidence of 7 therapeutic radiographers when undertaking online CBCT review increased, and the pooled median online match time was reduced by 1 m 8 s. While this may be advantageous for abdominal SABR, further evaluation of this work in a larger cohort is required to validate these results

Clinically Applicable Segmentation of Head and Neck Anatomy for Radiotherapy: Deep Learning Algorithm Development and Validation Study

BACKGROUND: Over half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This planning process can delay treatment while also introducing interoperator variability, resulting in downstream radiation dose differences. Although auto-segmentation algorithms offer a potentially time-saving solution, the challenges in defining, quantifying, and achieving expert performance remain. OBJECTIVE: Adopting a deep learning approach, we aim to demonstrate a 3D U-Net architecture that achieves expert-level performance in delineating 21 distinct head and neck organs at risk commonly segmented in clinical practice. METHODS: The model was trained on a data set of 663 deidentified computed tomography scans acquired in routine clinical practice and with both segmentations taken from clinical practice and segmentations created by experienced radiographers as part of this research, all in accordance with consensus organ at risk definitions. RESULTS: We demonstrated the model's clinical applicability by assessing its performance on a test set of 21 computed tomography scans from clinical practice, each with 21 organs at risk segmented by 2 independent experts. We also introduced surface Dice similarity coefficient, a new metric for the comparison of organ delineation, to quantify the deviation between organ at risk surface contours rather than volumes, better reflecting the clinical task of correcting errors in automated organ segmentations. The model's generalizability was then demonstrated on 2 distinct open-source data sets, reflecting different centers and countries to model training. CONCLUSIONS: Deep learning is an effective and clinically applicable technique for the segmentation of the head and neck anatomy for radiotherapy. With appropriate validation studies and regulatory approvals, this system could improve the efficiency, consistency, and safety of radiotherapy pathways

Managing neonatal and early childhood syndromic sepsis in sub-district hospitals in resource poor settings: improvement in quality of care through introduction of a package of interventions in rural Bangladesh

Sepsis is dysregulated systemic inflammatory response which can lead to tissue damage, organ failure, and death. With an estimated 30 million cases per year, it is a global public health concern. Severe infections leading to sepsis account for more than half of all under five deaths and around one quarter of all neonatal deaths annually. Most of these deaths occur in low and middle income countries and could be averted by rapid assessment and appropriate treatment. Evidence suggests that service provision and quality of care pertaining to sepsis management in resource poor settings can be improved significantly with minimum resource allocation and investments. Cognizant of the stark realities, a project titled 'Interrupting Pathways to Sepsis Initiative' (IPSI) introduced a package of interventions for improving quality of care pertaining to sepsis management at 2 sub-district level public hospitals in rural Bangladesh. We present here the quality improvement process and achievements regarding some fundamental steps of sepsis management which include rapid identification and admission, followed by assessment for hypoxemia, hypoglycaemia and hypothermia, immediate resuscitation when required and early administration of parenteral broad spectrum antibiotics.Key components of the intervention package include identification of structural and functional gaps through a baseline environmental scan, capacity development on protocolized management through training and supportive supervision by onsite 'Program Coaches', facilitating triage and rapid transfer of patients through 'Welcoming Persons' and enabling rapid treatment through 'Task Shifting' from on-call physicians to on-duty paramedics in the emergency department and on-call physicians to on-duty nurses in the inpatient department.From August, 2013 to March, 2015, 1,262 under-5 children were identified as syndromic sepsis in the emergency departments; of which 82% were admitted. More neonates (30%) were referred to higher level facilities than post-neonates (6%) (p<0.05). Immediately after admission, around 99% were assessed for hypoxemia, hypoglycaemia and hypothermia. Around 21% were hypoxemic (neonate-37%, post-neonate-18%, p<0.05), among which 94% received immediate oxygenation. Vascular access was established in 78% cases and 85% received recommended broad spectrum antibiotics parenterally within 1 hour of admission. There was significant improvement in the rate of establishing vascular access and choice of recommended first line parenteral antibiotic over time. After arrival in the emergency department, the median time taken for identification of syndromic sepsis and completion of admission procedure was 6 minutes. The median time taken for completion of assessment for complications was 15 minutes and administration of first dose of broad spectrum antibiotics was 35 minutes. There were only 3 inpatient deaths during the reporting period.Needs based health systems strengthening, supportive-supervision and task shifting can improve the quality and timeliness of in-patient management of syndromic sepsis in resource limited settings