Dysphagia-optimised intensity-modulated radiotherapy versus standard intensity-modulated radiotherapy in patients with head and neck cancer (DARS): a phase 3, multicentre, randomised, controlled trial.

BACKGROUND: Most newly diagnosed oropharyngeal and hypopharyngeal cancers are treated with chemoradiotherapy with curative intent but at the consequence of adverse effects on quality of life. We aimed to investigate if dysphagia-optimised intensity-modulated radiotherapy (DO-IMRT) reduced radiation dose to the dysphagia and aspiration related structures and improved swallowing function compared with standard IMRT. METHODS: DARS was a parallel-group, phase 3, multicentre, randomised, controlled trial done in 22 radiotherapy centres in Ireland and the UK. Participants were aged 18 years and older, had T1-4, N0-3, M0 oropharyngeal or hypopharyngeal cancer, a WHO performance status of 0 or 1, and no pre-existing swallowing dysfunction. Participants were centrally randomly assigned (1:1) using a minimisation algorithm (balancing factors: centre, chemotherapy use, tumour type, American Joint Committee on Cancer tumour stage) to receive DO-IMRT or standard IMRT. Participants and speech language therapists were masked to treatment allocation. Radiotherapy was given in 30 fractions over 6 weeks. Dose was 65 Gy to primary and nodal tumour and 54 Gy to remaining pharyngeal subsite and nodal areas at risk of microscopic disease. For DO-IMRT, the volume of the superior and middle pharyngeal constrictor muscle or inferior pharyngeal constrictor muscle lying outside the high-dose target volume had a mandatory 50 Gy mean dose constraint. The primary endpoint was MD Anderson Dysphagia Inventory (MDADI) composite score 12 months after radiotherapy, analysed in the modified intention-to-treat population that included only patients who completed a 12-month assessment; safety was assessed in all randomly assigned patients who received at least one fraction of radiotherapy. The study is registered with the ISRCTN registry, ISRCTN25458988, and is complete. FINDINGS: From June 24, 2016, to April 27, 2018, 118 patients were registered, 112 of whom were randomly assigned (56 to each treatment group). 22 (20%) participants were female and 90 (80%) were male; median age was 57 years (IQR 52-62). Median follow-up was 39·5 months (IQR 37·8-50·0). Patients in the DO-IMRT group had significantly higher MDADI composite scores at 12 months than patients in the standard IMRT group (mean score 77·7 [SD 16·1] vs 70·6 [17·3]; mean difference 7·2 [95% CI 0·4-13·9]; p=0·037). 25 serious adverse events (16 serious adverse events assessed as unrelated to study treatment [nine in the DO-IMRT group and seven in the standard IMRT group] and nine serious adverse reactions [two vs seven]) were reported in 23 patients. The most common grade 3-4 late adverse events were hearing impairment (nine [16%] of 55 in the DO-IMRT group vs seven [13%] of 55 in the standard IMRT group), dry mouth (three [5%] vs eight [15%]), and dysphagia (three [5%] vs eight [15%]). There were no treatment-related deaths. INTERPRETATION: Our findings suggest that DO-IMRT improves patient-reported swallowing function compared with standard IMRT. DO-IMRT should be considered a new standard of care for patients receiving radiotherapy for pharyngeal cancers. FUNDING: Cancer Research UK.

Comparison of transversus abdominis activation characteristics between healthy and chronic low back pain population during upright functional movement.

BACKGROUND: Previous literature suggests that transversus abdominis (TrA) activation is diminished in chronic low back pain (cLBP) subjects compared to healthy subjects in less-functional positions. However, few studies have investigated the effects of upright functional movement on TrA activation in cLBP individuals. OBJECTIVE: This pilot study aimed to compare TrA activation characteristics in healthy and cLBP subjects during the movement of double leg standing (DLS) to single leg standing (SLS) and to a 30∘ single leg quarter squat (QSLS). METHODS: TrA activation was determined by the percentage change in TrA thickness from DLS to SLS and DLS to QSLS. TrA thickness was measured in 14 healthy and 14 cLBP participants using ultrasound imaging with a probe holder at 20 mm and 30 mm from the fascia conjunction point. RESULTS: At both measurement points (20 and 30 mm), there were no significant main effects of body sides, lower limb movements and the interactions between them on TrA activations between the healthy and cLBP participants even after covariates were adjusted for (all p> 0.05). CONCLUSIONS: Results from this study suggest the evaluation of TrA activation during upright functional movements as part of an assessment for cLBP management may not be suggested.

Chemical Advances in Therapeutic Application of Exosomes and Liposomes.

Exosomes and liposomes are vesicular nanoparticles that can encapsulate functional cargo. The chemical similarities between naturally occurring exosomes and synthetic liposomes have accelerated the development of exosome mimetics as a therapeutic drug delivery platform under physiological and pathological environments. To maximise the applications of exosomes and liposomes in the clinical setting, it is essential to look into their basic chemical properties and utilise these characteristics to optimise the preparation, loading, modification and hybridisation. This review summarises the chemical and biological properties of both exosomal and liposomal systems as well as some of the challenges related to their production and application. This article concludes with a discussion on potential perspectives for the integration of exosomal and liposomal technologies in mapping better approaches for their biomedical use, especially in therapeutics.

Wound Healing Properties of Exosomes - A Review and Modelling of Combinatorial Analysis Strategies.

Wound healing is an elaborated process, well-regulated via cell migration and proliferation. Although the physiological basics of wound healing have been thoroughly investigated and reported, much remains to be studied. Particularly, various studies have demonstrated the immunomodulatory roles of exosomes derived from plant cells, mammalian cells, and mesenchymal stem cells (MSCs) in the healing and repairing system. The paracrine and therapeutic effects of exosomes are mainly associated with the broad exosomal cargo content comprising growth factors, cytokines, enzymes, nucleic acids, proteins, and lipid signaling molecules. Nevertheless, the functional or mechanism pathway of exosomes with reference to overall exosomal cargo remains undetermined. To date, combinatorial analysis strategies employing Database for Annotation, Visualization, and Integrated Discovery (DAVID), STRING tools, Gene Ontology (GO), Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway enrichment analysis, as well as Ingenuity Pathway Analysis (IPA) have been applied in elucidating network interaction and functional pathway of exosomes. In this review paper, the application of combinatorial analysis strategies is demonstrated to better understand the therapeutic potentials of exosomes in the wound healing process. In conclusion, functional modulation of exosomal cargo for specific biological treatment is achievable, and modelling of combinatorial analysis strategies will hopefully bridge the research gap and provide a paradigm shift to regenerative processes.

Chemotherapy-Induced Peripheral Neuropathy: Epidemiology, Pathomechanisms and Treatment.

PURPOSE: This review provides an update on the current clinical, epidemiological and pathophysiological evidence alongside the diagnostic, prevention and treatment approach to chemotherapy-induced peripheral neuropathy (CIPN). FINDINGS: The incidence of cancer and long-term survival after treatment is increasing. CIPN affects sensory, motor and autonomic nerves and is one of the most common adverse events caused by chemotherapeutic agents, which in severe cases leads to dose reduction or treatment cessation, with increased mortality. The primary classes of chemotherapeutic agents associated with CIPN are platinum-based drugs, taxanes, vinca alkaloids, bortezomib and thalidomide. Platinum agents are the most neurotoxic, with oxaliplatin causing the highest prevalence of CIPN. CIPN can progress from acute to chronic, may deteriorate even after treatment cessation (a phenomenon known as coasting) or only partially attenuate. Different chemotherapeutic agents share both similarities and key differences in pathophysiology and clinical presentation. The diagnosis of CIPN relies heavily on identifying symptoms, with limited objective diagnostic approaches targeting the class of affected nerve fibres. Studies have consistently failed to identify at-risk cohorts, and there are no proven strategies or interventions to prevent or limit the development of CIPN. Furthermore, multiple treatments developed to relieve symptoms and to modify the underlying disease in CIPN have failed. IMPLICATIONS: The increasing prevalence of CIPN demands an objective approach to identify at-risk patients in order to prevent or limit progression and effectively alleviate the symptoms associated with CIPN. An evidence base for novel targets and both pharmacological and non-pharmacological treatments is beginning to emerge and has been recognised recently in publications by the American Society of Clinical Oncology and analgesic trial design expert groups such as ACTTION.

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.

Buried Bumper Syndrome: a rare complication during radical chemoradiotherapy for head and neck cancer.

Patients undergoing radical treatment particularly chemoradiotherapy for cancer of the upper aerodigestive tract frequently experience progressive deterioration in swallow during and immediately after treatment. It is important to identify patients at high risk of compromised feeding early, following diagnosis, so that alternate feeding routes, such as percutaneous endoscopic gastrostomies (PEGs), can be promptly and prophylactically instituted, in keeping with the UK Head and Neck Cancer Guidelines (2016).

Life Beyond Heart Failure-What Are the Long-Term Challenges, Supportive Care Needs, and Views Toward Supportive Care of Multiethnic Asian Patients With Left Ventricular Assist Device and Their Caregivers?

CONTEXT: Challenges experienced by patients with the left ventricular assist device (LVAD) and their caregivers during the early period after LVAD implantation are well documented. However, little is known about long-term challenges, supportive care needs, and views toward supportive care of Asian LVAD patients and caregivers. OBJECTIVES: We aimed to explore the experiences of multiethnic Asian LVAD patients and caregivers so as to identify their long-term challenges, supportive care needs, and views toward supportive care. METHODS: Semistructured interviews with LVAD patients and caregivers were conducted based on the grounded theory approach. Participants were purposively recruited from the inpatient and outpatient settings of the National Heart Center Singapore. RESULTS: A total of 30 patients and 11 caregivers participated. More than half of the participants were Chinese (patients 63%; caregivers 64%). Most patients (83%) were males, whereas most caregivers were females (91%). The median duration on support was 31 months and 46 months for patients and caregivers, respectively. The implantation of the LVAD was a significant milestone in their lives and caused long-term changes in multiple domains (physical, financial, social, psychoemotional, and spiritual). Experiencing permanent and recurrent losses over time was particularly challenging. Participants expressed the need for mutual support between patient and caregiver and connectedness with others and society at large. Participants desired holistic supportive care from their health care team. CONCLUSION: Asian LVAD patients and caregivers experienced long-term challenges and had unique supportive care needs. Our findings have implications on the design of future interventions and supportive care models.

MRI-Based Upper Abdominal Organs-at-Risk Atlas for Radiation Oncology.

PURPOSE: The purpose of our study was to provide a guide for identification and contouring of upper abdominal organs-at-risk (OARs) in the setting of online magnetic resonance imaging (MRI)-guided radiation treatment planning and delivery. METHODS AND MATERIALS: After a needs assessment survey, it was determined that an upper abdominal MRI-based atlas of normal OARs would be of benefit to radiation oncologists and radiation therapists. An anonymized diagnostic 1.5T MRI from a patient with typical upper abdominal anatomy was used for atlas development. Two MRI sequences were selected for contouring, a T1-weighted gadoxetic acid contrast-enhanced MRI acquired in the hepatobiliary phase and axial fast imaging with balanced steady-state precession. Two additional clinical MRI sequences from commercial online MRI-guided radiation therapy systems were selected for contouring and were included in the final atlas. Contours from each data set were completed and reviewed by radiation oncologists, along with a radiologist who specializes in upper abdominal imaging, to generate a consensus upper abdominal MRI-based OAR atlas. RESULTS: A normal OAR atlas was developed, including recommendations for contouring. The atlas and contouring guidance are described, and high-resolution MRI images and contours are displayed. OARs, such as the bile duct and biliary tree, which may be better seen on MRI than on computed tomography, are highlighted. The full DICOM/DICOM-RT MRI images from both the diagnostic and clinical online MRI-guided radiation therapy systems data sets have been made freely available, for educational purposes, at econtour.org. CONCLUSIONS: This MRI contouring atlas for upper abdominal OARs should provide a useful reference for contouring and education. Its routine use may help to improve uniformity in contouring in radiation oncology planning and OAR dose calculation. Full DICOM/DICOM-RT images are available online and provide a valuable educational resource for upper abdominal MRI-based radiation therapy planning and delivery.

Impact of a Formal Advance Care Planning Program on End-of-Life Care for Patients With Heart Failure: Results From a Randomized Controlled Trial.

BACKGROUND: There is no evidence on effectiveness of advance care planning (ACP) among patients with heart failure (HF). We examined the effect of an ACP program in facilitating end of life (EOL) care consistent with the preferences of patients with HF (primary aim), and on their decisional conflict, discussion with surrogates, illness understanding, anxiety, depression, and quality of life (secondary aims). METHODS: We randomized 282 patients with HF to receive ACP (n=93) or usual care (control arm, n=189). Primary outcomes were assessed among deceased (n=89) and secondary outcomes from baseline and 6 follow-ups conducted every 4 months. RESULTS: Deceased patients in the ACP arm were no more likely than those in control arm to have wishes followed for EOL treatments (ACP: 35%, Control: 44%; P= .47), or place of death (ACP: 52%, Control: 51%; P = .1.00). A higher proportion in the ACP arm had wishes followed for cardiopulmonary resuscitation (ACP: 83%, Control: 62%; P = .12). At first follow-up, patients with ACP had lower decisional conflict (ß = -10.8, P< .01) and were more likely to discuss preferences with surrogates (ß = 1.3, P = .04). ACP did not influence other outcomes. CONCLUSION: This trial did not confirm that our ACP program was effective in facilitating EOL care consistent with patient preferences. The program led to short-term improvements in the decision-making.

Assessing the Role of Artificial Intelligence (AI) in Clinical Oncology: Utility of Machine Learning in Radiotherapy Target Volume Delineation.

The fields of radiotherapy and clinical oncology have been rapidly changed by the advances of technology. Improvement in computer processing power and imaging quality heralded precision radiotherapy allowing radiotherapy to be delivered efficiently, safely and effectively for patient benefit. Artificial intelligence (AI) is an emerging field of computer science which uses computer models and algorithms to replicate human-like intelligence and perform specific tasks which offers a huge potential to healthcare. We reviewed and presented the history, evolution and advancement in the fields of radiotherapy, clinical oncology and machine learning. Radiotherapy target delineation is a complex task of outlining tumour and organ at risks volumes to allow accurate delivery of radiotherapy. We discussed the radiotherapy planning, treatment delivery and reviewed how technology can help with this challenging process. We explored the evidence and clinical application of machine learning to radiotherapy. We concluded on the challenges, possible future directions and potential collaborations to achieve better outcome for cancer patients.