Paul A. Bromiley’s research while affiliated with University of Manchester and other places

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Publications (102)


Are Different Modes of Weight Loss Associated with Survival in Oropharyngeal Cancer?
  • Article

October 2023

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28 Reads

International Journal of Radiation Oncology*Biology*Physics

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A. McWilliam

Low muscle mass measured at T12 is a prognostic biomarker in unresectable oesophageal cancers receiving chemoradiotherapy

June 2023

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23 Reads

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6 Citations

Radiotherapy and Oncology

Background and purpose: Low muscle mass is an imaging biomarker of patient frailty that has been associated with increased toxicity and decreased survival in a number of cancers. Patients with unresectable oesophageal cancer receive chemoradiotherapy as standard of care. Muscle mass is not yet an established prognostic marker in this population. Muscle mass is usually assessed by segmenting skeletal muscle at the L3 vertebral level. But radiotherapy planning scans for oesophageal cancers do not always image this level, which has limited previous studies of body composition. Skeletal muscle is known to regulate immune function, but the association of muscle mass with lymphopenia in cancer patients has not been shown. Materials and methods: We retrospectively analyse 135 oesophageal cancer patients who received chemoradiotherapy and investigate the prognostic value of skeletal muscle area assessed at T12. We also examine the association between muscle mass and radiation-induced lymphopenia. Results: We find that low muscle mass is associated with poorer overall survival (hazard ratio [95% confidence interval]: 0.72 [0.53-0.97]). However, this effect interacts with body mass index (BMI) such that the prognostic value of low muscle mass is removed by high BMI. In our study, patients with low muscle mass were more prone to radiation-induced lymphopenia (75% vs. 50% in patients with high muscle mass). A significant decrease in circulating lymphocytes was associated with poorer overall survival (hazard ratio [95% confidence interval]: 0.68 [0.47-0.99]). Conclusion: Our study shows that assessing muscle mass at T12 is feasible and provides prognostic information. Low muscle mass at T12 is associated with poorer overall survival and increased risk of radiation-induced lymphopenia. Muscle mass provides additional information over performance status and BMI. Low BMI patients are most affected by low muscle mass, highlighting the importance of close nutritional support in this population.




Figure 2. The five reference points, one on each corner and the fifth on bra.
Figure 3. Selected lateral spine dual energy X-ray absorptiometry scans from a series of patients demonstrate the semiquantitative visual grading system of Genant et al. [16]: (a) normal vertebrae, (b) deformed vertebrae (spondylosis), (c) grade 1 (mild fracture, 20-25% reduction of vertebral height), (d) grade 2 (moderate fracture, 25-40% reduction of vertebral height), (e) grade 3 ( severe Figure 3. Selected lateral spine dual energy X-ray absorptiometry scans from a series of patients demonstrate the semiquantitative visual grading system of Genant et al. [16]: (a) normal vertebrae, (b) deformed vertebrae (spondylosis), (c) grade 1 (mild fracture, 20-25% reduction of vertebral height), (d) grade 2 (moderate fracture, 25-40% reduction of vertebral height), (e) grade 3 ( severe fracture, >40% reduction of vertebral height), and (f) vertebra where beginner radiographer misdiagnosed (giving grade 2 instead of 3).
Figure 7. Box-and-whisker plots of errors by image for F.A., comparing each landmark to the centroid of the other annotators and taking the median across each image.
Median errors for each observer across all points.Figure 5. Mean point-wise errors for all observers.
Median errors for each observer across all points.

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Accuracy of Using a New Semi-Automated Software Package to Diagnose Osteoporotic Vertebral Fractures in Adults
  • Article
  • Full-text available

February 2023

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66 Reads

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1 Citation

Electronics

We evaluate the accuracy of a semi-automated software package for annotating landmark points on vertebral body outlines in dual-energy X-ray absorptiometry (DXA) images of adults. The aim of the study was to determine the accuracy with which a non-expert radiographer could use the software to annotate vertebrae in support of osteoporotic vertebral fracture diagnosis and grading. In this study, 71 GE Lunar iDXA vertebral fracture assessment (VFA) images were used. Annotations of landmark points on vertebral body outlines were performed by four observers. Annotations consisted of 33 points on each vertebra between T4 and L4 inclusive; 11 on the upper end-plate, 8 on the anterior side, 11 on the lower end-plate, and 3 on the pedicle (429 points for each image). There were a total of 19 (26%) cases in which the non-expert radiographer made vertebral level assignment errors. All of them were one level too high (with L1 identified as T12). Their median error for landmark annotation was 1.05 mm, comparable to the 0.8 mm error achieved by the expert radiographers. Normative mean vertebral body heights vary between approximately 22 mm at T4 and 36 mm at L4 in females. Mild, moderate, and severe vertebral fragility fractures are defined through vertebral body height reductions of 20%, 25%, and 40%, respectively. Therefore, the annotation accuracy of the software when used by a non-expert was 14–23% of the height reduction indicative of a mild fracture. We conclude that, even when used by non-experts, the software can annotate vertebral body outlines accurately enough to support vertebral fragility fracture diagnosis and grading.

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Standard care pathway for vertebral fragility fracture (VFF) identification in current practice
Understanding current UK practice for the incidental identification of vertebral fragility fractures from CT scans: an expert elicitation study

August 2022

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47 Reads

Aging Clinical and Experimental Research

Background There is an emerging interest in using automated approaches to enable the incidental identification of vertebral fragility fractures (VFFs) on existing medical images visualising the spine. Aim To quantify values, and the degree of uncertainty associated with them, for the incidental identification of VFFs from computed tomography (CT) scans in current practice. Methods An expert elicitation exercise was conducted to generate point estimates and measures of uncertainty for four values representing the probability of: VFF being correctly reported by the radiologist; the absence of VFF being correctly assessed by the radiologist; being referred for management when a VFF is identified; having a dual-energy X-ray absorptiometry (DXA) scan after general practitioner (GP) referral. Data from a sample of seven experts in the diagnosis and management of people with VFFs were pooled using mathematical aggregation. Results The estimated mean values for each probability parameter were: VFF being correctly reported by the radiologist = 0.25 (standard deviation (SD): 0.21); absence of VFF being correctly assessed by the radiologist = 0.89 (0.10); being referred for management when a VFF is identified by the radiologist = 0.15 (0.12); having a DXA scan after GP referral = 0.66 (0.28). Discussion These estimates could be used to facilitate the subsequent early economic evaluation of potential new approaches to improve the health outcomes of people with VFFs. Conclusion In the absence of epidemiological studies, this study produced point estimates and measures of uncertainty for key parameters needed to describe current pathways for the incidental diagnosis of VFFs.


Educating the Healthcare Workforce to Support Digital Transformation

June 2022

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94 Reads

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5 Citations

Digital transformation of the healthcare workforce is a priority if we are to leverage the potential of digital technologies, artificial intelligence in clinical decision support and the potential of data captured within electronic health records. Educational programmes need to be diverse and support the digital novices through to the champions whom will be responsible for procuring and implementing digital solutions. In order to professionalise the workforce in this area, digital competencies need to be built into training from early on and be underpinned by frameworks that help to guide regulators and professional bodies and support educational providers to deliver them. Here we describe Manchester’s involvement in the development of digital competency frameworks and our digital transformation education programmes that we have created, including a Massive Online Open Course and a professional development course for England’s Topol Digital Fellows.



Sub-categories of digital health.
Source: Adapted from Deloitte UK (2015). 15
Example of osteoporosis mHealth app.
Free apps through search on app store (Apple, California, USA).
Digital health interventions for osteoporosis and post-fragility fracture care

March 2022

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189 Reads

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14 Citations

The growing burden from osteoporosis and fragility fractures highlights a need to improve osteoporosis management across healthcare systems. Sub-optimal management of osteoporosis is an area suitable for digital health interventions. While fracture liaison services (FLSs) are proven to greatly improve care for people with osteoporosis, such services might benefit from technologies that enhance automation. The term ‘Digital Health’ covers a variety of different tools including clinical decision support systems, electronic medical record tools, patient decision aids, patient apps, education tools, and novel artificial intelligence (AI) algorithms. Within the scope of this review are AI solutions that use algorithms within health system registries to target interventions. Clinician-targeted, patient-targeted, or system-targeted digital health interventions could be used to improve management and prevent fragility fractures. This review was commissioned by The Royal Osteoporosis Society and Bone Research Academy during the production of the 2020 Research Roadmap ( https://theros.org.uk ), with the intention of identifying gaps where targeted research funding could lead to improved patient health. We explore potential uses of digital technology in the general management of osteoporosis. Evidence suggests that digital technologies can support multidisciplinary teams to provide the best possible patient care based on current evidence and to support patients in self-management. However, robust randomised controlled studies are still needed to assess the effectiveness and cost-effectiveness of these technologies.


Citations (58)


... Prevalence data for sarcopenia were available in 37 [53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69] of 39 included studies (n = 8754), generating a pooled prevalence of 0.42 (95% CI 0.36-0.48, p < 0.001) ( Figure S1). ...

Reference:

Sarcopenia Is a Prognostic Factor of Adverse Effects and Mortality in Patients With Tumour: A Systematic Review and Meta‐Analysis
Low muscle mass measured at T12 is a prognostic biomarker in unresectable oesophageal cancers receiving chemoradiotherapy
  • Citing Article
  • June 2023

Radiotherapy and Oncology

... The output was more accurate than the existing method but the computational cost of the process was higher. In 2023, Alqahtani et al. [34] experimented with using semi-automated software to point out the outline of the vertebral body through DXA images. Initially, the images were drawn. ...

Accuracy of Using a New Semi-Automated Software Package to Diagnose Osteoporotic Vertebral Fractures in Adults

Electronics

... Part of the challenges faced by the rehabilitation sector include the lack of technical knowledge, capacities, and didactical competencies in the application of digital rehabilitation (Longhini et al, 2022;Mikkonen et al, 2018). One of the main identified challenges in the adaption of new digital opportunities, was the access to relevant and evidence-based knowledge of which solutions to use to include digital rehabilitation into the scope of services provided (Davies et al, 2022;Redecker et al, 2017). Another identified challenge was the general competence and capability of rehabilitation workforce to design use cases, with the users, for the existing digital solutions and for the different emerging technologies (Jarva et al, 2022;Seeman et al, 2023). ...

Educating the Healthcare Workforce to Support Digital Transformation

... Accurate assessment of fracture risk is crucial in targeted interventions to prevent fractures. As reviewed elsewhere, risk estimation tools are available for use by patients themselves or by health professionals [9,10]. Obtaining risk factor information directly from patients is critical in tools such as FRAX®, but self-reported health information can be subjected to bias or simply unavailable due to unknown family history [11,12]. ...

Digital health interventions for osteoporosis and post-fragility fracture care

... These biomarkers can be used for the diagnosis of muscle pathologies, such as muscular dystrophy 13 , cachexia 14 , and sarcopenia 15 . The models were tested on the rotator cuff 8 , chest 3 , hip and thigh 7 , and abdominal muscles 1,2,4,9,10,16,17 . However, multiple issues exist in those studies that limit the reliable application in large-scale databases. ...

Transfer learning for data‐efficient abdominal muscle segmentation with convolutional neural networks

... The scientific rationale of detecting and improving the strategy of addressing the osteoporotic fractures in the general population (and in type 2 diabetic individuals in particular) comes from a major burden that may be reflected by impressive data: the mortality within the first year following a hip fracture may rise to 25% while disability and dysfunctionality might affect up to 60% of affected persons following this type of fracture; the projections of osteoporotic fractures as increasing numbers of patients involve both females and males; a call for action has been released by World Health Organization to address the issue of fragility fractures and osteoporosis detection due to the associated burden; remaining lifetime probability of suffering from a fracture is one out of three females and one out of five men aged over 50 in Europe and, respectively, one out of two and one out of four in the US; the number and costs of hospitalizations due to fractures surpasses those related to cardiovascular events; the panel of osteoporosis-associated disability represents a heterogeneous spectrum that is also reflected by the aggravation of other co-morbidities, increased costs, and an overall impaired quality of life. On the other hand, only 2 out of 10 patients with osteoporosis are recognized with this diagnosis, and only 3 out of 10 subjects with an osteoporotic fracture who should receive specific anti-osteoporotic medication are actually treated for this condition in order to reduce the increased fracture risk, while almost half of the patients that start this medication will no longer be compliant after the first year since drug initiation [20][21][22][23][24][25][26]. ...

Towards a cure for osteoporosis: the UK Royal Osteoporosis Society (ROS) Osteoporosis Research Roadmap

Archives of Osteoporosis

... A total of 54% (15/28) of the enablers were shared findings between the previous reviews and this study. Within the scope of the 3-horizon framework [15], most included studies in this paper (22/26, 85%) indicated that the process domain facilitated the development of AI analytics within horizon 2 [20,30,31,[33][34][35][36][37][38][39][40][41][42][43][44]47,48,[50][51][52][53][54]. Co-design with clinicians was the most commonly reported enabler in 46% (12/26) of the papers in horizon 2 [30,31,33,35,[39][40][41]43,44,[52][53][54]. ...

Artificial intelligence projects in healthcare: 10 practical tips for success in a clinical environment

... It has been shown that more than 80% of patients having a severe vertebral fracture do not have a previous assessment of their BMD [28]. Thus, the interest in using routinely acquired imaging studies such as CT scans as an opportunistic tool to measure BMD has increased [24]. ...

Opportunistic diagnosis of osteoporosis, fragile bone strength and vertebral fractures from routine CT scans; a review of approved technology systems and pathways to implementation

... One way to improve both vertebral fracture identification and the diagnosis of osteoporosis is to assess a patient's spine or hips during routine computed tomography (CT) scans [28], an approach that is enthusing clinicians, software engineers, and patients alike. Patients attend routine CT for diagnosis and monitoring of various medical conditions, but the skeleton can be overlooked as radiologists concentrate on the primary reason for scanning. ...

Computer‐Aided Diagnostic Systems for Osteoporotic Vertebral Fracture Detection: Opportunities and Challenges

Journal of bone and mineral research: the official journal of the American Society for Bone and Mineral Research

... Modern DXA scanners usually provide the treating team with data for both the lumbar spine and total body-hip scans are less reliable in children due to the evolving anatomy of the region and the difficulties of repositioning. In addition, lateral spine images can be obtained, allowing the assessment of changes in the shape of crush-fractured vertebrae with lower doses of radiation than conventional plain radiography [32,33]. Lateral vertebral scans using DXA are particularly useful for assessing the upper thoracic vertebrae, which are often less well visualised on plain radiographs. ...

Diagnostic performance of morphometric vertebral fracture analysis (MXA) in children using a 33-point software program
  • Citing Article
  • January 2020

Bone