Impact of the COVID-19 pandemic on radiography practice: findings from a UK radiography workforce survey.

OBJECTIVES: Radiographers are key patient-facing healthcare professionals involved in many aspects of patient care. The working patterns and professional practice of the radiography workforce (RW) has been altered during the COVID-19 pandemic. This survey aimed to assess the impact of the pandemic on radiography practice in the United Kingdom (UK). METHODS: An online cross-sectional survey of the UK RW was performed (March 25th to April 26th, 2020). The survey sought information regarding 1. Demographics 2. Impact of the pandemic on professional practice 3. Infection prevention/control and 4. COVID-19 related stress. Data collected was analysed using the Statistical Package for Social Sciences (v.26). RESULTS: A total of 522 responses were received, comprising n = 412 (78.9%) diagnostic and n = 110 (21.1%) therapeutic RW categories from across the UK. 12.5% (65/522) of the respondents were redeployed. Redeployment did not appear to contribute (p = 0.31) to work-related stress. However, fear of contracting the infection and perceived inadequate personal protective equipment (PPE) were identified as key contributors to stress during the study period. Compared to the therapeutic RW, a significantly higher proportion of the diagnostic RW identified fear of being infected as a major stressor (166/412 (40.3%) vs 30/110 (27.3%), p = 0.01). CONCLUSION: This survey has demonstrated changes to clinical practice, in particular to working patterns, service delivery and infection prevention and control were key contributors to workplace-related stress during the pandemic. ADVANCES IN KNOWLEDGE: Timely and adequate staff training and availability of PPE as well as psychosocial support during future pandemics would enhance quality patient and staff safety.

Tumour subregion analysis of colorectal liver metastases using semi-automated clustering based on DCE-MRI: Comparison with histological subregions and impact on pharmacokinetic parameter analysis.

PURPOSE: To use a novel segmentation methodology based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to define tumour subregions of liver metastases from colorectal cancer (CRC), to compare these with histology, and to use these to compare extracted pharmacokinetic (PK) parameters between tumour subregions. MATERIALS AND METHODS: This ethically-approved prospective study recruited patients with CRC and ≥1 hepatic metastases scheduled for hepatic resection. Patients underwent DCE-MRI pre-metastasectomy. Histological sections of resection specimens were spatially matched to DCE-MRI acquisitions and used to define histological subregions of viable and non-viable tumour. A semi-automated voxel-wise image segmentation algorithm based on the DCE-MRI contrast-uptake curves was used to define imaging subregions of viable and non-viable tumour. Overlap of histologically-defined and imaging subregions was compared using the Dice similarity coefficient (DSC). DCE-MRI PK parameters were compared for the whole tumour and histology-defined and imaging-derived subregions. RESULTS: Fourteen patients were included in the analysis. Direct histological comparison with imaging was possible in nine patients. Mean DSC for viable tumour subregions defined by imaging and histology was 0.738 (range 0.540-0.930). There were significant differences between Ktrans and kep for viable and non-viable subregions (p < 0.001) and between whole lesions and viable subregions (p < 0.001). CONCLUSION: We demonstrate good concordance of viable tumour segmentation based on pre-operative DCE-MRI with a post-operative histological gold-standard. This can be used to extract viable tumour-specific values from quantitative image analysis, and could improve treatment response assessment in clinical practice.

GIFTed Demons: deformable image registration with local structure-preserving regularization using supervoxels for liver applications.

Deformable image registration, a key component of motion correction in medical imaging, needs to be efficient and provides plausible spatial transformations that reliably approximate biological aspects of complex human organ motion. Standard approaches, such as Demons registration, mostly use Gaussian regularization for organ motion, which, though computationally efficient, rule out their application to intrinsically more complex organ motions, such as sliding interfaces. We propose regularization of motion based on supervoxels, which provides an integrated discontinuity preserving prior for motions, such as sliding. More precisely, we replace Gaussian smoothing by fast, structure-preserving, guided filtering to provide efficient, locally adaptive regularization of the estimated displacement field. We illustrate the approach by applying it to estimate sliding motions at lung and liver interfaces on challenging four-dimensional computed tomography (CT) and dynamic contrast-enhanced magnetic resonance imaging datasets. The results show that guided filter-based regularization improves the accuracy of lung and liver motion correction as compared to Gaussian smoothing. Furthermore, our framework achieves state-of-the-art results on a publicly available CT liver dataset.

Predicting Pathologic Response of Esophageal Cancer to Neoadjuvant Chemotherapy: The Implications of Metabolic Nodal Response for Personalized Therapy.

Only a minority of esophageal cancers demonstrates a pathologic tumor response (pTR) to neoadjuvant chemotherapy (NAC). 18F-FDG PET/CT is often used for restaging after NAC and to assess response. Increasingly, it is used during therapy to identify unresponsive tumors and predict pTR, using avidity of the primary tumor alone. However, definitions of such metabolic tumor response (mTR) vary. We aimed to comprehensively reevaluate metabolic response assessment using accepted parameters, as well as novel concepts of metabolic nodal stage (mN) and metabolic nodal response (mNR). METHODS: This was a single-center retrospective U.K. cohort study. All patients with esophageal cancer staged before NAC with PET/CT and after with CT or PET/CT and undergoing resection from 2006 to 2014 were identified. pTR was defined as Mandard tumor regression grade 1-3; imaging parameters included metrics of tumor avidity (SUVmax/mean/peak), composites of avidity and volume (including metabolic tumor volume), nodal SUVmax, and our new concepts of mN stage and mNR. RESULTS: Eighty-two (27.2%) of 301 patients demonstrated pTR. No pre-NAC PET parameters predicted pTR. In 220 patients restaged by PET/CT, the optimal tumor ΔSUVmax threshold was a 77.8% reduction. This was as sensitive as the current PERCIST 30% reduction, but more specific with a higher negative predictive value (P < 0.001). ΔSUVmax and Δlength independently predicted pTR, and composite avidity/spatial metrics outperformed avidity alone. Although both mTR and mNR were associated with pTR, in 82 patients with 18F-FDG-avid nodes before NAC we observed mNR in 10 (12.2%) not demonstrating mTR. CONCLUSION: Current definitions of metabolic response are suboptimal and too simplistic. Composite avidity/volume measures improve prediction. mNR may further improve response assessment, by specifically assessing metastatic tumor subpopulations, likely responsible for disease relapse, and should be urgently assessed when considering aborting therapy on the basis of mTR alone.

Imaging oligometastatic cancer before local treatment.

With the advent of novel treatment strategies to help widen the therapeutic window for patients with oligometastatic cancer, improved biomarkers are needed to reliably define patients who can benefit from these treatments. Multimodal imaging is one such option and should be optimised to comprehensively assess metastatic sites, disease burden, and response to neoadjuvant treatment in each disease setting. These features will probably remain important prognostic biomarkers, and are crucial in planning multidisciplinary treatment. There are opportunities to extract additional phenotypic information from conventional imaging, while novel imaging techniques can also reveal specific aspects of tumour biology. Imaging can both characterise and localise the phenotypic heterogeneity of multiple tumour sites. Novel approaches to existing imaging datasets and correlation with tumour biology will be important in realising the potential of imaging to guide treatment in the oligometastatic setting. In this Personal View, we discuss the current status and future directions of imaging before treatment in patients with extracranial oligometastases.

Pieces-of-parts for supervoxel segmentation with global context: Application to DCE-MRI tumour delineation.

Rectal tumour segmentation in dynamic contrast-enhanced MRI (DCE-MRI) is a challenging task, and an automated and consistent method would be highly desirable to improve the modelling and prediction of patient outcomes from tissue contrast enhancement characteristics - particularly in routine clinical practice. A framework is developed to automate DCE-MRI tumour segmentation, by introducing: perfusion-supervoxels to over-segment and classify DCE-MRI volumes using the dynamic contrast enhancement characteristics; and the pieces-of-parts graphical model, which adds global (anatomic) constraints that further refine the supervoxel components that comprise the tumour. The framework was evaluated on 23 DCE-MRI scans of patients with rectal adenocarcinomas, and achieved a voxelwise area-under the receiver operating characteristic curve (AUC) of 0.97 compared to expert delineations. Creating a binary tumour segmentation, 21 of the 23 cases were segmented correctly with a median Dice similarity coefficient (DSC) of 0.63, which is close to the inter-rater variability of this challenging task. A second study is also included to demonstrate the method's generalisability and achieved a DSC of 0.71. The framework achieves promising results for the underexplored area of rectal tumour segmentation in DCE-MRI, and the methods have potential to be applied to other DCE-MRI and supervoxel segmentation problems.

Restaging oesophageal cancer after neoadjuvant therapy with (18)F-FDG PET-CT: identifying interval metastases and predicting incurable disease at surgery.

OBJECTIVES: It is unknown whether restaging oesophageal cancer after neoadjuvant therapy with positron emission tomography-computed tomography (PET-CT) is more sensitive than contrast-enhanced CT for disease progression. We aimed to determine this and stratify risk. METHODS: This was a retrospective study of patients staged before neoadjuvant chemotherapy (NAC) by (18)F-FDG PET-CT and restaged with CT or PET-CT in a single centre (2006-2014). RESULTS: Three hundred and eighty-three patients were restaged (103 CT, 280 PET-CT). Incurable disease was detected by CT in 3 (2.91 %) and PET-CT in 17 (6.07 %). Despite restaging unsuspected incurable disease was encountered at surgery in 34/336 patients (10.1 %). PET-CT was more sensitive than CT (p = 0.005, McNemar's test). A new classification of FDG-avid nodal stage (mN) before NAC (plus tumour FDG-avid length) predicted subsequent progression, independent of conventional nodal stage. The presence of FDG-avid nodes after NAC and an impassable tumour stratified risk of incurable disease at surgery into high (75.0 %; both risk factors), medium (22.4 %; either), and low risk (3.87 %; neither) groups (p < 0.001). Decision theory supported restaging PET-CT. CONCLUSIONS: PET-CT is more sensitive than CT for detecting interval progression; however, it is insufficient in at least higher risk patients. mN stage and response (mNR) plus primary tumour characteristics can stratify this risk simply. KEY POINTS: • Restaging (18) F-FDG-PET-CT after neoadjuvant chemotherapy identifies metastases in 6 % of patients • Restaging (18) F-FDG-PET-CT is more sensitive than CT for detecting interval progression • Despite this, at surgery 10 % of patients had unsuspected incurable disease • New concepts (FDG-avid nodal stage and response) plus tumour impassability stratify risk • Higher risk (if not all) patients may benefit from additional restaging modalities.

Does a novel penalized likelihood reconstruction of 18F-FDG PET-CT improve signal-to-background in colorectal liver metastases?

PURPOSE: Iterative reconstruction algorithms are widely used to reconstruct positron emission tomography computerised tomography (PET/CT) data. Lesion detection in the liver by 18F-fluorodeoxyglucose PET/CT (18F-FDG-PET/CT) is hindered by 18F-FDG uptake in background liver parenchyma. The aim of this study was to compare semi-quantitative parameters of histologically-proven colorectal liver metastases detected by 18F-FDG-PET/CT using data based on a Bayesian penalised likelihood (BPL) reconstruction, with data based on a conventional time-of-flight (ToF) ordered subsets expectation maximisation (OSEM) reconstruction. METHODS: A BPL reconstruction algorithm was used to retrospectively reconstruct sinogram PET data. This data was compared with OSEM reconstructions. A volume of interest was placed within normal background liver parenchyma. Lesions were segmented using automated thresholding. Lesion maximum standardised uptake value (SUVmax), standard deviation of background liver parenchyma SUV, signal-to-background ratio (SBR), and signal-to-noise ratio (SNR) were collated. Data was analysed using paired Student's t-tests and the Pearson correlation. RESULTS: Forty-two liver metastases from twenty-four patients were included in the analysis. The average lesion SUVmax increased from 8.8 to 11.6 (p<0.001) after application of the BPL algorithm, with no significant difference in background noise. SBR increased from 4.0 to 4.9 (p<0.001) and SNR increased from 10.6 to 13.1 (p<0.001) using BPL. There was a statistically significant negative correlation between lesion size and the percentage increase in lesion SUVmax (p=0.03). CONCLUSIONS: This BPL reconstruction algorithm improved SNR and SBR for colorectal liver metastases detected by 18F-FDG-PET/CT, increasing the lesion SUVmax without increasing background liver SUV or image noise. This may improve the detection of FDG-avid focal liver lesions and the diagnostic performance of clinical 18F-FDG-PET/CT in this setting, with the largest impact for small foci.

Clinical trials of interventional oncology-moving from efficacy to outcomes.

Interventional oncology is a rapidly growing sub-speciality that aims to develop new disease-modifying treatment options beyond conventional surgical and oncological therapies in several disease settings. The evidence for interventional oncology success is dominated by single-arm studies reporting technical success or clinical efficacy. These studies have successfully resulted in the development of new techniques, but are not sufficient to change clinical practice uniformly across health-care systems. This Review discusses why clinical investigators must incorporate measures of cost-effectiveness and patient-reported outcomes into large-scale studies currently being designed to provide robust evidence for changing clinical practice. In particular, interventional oncology trials could be designed to show that certain treatments may be as effective as the current standard of care, but with significantly less morbidity and with better outcomes for patients with cancer. Innovative trial design and awareness of the challenges from interventional studies in other fields of medicine and surgery are also discussed to demonstrate how this new speciality can make progress. Registry-based models are emerging as an alternative means of deriving cohort data and can be used in parallel with local or national commissioning of new services.

The clinician's response to a report of an incidental pulmonary embolism detected on multidetector CT.

BACKGROUND: The prevalence of incidental pulmonary emboli (PE) detected on contrast enhanced CT performed for other reasons is approximately 2.5%. The treatment decisions based upon the discovery of incidental PE have been less well reported. The purpose of this study was to report the clinician's response to, and consequences of, the finding of incidental PE on contrast enhanced CT. METHODS: Retrospective cohort study. Patients with incidental PE detected on a contrast enhanced CT were retrospectively identified at a single institution between 1 January 2009 and 31 December 2009. Case note review was performed to assess clinicians' responses to this finding. Patients with synchronous venous thromboembolism, unrecognised symptoms or factors preventing response assessment were excluded from this analysis. Patient and PE characteristics, treatment, and outcomes related to treatment and non-treatment were recorded. RESULTS: There were 73 patients with incidental PE: 52 were in the proximal pulmonary arteries and 21 were distal. 16 patients were excluded from the treatment analysis. 52 of 57 (91.2%) patients were treated with therapeutic anticoagulation. There were 2 (3.8%) serious adverse events related to treatment. 5 (8.8%) patients were not treated; 2 (40%) developed recurrent venous thromboembolism. Treatment of incidental PE was not significantly associated with patient age, PE risk factors or PE location. A smaller proportion of single incidental PE were treated than multiple incidental PE (p=0.047). CONCLUSION: There is morbidity associated with both treatment and non-treatment of incidental PE. However, despite the uncertainty about the natural history and clinical significance of incidental PE, the majority of patients at the authors' institution received prompt anticoagulation.