Towards nationally curated data archives for clinical radiology image analysis at scale: Learnings from national data collection in response to a pandemic

The prevalence of the coronavirus SARS-CoV-2 disease has resulted in the unprecedented collection of health data to support research. Historically, coordinating the collation of such datasets on a national scale has been challenging to execute for several reasons, including issues with data privacy, the lack of data reporting standards, interoperable technologies, and distribution methods. The coronavirus SARS-CoV-2 disease pandemic has highlighted the importance of collaboration between government bodies, healthcare institutions, academic researchers and commercial companies in overcoming these issues during times of urgency. The National COVID-19 Chest Imaging Database, led by NHSX, British Society of Thoracic Imaging, Royal Surrey NHS Foundation Trust and Faculty, is an example of such a national initiative. Here, we summarise the experiences and challenges of setting up the National COVID-19 Chest Imaging Database, and the implications for future ambitions of national data curation in medical imaging to advance the safe adoption of artificial intelligence in healthcare.

International survey on residency programs in radiology: similarities and differences among 17 countries

OBJECTIVE

With the initiative of the ACR International Economics Committee, a multinational survey was conducted to evaluate radiology residency programs around the world.

METHODS

A 31-question survey was developed. It included: economic issues, program size and length, resident's activities during daytime and call, academic aspects including syllabus and examinations. Data was tabulated using the forementioned thematic framework and was qualitatively analyzed.

RESULTS

Responses were received from all 17 countries that were invited to participate (France, Netherlands, Israel, UK, Russia, USA, Japan, India, Germany, Canada, Turkey, Croatia, Serbia, Italy, Ireland, Hungary, and Greece). Residency length varied between 2 and 5 years. The certificate of residency completion is provided by a local hospital [4/17 (23%)], University [6/17 (36%)], National Board [6/17 (36%)], and Ministry of Health [1/17 (6%)]. There was variability among the number of residency programs and residents per program ranging from 15 to 300 programs per nation with a 1-700 residents in each one respectively. Salaries varied significantly and ranged from 8000 to 75,000 USD equivalent. Exams are an integral part of training in all surveyed countries. Length of call varied between 5 and 26 h and the number of monthly calls ranged from 3 to 6. The future of radiology was judged as growing in [12/17 (70%)] countries and stagnant in [5/17 (30%)] countries.

DISCUSSION

Radiology residency programs worldwide have many similarities. The differences are in the structure of the residency programs. Stagnation and uncertainties need to be addressed to ensure the continued development of the next generation of radiologists.

SUMMARY STATEMENT

There are many similarities in the academic aims and approach to education and training of radiology residency programs worldwide. The differences are in the structure of the residency programs and payments to individual residents.

An International Survey of Quality and Safety Programs in Radiology

PURPOSE

The aim of this study was to determine the status of radiology quality improvement programs in a variety of selected nations worldwide.

METHODS

A survey was developed by select members of the International Economics Committee of the American College of Radiology on quality programs and was distributed to committee members. Members responded on behalf of their country. The 51-question survey asked about 12 different quality initiatives which were grouped into 4 themes: departments, users, equipment, and outcomes. Respondents reported whether a designated type of quality initiative was used in their country and answered subsequent questions further characterizing it.

RESULTS

The response rate was 100% and represented Australia, Canada, China, England, France, Germany, India, Israel, Japan, the Netherlands, Russia, and the United States. The most frequently reported quality initiatives were imaging appropriateness (91.7%) and disease registries (91.7%), followed by key performance indicators (83.3%) and morbidity and mortality rounds (83.3%). Peer review, equipment accreditation, radiation dose monitoring, and structured reporting were reported by 75.0% of respondents, followed by 58.3% of respondents for quality audits and critical incident reporting. The least frequently reported initiatives included Lean/Kaizen exercises and physician performance assessments, implemented by 25.0% of respondents.

CONCLUSION

There is considerable diversity in the quality programs used throughout the world, despite some influence by national and international organizations, from whom further guidance could increase uniformity and optimize patient care in radiology.

Breast ultrasound region of interest detection and lesion localisation

In current breast ultrasound computer aided diagnosis systems, the radiologist preselects a region of interest (ROI) as an input for computerised breast ultrasound image analysis. This task is time consuming and there is inconsistency among human experts. Researchers attempting to automate the process of obtaining the ROIs have been relying on image processing and conventional machine learning methods. We propose the use of a deep learning method for breast ultrasound ROI detection and lesion localisation. We use the most accurate object detection deep learning framework - Faster-RCNN with Inception-ResNet-v2 - as our deep learning network. Due to the lack of datasets, we use transfer learning and propose a new 3-channel artificial RGB method to improve the overall performance. We evaluate and compare the performance of our proposed methods on two datasets (namely, Dataset A and Dataset B), i.e. within individual datasets and composite dataset. We report the lesion detection results with two types of analysis: (1) detected point (centre of the segmented region or the detected bounding box) and (2) Intersection over Union (IoU). Our results demonstrate that the proposed methods achieved comparable results on detected point but with notable improvement on IoU. In addition, our proposed 3-channel artificial RGB method improves the recall of Dataset A. Finally, we outline some future directions for the research.

Breast ultrasound lesions recognition: end-to-end deep learning approaches

Multistage processing of automated breast ultrasound lesions recognition is dependent on the performance of prior stages. To improve the current state of the art, we propose the use of end-to-end deep learning approaches using fully convolutional networks (FCNs), namely FCN-AlexNet, FCN-32s, FCN-16s, and FCN-8s for semantic segmentation of breast lesions. We use pretrained models based on ImageNet and transfer learning to overcome the issue of data deficiency. We evaluate our results on two datasets, which consist of a total of 113 malignant and 356 benign lesions. To assess the performance, we conduct fivefold cross validation using the following split: 70% for training data, 10% for validation data, and 20% testing data. The results showed that our proposed method performed better on benign lesions, with a top "mean Dice" score of 0.7626 with FCN-16s, when compared with the malignant lesions with a top mean Dice score of 0.5484 with FCN-8s. When considering the number of images with Dice score > 0.5 , 89.6% of the benign lesions were successfully segmented and correctly recognised, whereas 60.6% of the malignant lesions were successfully segmented and correctly recognized. We conclude the paper by addressing the future challenges of the work.

Tackling Climate Change Close to Home: Mobile Breast Screening as a Model

Objective

Health services contribute significantly to carbon dioxide (CO2) emissions and, while services in the UK are beginning to address this, the focus has been on reducing energy consumption rather than road transport, a major component of emissions. We aimed to compare the distances travelled by patients attending mobile breast screening clinics compared to the distance they would need to travel if screening services were centralized.

Methods

Anonymized postcode records were analysed to determine driving distances potentially saved through attendance at 20 mobile breast screening clinics rather than at two centralized locations. Based on assumptions for the typical car used, the CO2 emissions were calculated for the current case of decentralized service through mobile clinics compared to a hypothetical case where only centralized services are available over one complete three-year cycle of breast screening invitations.

Results

The availability of mobile breast screening clinics for the 60,675 women who underwent screening over a three-year cycle led to a return journey distance savings of 1,429,908 km. Taking into account the CO2 emissions of the tractor unit used for moving the mobile clinics around, this equates to approximately 75 tonnes of CO2 saved in any one year.

Conclusions

Decentralizing health care delivery can potentially provide substantial reductions in emissions at the same time as improving the patient experience. Thus, the ‘care close to home’ agenda can simultaneously improve health outcomes and the environment.

Linking the Diagnostic Imaging Dataset (DID) to Hospital Episode Statistics (HES) – improving and understanding the diagnosis of lung cancer

ABSTRACT ObjectivesTo link the Diagnostic Imaging Dataset (DID) to Hospital Episode Statistics (HES) to explore the association between patient imaging and hospital based care and outcomes for cancer patients in English NHS hospitals. This is the first time this linkage has taken place. The analysis also aims to look at how each patient first presented in HES (A&E, emergency admission, elective care, regular attendance), when and by what route relevant tests were requested and geographic variation in access to imaging ApproachPatient imaging records from the DID were linked to HES databases containing details of all inpatient, outpatient and A&E admissions at NHS hospitals in England in 2012/13 and 2013/14. Match rank criteria were developed to ensure that patients in HES were accurately linked to patients in DID by NHS number, date of birth and other unique identifiers. We used HES to identify patients with a lung cancer diagnosis and investigate their use of imaging and the temporal nature of tests to evaluate whether patients were following recommended pathways (e.g. having chest x-rays followed by CT scans before their lung cancer diagnosis) and the time between these events. Lung cancer patients were identified by developing an algorithm to search through diagnostic fields for clinical codes within HES databases. Where there was a lung cancer code the record was flagged and subsequently extracted. ResultsThe combined HES and DID datasets consisted of more than 340 million records. Within this large dataset we identified 49,888 patients with a lung cancer code in one of their HES diagnosis fields to a DID diagnostic image record for inpatient records alone. A high proportion (97%) of records were matched in one of the top 3 rank levels, suggesting the linkage was successful. The results illustrate the relationship between the imaging referral pathway and hospital episodes (e.g. surgical resection, emergency presentation). ConclusionInvestigating how people engage with imaging services and hospital care will increase our understanding of the pathways associated with lung cancer diagnosis. The results from this analysis will contribute new knowledge about how lung cancer patients interact with hospitals and imaging services.

Breast fat volume measurement using wide-bore 3 T MRI: comparison of traditional mammographic density evaluation with MRI density measurements using automatic segmentation

AIM

To compare magnetic resonance imaging (MRI)-derived breast density measurements using automatic segmentation algorithms with radiologist estimations using the Breast Imaging Reporting and Data Systems (BI-RADS) density classification.

MATERIALS AND METHODS

Forty women undergoing mammography and dynamic breast MRI as part of their clinical management were recruited. Fat-water separated MRI images derived from a two-point Dixon technique, phase-sensitive reconstruction, and atlas-based segmentation were obtained before and after intravenous contrast medium administration. Breast density was assessed using software from Advanced MR Analytics (AMRA), Linköping, Sweden, with results compared to the widely used four-quartile quantitative BI-RADS scale.

RESULTS

The proportion of glandular tissue in the breast on MRI was derived from the AMRA sequence. The mean unenhanced breast density was 0.31±0.22 (mean±SD; left) and 0.29±0.21 (right). Mean breast density on post-contrast images was 0.32±0.19 (left) and 0.32±0.2 (right). There was "almost perfect" correlation between pre- and post-contrast breast density quantification: Spearman's correlation rho=0.98 (95% confidence intervals [CI]: 0.97-0.99; left) and rho=0.99 (95% CI: 0.98-0.99; right). The 95% limits of agreement were -0.11-0.08 (left) and -0.08-0.03 (right). Interobserver reliability for BI-RADS was "substantial": weighted Kappa k=0.8 (95% CI: 0.74-0.87). The Spearman correlation coefficient between BI-RADS and MRI breast density was rho=0.73 (95% CI: 0.60-0.82; left) and rho=0.75 (95% CI: 0.63-0.83; right) which was also "substantial".

CONCLUSION

The AMRA sequence provides a fully automated, reproducible, objective assessment of fibroglandular breast tissue proportion that correlates well with mammographic assessment of breast density with the added advantage of avoidance of ionising radiation.

Impact of errors in recorded compressed breast thickness measurements on volumetric density classification using volpara v1.5.0 software

PURPOSE

Mammographic density has been demonstrated to predict breast cancer risk. It has been proposed that it could be used for stratifying screening pathways and recommending additional imaging. Volumetric density tools use the recorded compressed breast thickness (CBT) of the breast measured at the x-ray unit in their calculation; however, the accuracy of the recorded thickness can vary. The aim of this study was to investigate whether inaccuracies in recorded CBT impact upon volumetric density classification and to examine whether the current quality control (QC) standard is sufficient for assessing mammographic density.

METHODS

Raw data from 52 digital screening mammograms were included in the study. For each image, the clinically recorded CBT was artificially increased and decreased in increments of 1 mm to simulate measurement error, until ±15% from the recorded CBT was reached. New images were created for each 1 mm step in thickness resulting in a total of 974 images which then had volpara density grade (VDG) and volumetric density percentage assigned.

RESULTS

A change in VDG was observed in 38.5% (n = 20) of mammograms when applying ±15% error to the recorded CBT and 11.5% (n = 6) was within the QC standard prescribed error of ±5 mm.

CONCLUSIONS

The current QC standard of ±5 mm error in recorded CBT creates the potential for error in mammographic density measurement. This may lead to inaccurate classification of mammographic density. The current QC standard for assessing mammographic density should be reconsidered.

Breast cancer screening and diagnosis in the 21st century within the U.K

In the UK, breast cancer represents the most commonly diagnosed cancer in females and carries with it a significant morbidity and mortality. An established national screening programme is in place to identify those with the disease at an early stage in order to optimise treatment and prognosis. This article provides an overview for the non-breast specialist clinician whose practice regularly deals with women who may be the subject of the screening programme. It outlines the diagnostic methods employed in the screening programme, the controversies that have surrounded it and the evolving technologies that will improve detection and diagnostic accuracy.

Pressure and breast thickness in mammography--an exploratory calibration study

OBJECTIVE

To perform a calibration study to provide data to help improve consistency in the pressure that is applied during mammography.

METHODS

Automatic readouts of breast thickness accuracy vary between mammography machines; therefore, one machine was selected for calibration. 250 randomly selected patients were invited to participate; 235 agreed, and 940 compression data sets were recorded (breast thickness, breast density and pressure). Pressure (measured in decanewtons) was increased from 5 daN through 1-daN intervals until the practitioner felt that the pressure was appropriate for imaging; at each pressure increment, breast thickness was recorded.

RESULTS

Graphs were generated and equations derived; second-order polynomial trend lines were applied using the method of least squares. No difference existed between breast densities, but a difference did exist between "small" (15×29 cm) and "medium/large" (18×24/24×30 cm) paddles. Accordingly, data were combined. Graphs show changes in thickness from 5-daN pressure for craniocaudal and mediolateral oblique views for the small and medium/large paddles combined. Graphs were colour coded into three segments indicating high, intermediate and low gradients [≤-2 (light grey); -1.99 to -1 (mid-grey); and ≥-0.99 (dark grey)]. We propose that 13 daN could be an appropriate termination pressure on this mammography machine.

CONCLUSION

Using patient compression data we have calibrated a mammography machine to determine its breast compression characteristics. This calibration data could be used to guide practice to minimise pressure variations between practitioners, thereby improving patient experience and reducing potential variation in image quality.

ADVANCES IN KNOWLEDGE

For the first time, pressure-thickness graphs are now available to help guide mammographers in the application of pressure.

Associations among mammographic density, circulating sex hormones, and polymorphisms in sex hormone metabolism genes in postmenopausal women

Mammographic density and serum sex hormone levels are important risk factors for breast cancer, but their associations with one another are unclear. We studied these phenotypes, together with single nucleotide polymorphisms (SNP) in genes related to sex hormone metabolism, in a cross-sectional study of 1,413 postmenopausal women from the European Prospective Investigation into Cancer and Nutrition-Norfolk. All women were >1 year postmenopausal and had not taken hormone replacement therapy for >3 months before sampling. Serum levels of 7 sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG), androstenedione, 17-OH-progesterone, estrone, and estrone sulfate] and 15 SNPs in the CYP17, CYP19, EDH17B2, SHBG, COMT, and CYP1B1 genes were studied. Mammograms nearest in time to the blood sampling were identified through the national breast screening program and visually assessed by three radiologists using the Boyd six-category and Wolfe four-category scales. We found a weak positive association between mammographic density and SHBG levels (P = 0.09) but no association with any other hormones. None of the SNPs, including those shown previously to be associated with estradiol or SHBG, showed significant associations with density. We conclude that mammographic density is largely independent of postmenopausal steroid hormone levels, indicating that these risk factors have, to a large extent, an independent etiology and suggesting that they may be independent predictors of breast cancer risk.

How predictive is breast arterial calcification of cardiovascular disease and risk factors when found at screening mammography?

OBJECTIVE

The purpose of this study was to examine the relationship between breast arterial calcification (BAC), commonly found on mammography, and cardiovascular disease and its risk factors.

SUBJECTS AND METHODS

The study population, nested within the European Prospective Investigation of Cancer-Norfolk (EPIC-Norfolk) cohort study, consisted of 1,590 women older than 55 years, not taking hormone replacement therapy, and with available screening mammograms. Mammograms were coded by three radiologists for presence or absence of BAC. History of coronary heart disease (CHD), stroke, and diabetes and risk factors for cardiovascular disease (including smoking status, body mass index [BMI], blood pressure, diabetes, and glycosylated hemoglobin [HbA1c]) were independently measured from health examinations in the EPIC study.

RESULTS

The prevalence of BAC was 16.0%. Women with BAC were significantly older than those without it. BAC was associated with prevalent CHD, but not stroke. The odds ratio of having CHD was 2.54 (95% confidence interval, 1.03-6.30). The sensitivity and specificity were 32.4% and 85.5%, respectively. Except for smoking, which showed an inverse association, there was no consistent significant association of BAC with cardiovascular disease risk factors including BMI, diabetes, HbA1c, or lipids.

CONCLUSION

BAC found on mammograms was associated with prevalent CHD after adjustment for age, but with low sensitivity. BAC may provide additional information toward identifying cardiovascular disease risk among otherwise healthy women.

Cystic kidney disease presenting in infancy

AIM

The clinical, histological and imaging findings of 12 children with ultrasound features of severe renal cystic disease presenting in the first year of life were reviewed.

METHODS AND RESULTS

Two children had cystic dysplasia and four had autosomal dominant polycystic disease. Two had a malformation syndrome, one a variant of Meckel syndrome and the other Bardet Biedl syndrome. One had autosomal recessive polycystic disease and in three there was no final diagnosis. Intravenous urography gave non-specific information. In six cases clinical findings combined with imaging established a diagnosis. Diagnosis was established by biopsy in two and gave supportive evidence in one. Outlook for renal function is variable. One child has had a transplant and one is on dialysis awaiting a transplant. Three have a degree of renal failure and one has died. Six have normal renal function. Renal cystic disease is the common pathway for a heterogeneous group of disorders as shown in these children.

CONCLUSION

It is emphasized that a specific diagnosis could not be made from the renal sonographic appearances alone, nor could any prognostic implications for renal function be made. Contrast retention on intravenous urography was also insufficiently specific to be of value. Ultrasound of the parents was the most useful imaging procedure and should be done in all cases.