183 results found
© 2019, The Author(s). This Strategic Research Agenda identifies current challenges and needs in healthcare, illustrates how biomedical imaging and derived data can help to address these, and aims to stimulate dedicated research funding efforts. Medicine is currently moving towards a more tailored, patient-centric approach by providing personalised solutions for the individual patient. Innovation in biomedical imaging plays a key role in this process as it addresses the current needs for individualised prevention, treatment, therapy response monitoring, and image-guided surgery. The use of non-invasive biomarkers facilitates better therapy prediction and monitoring, leading to improved patient outcomes. Innovative diagnostic imaging technologies provide information about disease characteristics which, coupled with biological, genetic and -omics data, will contribute to an individualised diagnosis and therapy approach. In the emerging field of theranostics, imaging tools together with therapeutic agents enable the selection of best treatments and allow tailored therapeutic interventions. For prenatal monitoring, the use of innovative imaging technologies can ensure an early detection of malfunctions or disease. The application of biomedical imaging for diagnosis and management of lifestyle-induced diseases will help to avoid disease development through lifestyle changes. Artificial intelligence and machine learning in imaging will facilitate the improvement of image interpretation and lead to better disease prediction and therapy planning. As biomedical imaging technologies and analysis of existing imaging data provide solutions to current challenges and needs in healthcare, appropriate funding for dedicated research is needed to implement the innovative approaches for the wellbeing of citizens and patients.
Lai AYT, Riddell A, Barwick T, et al., 2019, Interobserver agreement of whole-body magnetic resonance imaging is superior to whole-body computed tomography for assessing disease burden in patients with multiple myeloma., Eur Radiol
OBJECTIVES: Whole-body MRI (WB-MRI) is recommended by the International Myeloma Working Group for all patients with asymptomatic myeloma and solitary plasmacytoma and by the UK NICE guidance for all patients with suspected myeloma. Some centres unable to offer WB-MRI offer low-dose whole-body CT (WB-CT). There are no studies comparing interobserver agreement and disease detection of contemporary WB-MRI (anatomical imaging and DWI) versus WB-CT. Our primary aim is to compare the interobserver agreement between WB-CT and WB-MRI in the diagnosis of myeloma. METHODS: Consecutive patients with newly diagnosed myeloma imaged with WB-MRI and WB-CT were prospectively reviewed. For each body region and modality, two experienced and two junior radiologists scored disease burden with final scores by consensus. Intraclass correlation coefficients (ICC), median scores, Wilcoxon signed-rank test and Spearman's correlation coefficients were calculated. RESULTS: There was no significant difference in overall observer scores between WB-MRI and WB-CT (p = 0.87). For experienced observers, interobserver agreement for WB-MRI was superior to WB-CT overall and for each region, without overlap in whole-skeleton confidence intervals (ICC 0.98 versus 0.77, 95%CI 0.96-0.99 versus 0.45-0.91). For inexperienced observers, although there is a trend for a better interobserver score for the whole skeleton on WB-MRI (ICC 0.95, 95%CI 0.72-0.98) than on WB-CT (ICC 0.72, 95%CI 0.34-0.88), the confidence intervals overlap. CONCLUSIONS: WB-MRI offers excellent interobserver agreement which is superior to WB-CT for experienced observers. Although the overall burden was similar across both modalities, patients with lower disease burdens where MRI could be advantageous are not included in this series. KEY POINTS: • Whole-body MRI is recommended by the International Myeloma Working Group for patients with multiple myeloma and solitary plasmacytoma and by the NICE guidance for those with
Taylor SA, Mallett S, Beare S, et al., 2019, Diagnostic accuracy of whole-body MRI versus standard imaging pathways for metastatic disease in newly diagnosed colorectal cancer: the prospective Streamline C trial, Lancet Gastroenterology and Hepatology, Vol: 4, Pages: 529-537, ISSN: 2468-1253
BACKGROUND: Whole-body MRI (WB-MRI) could be an alternative to multimodality staging of colorectal cancer, but its diagnostic accuracy, effect on staging times, number of tests needed, cost, and effect on treatment decisions are unknown. We aimed to prospectively compare the diagnostic accuracy and efficiency of WB-MRI-based staging pathways with standard pathways in colorectal cancer. METHODS: The Streamline C trial was a prospective, multicentre trial done in 16 hospitals in England. Eligible patients were 18 years or older, with newly diagnosed colorectal cancer. Exclusion criteria were severe systemic disease, pregnancy, contraindications to MRI, or polyp cancer. Patients underwent WB-MRI, the result of which was withheld until standard staging investigations were complete and the first treatment decision made. The multidisciplinary team recorded its treatment decision based on standard investigations, then on the WB-MRI staging pathway (WB-MRI plus additional tests generated), and finally on all tests. The primary outcome was difference in per-patient sensitivity for metastases between standard and WB-MRI staging pathways against a consensus reference standard at 12 months, in the per-protocol population. Secondary outcomes were difference in per-patient specificity for metastatic disease detection between standard and WB-MRI staging pathways, differences in treatment decisions, staging efficiency (time taken, test number, and costs), and per-organ sensitivity and specificity for metastases and per-patient agreement for local T and N stage. This trial is registered with the International Standard Randomised Controlled Trial registry, number ISRCTN43958015, and is complete. FINDINGS: Between March 26, 2013, and Aug 19, 2016, 1020 patients were screened for eligibility. 370 patients were recruited, 299 of whom completed the trial; 68 (23%) had metastasis at baseline. Pathway sensitivity was 67% (95% CI 56 to 78) for WB-MRI and 63% (51 to 74) for standard pathways
Miles A, Taylor SA, Evans REC, et al., 2019, Patient preferences for whole-body MRI or conventional staging pathways in lung and colorectal cancer: a discrete choice experiment, Publisher: SPRINGER, Pages: 3889-3900, ISSN: 0938-7994
Lu H, Arshad M, Thornton A, et al., 2019, A mathematical descriptor of tumour mesoscopic structure from computed tomography images annotates prognostic and molecular phenotypes of epithelial ovarian cancer, Publisher: WILEY, Pages: 89-89, ISSN: 1470-0328
Taylor SA, Mallett S, Ball S, et al., 2019, Diagnostic accuracy of whole-body MRI versus standard imaging pathways for metastatic disease in newly diagnosed non-small-cell lung cancer: The prospective Streamline L trial., Lancet Respiratory Medicine, Vol: 7, Pages: 523-532, ISSN: 2213-2600
BACKGROUND: Whole-body magnetic resonance imaging (WB-MRI) could be an alternative to multi-modality staging of non-small-cell lung cancer (NSCLC), but its diagnostic accuracy, effect on staging times, number of tests needed, cost, and effect on treatment decisions are unknown. We aimed to prospectively compare the diagnostic accuracy and efficiency of WB-MRI-based staging pathways with standard pathways in NSCLC. METHODS: The Streamline L trial was a prospective, multicentre trial done in 16 hospitals in England. Eligible patients were 18 years or older, with newly diagnosed NSCLC that was potentially radically treatable on diagnostic chest CT (defined as stage IIIb or less). Exclusion criteria were severe systemic disease, pregnancy, contraindications to MRI, or histologies other than NSCLC. Patients underwent WB-MRI, the result of which was withheld until standard staging investigations were complete and the first treatment decision made. The multidisciplinary team recorded its treatment decision based on standard investigations, then on the WB-MRI staging pathway (WB-MRI plus additional tests generated), and finally on all tests. The primary outcome was difference in per-patient sensitivity for metastases between standard and WB-MRI staging pathways against a consensus reference standard at 12 months, in the per-protocol population. Secondary outcomes were difference in per-patient specificity for metastatic disease detection between standard and WB-MRI staging pathways, differences in treatment decisions, staging efficiency (time taken, test number, and costs) and per-organ sensitivity and specificity for metastases and per-patient agreement for local T and N stage. This trial is registered with the International Standard Randomised Controlled Trial registry, number ISRCTN50436483, and is complete. FINDINGS: Between Feb 26, 2013, and Sept 5, 2016, 976 patients were screened for eligibility. 353 patients were recruited, 187 of whom completed the trial; 52 (28%)
Lavdas I, Glocker B, Rueckert D, et al., 2019, Machine learning in whole-body MRI: experiences and challenges from an applied study using multicentre data, CLINICAL RADIOLOGY, Vol: 74, Pages: 346-356, ISSN: 0009-9260
Lu H, Arshad M, Thornton A, et al., 2019, A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic and molecular-phenotypes of epithelial ovarian cancer, Nature Communications, Vol: 10, ISSN: 2041-1723
The five-year survival rate of epithelial ovarian cancer (EOC) is approximately 35–40% despite maximal treatment efforts, highlighting a need for stratification biomarkers for personalized treatment. Here we extract 657 quantitative mathematical descriptors from the preoperative CT images of 364 EOC patients at their initial presentation. Using machine learning, we derive a non-invasive summary-statistic of the primary ovarian tumor based on 4 descriptors, which we name “Radiomic Prognostic Vector” (RPV). RPV reliably identifies the 5% of patients with median overall survival less than 2 years, significantly improves established prognostic methods, and is validated in two independent, multi-center cohorts. Furthermore, genetic, transcriptomic and proteomic analysis from two independent datasets elucidate that stromal phenotype and DNA damage response pathways are activated in RPV-stratified tumors. RPV and its associated analysis platform could be exploited to guide personalized therapy of EOC and is potentially transferrable to other cancer types.
Arshad MA, Thornton A, Lu H, et al., 2019, Discovery of pre-therapy 2-deoxy-2-F-18-fluoro-D-glucose positron emission tomography-based radiomics classifiers of survival outcome in non-small-cell lung cancer patients, EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, Vol: 46, Pages: 455-466, ISSN: 1619-7070
Nougaret S, Horta M, Sala E, et al., 2019, Endometrial Cancer MRI staging: Updated Guidelines of the European Society of Urogenital Radiology, EUROPEAN RADIOLOGY, Vol: 29, Pages: 792-805, ISSN: 0938-7994
Castellani F, Nganga EC, Dumas L, et al., 2019, Imaging in the pre-operative staging of ovarian cancer, Abdominal Radiology, ISSN: 2366-004X
© 2018, Springer Science+Business Media, LLC, part of Springer Nature. The main prognostic factor in ovarian cancer is the stage of disease at diagnosis. The staging system in use (FIGO classification, updated in 2014) is based on the surgical-pathological findings. Although surgical staging is the gold standard in ovarian cancer, the initial patient management depends on the imaging-based pre-surgical staging assessment, in order to identify unresectable or difficult to resect disease. Radiologists need to be aware of the strengths of the available imaging modalities, as well as the imaging pitfalls. Clear understanding of pattern of disease spread and review areas are critical for accurate staging and treatment planning. The current standard of care for pre-surgical staging is CT of the thorax, abdomen, and pelvis. This allows a rapid evaluation of disease extent and is fairly accurate in identifying bulky disease but has definite limitations in assessing the extent of small volume disease and in the confirmation of certain sites of disease beyond the abdomen. Functional MRI has been reported to be superior in detecting small peritoneal deposits. PET/CT may be used as a problem-solving tool in some patients where determination remains unclear, particularly in confirmation of advanced stage beyond the abdomen.
Davis A, Rockall A, 2019, Acute and chronic pelvic pain disorders, Medical Radiology, Pages: 381-405
© Springer International Publishing AG 2017. This chapter will cover common gynecological and non-gynecological causes of acute and chronic pelvic pain, with particular focus on the differential diagnosis and imaging characteristics. The relative frequency of each diagnosis by MRI or CT is listed in Table 1. Gynecologic disorders highly associated with chronic pelvic pain such as endometriosis, uterine leiomyomas, and adenomyosis are discussed in previous chapters in this book.
Barwick T, Bretsztajn L, Wallitt K, et al., 2019, Imaging in myeloma with focus on advanced imaging techniques., Br J Radiol, Vol: 92, Pages: 20180768-20180768
In recent years, there have been major advances in the imaging of myeloma with whole body MRI incorporating diffusion-weighted imaging, emerging as the most sensitive modality. Imaging is now a key component in the work-up of patients with a suspected diagnosis of myeloma. The International Myeloma Working Group now specifies that more than one focal lesion on MRI or lytic lesion on whole body low-dose CT or fludeoxyglucose (FDG) PET/CT fulfil the criteria for bone damage requiring therapy. The recent National Institute for Health and Care Excellence myeloma guidelines recommend imaging in all patients with suspected myeloma. In addition, there is emerging data supporting the use of functional imaging techniques (WB-DW MRI and FDG PET/CT) to predict outcome and evaluate response to therapy. This review summarises the imaging modalities used in myeloma, the latest guidelines relevant to imaging and future directions.
Alvarez RM, Biliatis I, Rockall A, et al., 2018, MRI measurement of residual cervical length after radical trachelectomy for cervical cancer and the risk of adverse pregnancy outcomes: a blinded imaging analysis, BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY, Vol: 125, Pages: 1726-1733, ISSN: 1470-0328
Kanavati F, Islam S, Aboagye EO, et al., 2018, Automatic L3 slice detection in 3D CT images using fully-convolutional networks, Publisher: arXiv
The analysis of single CT slices extracted at the third lumbar vertebra (L3) has garnered significant clinical interest in the past few years, in particular in regards to quantifying sarcopenia (muscle loss). In this paper, we propose an efficient method to automatically detect the L3 slice in 3D CT images. Our method works with images with a variety of fields of view, occlusions, and slice thicknesses. 3D CT images are first converted into 2D via Maximal Intensity Projection (MIP), reducing the dimensionality of the problem. The MIP images are then used as input to a 2D fully-convolutional network to predict the L3 slice locations in the form of 2D confidence maps. In addition we propose a variant architecture with less parameters allowing 1D confidence map prediction and slightly faster prediction time without loss of accuracy. Quantitative evaluation of our method on a dataset of 1006 3D CT images yields a median error of 1mm, similar to the inter-rater median error of 1mm obtained from two annotators, demonstrating the effectiveness of our method in efficiently and accurately detecting the L3 slice.
Soneji ND, Bharwani N, Ferri A, et al., 2018, Pre-operative MRI staging of endometrial cancer in a multicentre cancer network: can we match single centre study results?, EUROPEAN RADIOLOGY, Vol: 28, Pages: 4725-4734, ISSN: 0938-7994
Patel A, Rockall A, Guthrie A, et al., 2018, Can the completeness of radiological cancer staging reports be improved using proforma reporting? A prospective multicentre non-blinded interventional study across 21 centres in the UK, BMJ Open, Vol: 8, ISSN: 2044-6055
Objectives: Following a diagnosis of cancer, the detailed assessment of prognostic stage by radiology is a crucial determinant of initial therapeutic strategy offered to patients. Pre-therapeutic stage by imaging is known to be inconsistently documented. We tested whether the completeness of cancer staging radiology reports could be improved through a nationally introduced pilot of proforma-based reporting for a selection of six common cancers.Design: Prospective interventional study comparing the completeness of radiology cancer staging reports before and after the introduction of proforma reportingSetting: Twenty-one UK NHS Hospitals Participants: 1283 cancer staging radiology reports were submitted Main Outcome Measures: Radiology staging reports across the six cancers types were evaluated before and after the implementation of proforma based reporting. Report completeness was assessed using scoring forms listing the presence or absence of pre-determined key staging data. Qualitative data regarding proforma implementation and usefulness was collected from questionnaires provided to radiologists and end-users. Results: Electronic proforma based reporting was successfully implemented in 15 of the 21 centres during the evaluation period. A total of 787 pre-proforma and 496 post-proforma staging reports were evaluated. In the pre-proforma group, only 48.7% (5586/11470) of key staging items were present compared with 87.3% (6043/6920) in the post-proforma group. Thus, proforma reporting achieved an absolute improvement in staging completeness of 38.6% (95%CI,0.37-0.40%,p<0.001). An increase was seen across all cancer types and centres. The majority of respondents found proforma reporting improved report quality. Conclusion: The implementation of proforma reporting results in a significant improvement in completeness of cancer staging reports. Proforma based assessment of radiological stage facilitates objective comparison of quality and outcomes. It should be
Blagden SP, Rizzuto I, Suppiah P, et al., 2018, Anti-tumour activity of a first-in-class agent NUC-1031 in patients with advanced cancer: results of a phase I study, British Journal of Cancer, Vol: 119, Pages: 815-822, ISSN: 0007-0920
BackgroundGemcitabine is used to treat a wide range of tumours, but its efficacy is limited by cancer cell resistance mechanisms. NUC-1031, a phosphoramidate modification of gemcitabine, is the first anti-cancer ProTide to enter the clinic and is designed to overcome these key resistance mechanisms.MethodsSixty-eight patients with advanced solid tumours who had relapsed after treatment with standard therapy were recruited to a dose escalation study to determine the recommended Phase II dose (RP2D) and assess the safety of NUC-1031. Pharmacokinetics and anti-tumour activity was also assessed.ResultsSixty-eight patients received treatment, 50% of whom had prior exposure to gemcitabine. NUC-1031 was well tolerated with the most common Grade 3/4 adverse events of neutropaenia, lymphopaenia and fatigue occurring in 13 patients each (19%). In 49 response-evaluable patients, 5 (10%) achieved a partial response and 33 (67%) had stable disease, resulting in a 78% disease control rate. Cmax levels of the active intracellular metabolite, dFdCTP, were 217-times greater than those reported for equimolar doses of gemcitabine, with minimal toxic metabolite accumulation. The RP2D was determined as 825 mg/m2 on days 1, 8 and 15 of a 28-day cycle.ConclusionsNUC-1031 was well tolerated and demonstrated clinically significant anti-tumour activity, even in patients with prior gemcitabine exposure and in cancers not traditionally perceived as gemcitabine-responsive.
Valindria V, Lavdas I, Cerrolaza J, et al., 2018, Small organ segmentation in whole-body MRI using a two-stage FCN and weighting schemes, International Workshop on Machine Learning in Medical Imaging (MLMI) 2018, Publisher: Springer Verlag, Pages: 346-354, ISSN: 0302-9743
Accurate and robust segmentation of small organs in whole-body MRI is difficult due to anatomical variation and class imbalance. Recent deep network based approaches have demonstrated promising performance on abdominal multi-organ segmentations. However, the performance on small organs is still suboptimal as these occupy only small regions of the whole-body volumes with unclear boundaries and variable shapes. A coarse-to-fine, hierarchical strategy is a common approach to alleviate this problem, however, this might miss useful contextual information. We propose a two-stage approach with weighting schemes based on auto-context and spatial atlas priors. Our experiments show that the proposed approach can boost the segmentation accuracy of multiple small organs in whole-body MRI scans.
Lavdas I, Rockall AG, Daulton E, et al., 2018, Histogram analysis of apparent diffusion coefficient from whole-body diffusion-weighted MRI to predict early response to chemotherapy in patients with metastatic colorectal cancer: preliminary results, CLINICAL RADIOLOGY, Vol: 73, ISSN: 0009-9260
Sadowski EA, Rockall AG, Maturen KE, et al., 2018, Adnexal lesions: Imaging strategies for ultrasound and MR imaging, Diagnostic and Interventional Imaging
© 2018 Adnexal lesions are routinely encountered in general practice. Ultrasound is the first line of investigation in determining the benign or malignant potential of an adnexal lesion. In the cases of classic simple cysts, hemorrhagic cysts, endometriomas, dermoids and obviously malignant lesions, ultrasound may be sufficient for management recommendations. In cases where there is an isolated adnexal lesion, without peritoneal disease or serum CA-125 elevation, and in lesions considered indeterminate on ultrasound, MR imaging with incorporation of the ADNEx MR score can increase the specificity for the diagnosis of benignity or malignancy. This article will review the imaging evaluation of adnexal lesions and how to incorporate the ADNEx MR score to help guide clinical management.
Kubik-Huch RA, Weston M, Nougaret S, et al., 2018, European Society of Urogenital Radiology (ESUR) Guidelines: MR Imaging of Leiomyomas, EUROPEAN RADIOLOGY, Vol: 28, Pages: 3125-3137, ISSN: 0938-7994
Valindria VV, Lavdas I, Bai W, et al., 2018, Domain adaptation for MRI organ segmentation using reverse classification accuracy, International Conference on Medical Imaging with Deep Learning (MIDL)
The variations in multi-center data in medical imaging studies have broughtthe necessity of domain adaptation. Despite the advancement of machine learningin automatic segmentation, performance often degrades when algorithms areapplied on new data acquired from different scanners or sequences than thetraining data. Manual annotation is costly and time consuming if it has to becarried out for every new target domain. In this work, we investigate automaticselection of suitable subjects to be annotated for supervised domain adaptationusing the concept of reverse classification accuracy (RCA). RCA predicts theperformance of a trained model on data from the new domain and differentstrategies of selecting subjects to be included in the adaptation via transferlearning are evaluated. We perform experiments on a two-center MR database forthe task of organ segmentation. We show that subject selection via RCA canreduce the burden of annotation of new data for the target domain.
Valindria V, Pawlowski N, Rajchl M, et al., 2018, Multi-modal learning from unpaired images: Application to multi-organ segmentation in CT and MRI, IEEE Winter Conference on Applications of Computer Vision, Publisher: IEEE
Convolutional neural networks have been widely used in medical image segmentation. The amount of training data strongly determines the overall performance. Most approaches are applied for a single imaging modality, e.g., brain MRI. In practice, it is often difficult to acquire sufficient training data of a certain imaging modality. The same anatomical structures, however, may be visible in different modalities such as major organs on abdominal CT and MRI. In this work, we investigate the effectiveness of learning from multiple modalities to improve the segmentation accuracy on each individual modality. We study the feasibility of using a dual-stream encoder-decoder architecture to learn modality-independent, and thus, generalisable and robust features. All of our MRI and CT data are unpaired, which means they are obtained from different subjects and not registered to each other. Experiments show that multi-modal learning can improve overall accuracy over modality-specific training. Results demonstrate that information across modalities can in particular improve performance on varying structures such as the spleen.
Wale A, Wexner SD, Saur NM, et al., 2018, Session 1: The evolution and development of the multidisciplinary team approach: USA, European and UK experiences - what can we do better?, COLORECTAL DISEASE, Vol: 20, Pages: 17-27, ISSN: 1462-8910
Evans REC, Taylor SA, Beare S, et al., 2018, Perceived patient burden and acceptability of whole body MRI for staging lung and colorectal cancer; comparison with standard staging investigations, BRITISH JOURNAL OF RADIOLOGY, Vol: 91, ISSN: 0007-1285
Sadowski EA, Robbins JB, Rockall AG, et al., 2018, A systematic approach to adnexal masses discovered on ultrasound: the ADNEx MR scoring system, Abdominal Radiology, Vol: 43, Pages: 679-695, ISSN: 2366-004X
© 2018, Springer Science+Business Media, LLC. Adnexal lesions are a common occurrence in radiology practice and imaging plays a crucial role in triaging women appropriately. Current trends toward early detection and characterization have increased the need for accurate imaging assessment of adnexal lesions prior to treatment. Ultrasound is the first-line imaging modality for assessing adnexal lesions; however, approximately 20% of lesions are incompletely characterized after ultrasound evaluation. Secondary assessment with MR imaging using the ADNEx MR Scoring System has been demonstrated as highly accurate in the characterization of adnexal lesions and in excluding ovarian cancer. This review will address the role of MR imaging in further assessment of adnexal lesions discovered on US, and the utility of the ADNEx MR Scoring System.
Barnes A, Alonzi R, Blackledge M, et al., 2018, UK quantitative WB-DWI technical workgroup: consensus meeting recommendations on optimisation, quality control, processing and analysis of quantitative whole-body diffusion-weighted imaging for cancer, BRITISH JOURNAL OF RADIOLOGY, Vol: 91, ISSN: 0007-1285
Bazot M, Bharwani N, Huchon C, et al., 2017, European Society of Urogenital Radiology (ESUR) guidelines: MR imaging of pelvic endometriosis, IMAGERIE DE LA FEMME, Vol: 27, Pages: 267-279, ISSN: 1776-9817
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