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Variability induced by the MR imager in dynamic contrast-enhanced imaging of the prostate. Diagn Interv Imaging 2018; 99:255-264. [DOI: 10.1016/j.diii.2017.12.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2017] [Revised: 12/03/2017] [Accepted: 12/07/2017] [Indexed: 12/22/2022]
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252
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Multiparametric Magnetic Resonance Imaging of the Prostate: Repeatability of Volume and Apparent Diffusion Coefficient Quantification. Invest Radiol 2018; 52:538-546. [PMID: 28463931 PMCID: PMC5544576 DOI: 10.1097/rli.0000000000000382] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVES The aim of this study was to evaluate the repeatability of a region of interest (ROI) volume and mean apparent diffusion coefficient (ADC) in standard-of-care 3 T multiparametric magnetic resonance imaging (mpMRI) of the prostate obtained with the use of endorectal coil. MATERIALS AND METHODS This prospective study was Health Insurance Portability and Accountability Act compliant, with institutional review board approval and written informed consent. Men with confirmed or suspected treatment-naive prostate cancer scheduled for mpMRI were offered a repeat mpMRI within 2 weeks. Regions of interest corresponding to the whole prostate gland, the entire peripheral zone (PZ), normal PZ, and suspected tumor ROI (tROI) on axial T2-weighted, dynamic contrast-enhanced subtract, and ADC images were annotated and assessed using Prostate Imaging Reporting and Data System (PI-RADS) v2. Repeatability of the ROI volume for each of the analyzed image types and mean ROI ADC was summarized with repeatability coefficient (RC) and RC%. RESULTS A total of 189 subjects were approached to participate in the study. Of 40 patients that gave initial agreement, 15 men underwent 2 mpMRI examinations and completed the study. Peripheral zone tROIs were identified in 11 subjects. Tumor ROI volume was less than 0.5 mL in 8 of 11 subjects. PI-RADS categories were identical between baseline-repeat studies in 11/15 subjects and differed by 1 point in 4/15. Peripheral zone tROI volume RC (RC%) was 233 mm (71%) on axial T2-weighted, 422 mm (112%) on ADC, and 488 mm (119%) on dynamic contrast-enhanced subtract. Apparent diffusion coefficient ROI mean RC (RC%) were 447 × 10 mm/s (42%) in PZ tROI and 471 × 10 mm/s (30%) in normal PZ. Significant difference in repeatability of the tROI volume across series was observed (P < 0.005). The mean ADC RC% was lower than volume RC% for tROI ADC (P < 0.05). CONCLUSIONS PI-RADS v2 overall assessment was highly repeatable. Multiparametric magnetic resonance imaging sequences differ in volume measurement repeatability. The mean tROI ADC is more repeatable compared with tROI volume in ADC. Repeatability of prostate ADC is comparable with that in other abdominal organs.
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deSouza NM, Winfield JM, Waterton JC, Weller A, Papoutsaki MV, Doran SJ, Collins DJ, Fournier L, Sullivan D, Chenevert T, Jackson A, Boss M, Trattnig S, Liu Y. Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives. Eur Radiol 2018; 28:1118-1131. [PMID: 28956113 PMCID: PMC5811587 DOI: 10.1007/s00330-017-4972-z] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Revised: 05/24/2017] [Accepted: 06/28/2017] [Indexed: 12/18/2022]
Abstract
For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up. Disease detection and staging involve qualitative, subjective assessment of images, whereas for prognosis, progression or response, quantitative evaluation of the apparent diffusion coefficient (ADC) is required. Validation and qualification of ADC in multicentre trials involves examination of i) technical performance to determine biomarker bias and reproducibility and ii) biological performance to interrogate a specific aspect of biology or to forecast outcome. Unfortunately, the variety of acquisition and analysis methodologies employed at different centres make ADC values non-comparable between them. This invalidates implementation in multicentre trials and limits utility of ADC as a biomarker. This article reviews the factors contributing to ADC variability in terms of data acquisition and analysis. Hardware and software considerations are discussed when implementing standardised protocols across multi-vendor platforms together with methods for quality assurance and quality control. Processes of data collection, archiving, curation, analysis, central reading and handling incidental findings are considered in the conduct of multicentre trials. Data protection and good clinical practice are essential prerequisites. Developing international consensus of procedures is critical to successful validation if ADC is to become a useful biomarker in oncology. KEY POINTS • Standardised acquisition/analysis allows quantification of imaging biomarkers in multicentre trials. • Establishing "precision" of the measurement in the multicentre context is essential. • A repository with traceable data of known provenance promotes further research.
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Affiliation(s)
- N. M. deSouza
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - J. M. Winfield
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - J. C. Waterton
- Manchester Academic Health Sciences Institute, University of Manchester, Manchester, UK
| | - A. Weller
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - M.-V. Papoutsaki
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - S. J. Doran
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - D. J. Collins
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - L. Fournier
- Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Radiology Department, Université Paris Descartes Sorbonne Paris Cité, Paris, France
| | - D. Sullivan
- Duke Comprehensive Cancer Institute, Durham, NC USA
| | - T. Chenevert
- Department of Radiology, University of Michigan Health System, Ann Arbor, MI USA
| | - A. Jackson
- Manchester Academic Health Sciences Institute, University of Manchester, Manchester, UK
| | - M. Boss
- Applied Physics Division, National Institute of Standards and Technology (NIST), Boulder, CO USA
| | - S. Trattnig
- Department of Biomedical Imaging and Image guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Y. Liu
- European Organisation for Research and Treatment of Cancer, Headquarters, Brussels, Belgium
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254
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Obuchowski NA. Interpreting Change in Quantitative Imaging Biomarkers. Acad Radiol 2018; 25:372-379. [PMID: 29191687 DOI: 10.1016/j.acra.2017.09.023] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Revised: 09/26/2017] [Accepted: 09/27/2017] [Indexed: 10/18/2022]
Abstract
RATIONALE AND OBJECTIVES Quantitative imaging biomarkers (QIBs) are becoming increasingly adopted into clinical practice to monitor changes in patients' conditions. The repeatability coefficient (RC) is the clinical cut-point used to discern between changes in a biomarker's measurements due to measurement error and changes that exceed measurement error, thus indicating real change in the patient. Imaging biomarkers have characteristics that make them difficult for estimating the repeatability coefficient, including nonconstant error, non-Gaussian distributions, and measurement error that must be estimated from small studies. METHODS We conducted a Monte Carlo simulation study to investigate how well three statistical methods for estimating the repeatability coefficient perform under five settings common for QIBs. RESULTS When the measurement error is constant and replicates are normally distributed, all of the statistical methods perform well. When the measurement error is proportional to the true value, approaches that use the log transformation or coefficient of variation perform similarly. For other common settings, none of the methods for estimating the repeatability coefficient perform adequately. CONCLUSION Many of the common approaches to estimating the repeatability coefficient perform well for only limited scenarios. The optimal approach depends strongly on the pattern of the within-subject variability; thus, a precision profile is critical in evaluating the technical performance of QIBs. Asymmetric bounds for detecting regression vs progression can be implemented and should be used when clinically appropriate.
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255
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Moreau B, Iannessi A, Hoog C, Beaumont H. How reliable are ADC measurements? A phantom and clinical study of cervical lymph nodes. Eur Radiol 2018; 28:3362-3371. [PMID: 29476218 PMCID: PMC6028847 DOI: 10.1007/s00330-017-5265-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 12/11/2017] [Accepted: 12/20/2017] [Indexed: 12/11/2022]
Abstract
Objective To assess the reliability of ADC measurements in vitro and in cervical lymph nodes of healthy volunteers. Methods We used a GE 1.5 T MRI scanner and a first ice-water phantom according to recommendations released by the Quantitative Imaging Biomarker Alliance (QIBA) for assessing ADC against reference values. We analysed the target size effect by using a second phantom made of six inserted spheres with diameters ranging from 10 to 37 mm. Thirteen healthy volunteers were also scanned to assess the inter- and intra-observer reproducibility of volumetric ADC measurements of cervical lymph nodes. Results On the ice-water phantom, the error in ADC measurements was less than 4.3 %. The spatial bias due to the non-linearity of gradient fields was found to be 24 % at 8 cm from the isocentre. ADC measure reliability decreased when addressing small targets due to partial volume effects (up to 12.8 %). The mean ADC value of cervical lymph nodes was 0.87.10-3 ± 0.12.10-3 mm2/s with a good intra-observer reliability. Inter-observer reproducibility featured a bias of -5.5 % due to segmentation issues. Conclusion ADC is a potentially important imaging biomarker in oncology; however, variability issues preclude its broader adoption. Reliable use of ADC requires technical advances and systematic quality control. Key Points • ADC is a promising quantitative imaging biomarker. • ADC has a fair inter-reader variability and good intra-reader variability. • Partial volume effect, post-processing software and non-linearity of scanners are limiting factors. • No threshold values for detecting cervical lymph node malignancy can be drawn. Electronic supplementary material The online version of this article (10.1007/s00330-017-5265-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Bastien Moreau
- Department of Radiology, Centre Antoine Lacassagne, 06100, Nice, France
| | - Antoine Iannessi
- Department of Radiology, Centre Antoine Lacassagne, 06100, Nice, France
| | - Christopher Hoog
- Department of Radiology, Centre Antoine Lacassagne, 06100, Nice, France
| | - Hubert Beaumont
- Research and Development Department, Median Technologies, Les deux arcs - 1800 route des crêtes - Bat. B, 06560, Valbonne, France.
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256
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Kaneta T, Daisaki H, Ogawa M, Liu ET, Iizuka H, Arisawa T, Hino-Shishikura A, Yoshida K, Inoue T. Use of count-based image reconstruction to evaluate the variability and repeatability of measured standardised uptake values. PLoS One 2018; 13:e0192549. [PMID: 29432459 PMCID: PMC5809066 DOI: 10.1371/journal.pone.0192549] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Accepted: 01/25/2018] [Indexed: 12/02/2022] Open
Abstract
Standardized uptake values (SUVs) are the most widely used quantitative imaging biomarkers in PET. It is important to evaluate the variability and repeatability of measured SUVs. Phantom studies seem to be essential for this purpose; however, repetitive phantom scanning is not recommended due to the decay of radioactivity. In this study, we performed count-based image reconstruction to avoid the influence of decay using two different PET/CT scanners. By adjusting the ratio of 18F-fluorodeoxyglucose solution to tap water, a NEMA IEC body phantom was set for SUVs of 4.0 inside six hot spheres. The PET data were obtained using two scanners (Aquiduo and Celesteion; Toshiba Medical Systems, Tochigi, Japan). We set the start time for image reconstruction when the total radioactivity in the phantom was 2.53 kBq/cc, and employed the counts of the first 2-min acquisition as the standard. To maintain the number of counts for each image, we set the acquisition time for image reconstruction depending on the decay of radioactivity. We obtained 50 images, and calculated the SUVmax and SUVpeak of all six spheres in each image. The average values of the SUVmax were used to calculate the recovery coefficients to compare those measured by the two different scanners. Bland-Altman analyses of the SUVs measured by the two scanners were also performed. The measured SUVs using the two scanners exhibited a 10–30% difference, and the standard deviation (SD) of the measured SUVs was between 0.1–0.2. The Celesteion always exhibited higher values than the Aquiduo. The smaller sphere exhibited a larger SD, and the SUVpeak had a smaller SD than the SUVmax. The Bland-Altman analyses showed poor agreement between the SUVs measured by the two scanners. The recovery coefficient curves obtained from the two scanners were considerably different. The Celesteion exhibited higher recovery coefficients than the Aquiduo, especially at approximately 20-mm-diameter. Additionally, the curves were lower than those calculated from the standard 30-min acquisition images. We propound count-based image reconstruction to evaluate the variability and repeatability of measured SUVs. These results are also applicable for the standardization and harmonization of SUVs in multi-institutional studies.
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Affiliation(s)
- Tomohiro Kaneta
- Department of Radiology, Yokohama City University, Yokohama, Japan
- * E-mail:
| | - Hiromitsu Daisaki
- Department of Radiological Technology, Gunma Prefectual College of Health Sciences, Maebashi, Japan
| | - Matsuyoshi Ogawa
- Department of Radiology, Yokohama City University, Yokohama, Japan
| | - En-Tao Liu
- Department of Radiology, Yokohama City University, Yokohama, Japan
| | - Hitoshi Iizuka
- Department of Radiology, Yokohama City University, Yokohama, Japan
| | - Tetsu Arisawa
- Department of Radiology, Yokohama City University, Yokohama, Japan
| | | | - Keisuke Yoshida
- Department of Radiology, Yokohama City University, Yokohama, Japan
| | - Tomio Inoue
- Department of Radiology, Yokohama City University, Yokohama, Japan
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257
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West J, Romu T, Thorell S, Lindblom H, Berin E, Holm ACS, Åstrand LL, Karlsson A, Borga M, Hammar M, Leinhard OD. Precision of MRI-based body composition measurements of postmenopausal women. PLoS One 2018; 13:e0192495. [PMID: 29415060 PMCID: PMC5802932 DOI: 10.1371/journal.pone.0192495] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 01/24/2018] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVES To determine precision of magnetic resonance imaging (MRI) based fat and muscle quantification in a group of postmenopausal women. Furthermore, to extend the method to individual muscles relevant to upper-body exercise. MATERIALS AND METHODS This was a sub-study to a randomized control trial investigating effects of resistance training to decrease hot flushes in postmenopausal women. Thirty-six women were included, mean age 56 ± 6 years. Each subject was scanned twice with a 3.0T MR-scanner using a whole-body Dixon protocol. Water and fat images were calculated using a 6-peak lipid model including R2*-correction. Body composition analyses were performed to measure visceral and subcutaneous fat volumes, lean volumes and muscle fat infiltration (MFI) of the muscle groups' thigh muscles, lower leg muscles, and abdominal muscles, as well as the three individual muscles pectoralis, latissimus, and rhomboideus. Analysis was performed using a multi-atlas, calibrated water-fat separated quantification method. Liver-fat was measured as average proton density fat-fraction (PDFF) of three regions-of-interest. Precision was determined with Bland-Altman analysis, repeatability, and coefficient of variation. RESULTS All of the 36 included women were successfully scanned and analysed. The coefficient of variation was 1.1% to 1.5% for abdominal fat compartments (visceral and subcutaneous), 0.8% to 1.9% for volumes of muscle groups (thigh, lower leg, and abdomen), and 2.3% to 7.0% for individual muscle volumes (pectoralis, latissimus, and rhomboideus). Limits of agreement for MFI was within ± 2.06% for muscle groups and within ± 5.13% for individual muscles. The limits of agreement for liver PDFF was within ± 1.9%. CONCLUSION Whole-body Dixon MRI could characterize a range of different fat and muscle compartments with high precision, including individual muscles, in the study-group of postmenopausal women. The inclusion of individual muscles, calculated from the same scan, enables analysis for specific intervention programs and studies.
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Affiliation(s)
- Janne West
- Department of Medical and Health Sciences (IMH), Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Advanced MR Analytics AB, Linköping, Sweden
| | - Thobias Romu
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Advanced MR Analytics AB, Linköping, Sweden
- Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden
| | - Sofia Thorell
- Department of Medical and Health Sciences (IMH), Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - Hanna Lindblom
- Department of Medical and Health Sciences (IMH), Linköping University, Linköping, Sweden
| | - Emilia Berin
- Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - Anna-Clara Spetz Holm
- Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - Lotta Lindh Åstrand
- Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - Anette Karlsson
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden
| | - Magnus Borga
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Advanced MR Analytics AB, Linköping, Sweden
- Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden
| | - Mats Hammar
- Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - Olof Dahlqvist Leinhard
- Department of Medical and Health Sciences (IMH), Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Advanced MR Analytics AB, Linköping, Sweden
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258
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Jackson EF. Quantitative Imaging: The Translation from Research Tool to Clinical Practice. Radiology 2018; 286:499-501. [DOI: 10.1148/radiol.2017172258] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Edward F. Jackson
- From the Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, 1016 WIMR, Madison, WI 53705
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259
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Vonder M, van der Aalst CM, Vliegenthart R, van Ooijen PMA, Kuijpers D, Gratama JW, de Koning HJ, Oudkerk M. Coronary Artery Calcium Imaging in the ROBINSCA Trial: Rationale, Design, and Technical Background. Acad Radiol 2018; 25:118-128. [PMID: 28843465 DOI: 10.1016/j.acra.2017.07.010] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Revised: 07/18/2017] [Accepted: 07/20/2017] [Indexed: 01/20/2023]
Abstract
RATIONALE AND OBJECTIVES To describe the rationale, design, and technical background of coronary artery calcium (CAC) imaging in the large-scale population-based cardiovascular disease screening trial (Risk Or Benefit IN Screening for CArdiovascular Diseases [ROBINSCA]). MATERIALS AND METHODS First, literature search was performed to review the logistics, setup, and settings of previously performed CAC imaging studies, and current clinical CAC imaging protocols of participating centers in the ROBINSCA trial were evaluated. A second literature search was performed to evaluate the impact of computed tomography parameter settings on CAC score. RESULTS Based on literature reviews and experts opinion an imaging protocol accompanied by data management protocol was created for ROBINSCA. The imaging protocol should consist of a fixed tube voltage, individually tailored tube current setting, mid-diastolic electrocardiography-triggering, fixed field-of-view, fixed reconstruction kernel, fixed slice thickness, overlapping reconstruction and without iterative reconstruction. The analysis of scans is performed with one type and version of CAC scoring software, by two dedicated and experienced researchers. The data management protocol describes the organization of data handling between the coordinating center, participating centers, and core analysis center. CONCLUSION In this paper we describe the rationale and technical considerations to be taken in developing CAC imaging protocol, and we present a detailed protocol that can be implemented for CAC screening purposes.
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Affiliation(s)
- Marleen Vonder
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands
| | - Carlijn M van der Aalst
- Erasmus MC-University Medical Centre, Department of Public Health, Rotterdam, The Netherlands
| | - Rozemarijn Vliegenthart
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands
| | - Peter M A van Ooijen
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, The Netherlands
| | - Dirkjan Kuijpers
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands; Department of Radiology, Haaglanden Medical Center Bronovo, The Hague, The Netherlands
| | - Jan Willem Gratama
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands; Department of Radiology, Gelre Hospital, Apeldoorn, The Netherlands
| | - Harry J de Koning
- Erasmus MC-University Medical Centre, Department of Public Health, Rotterdam, The Netherlands
| | - Matthijs Oudkerk
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands.
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260
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Barnes A, Alonzi R, Blackledge M, Charles-Edwards G, Collins DJ, Cook G, Coutts G, Goh V, Graves M, Kelly C, Koh DM, McCallum H, Miquel ME, O’Connor J, Padhani A, Pearson R, Priest A, Rockall A, Stirling J, Taylor S, Tunariu N, van der Meulen J, Walls D, Winfield J, Punwani S. 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. Br J Radiol 2018; 91:20170577. [PMID: 29076749 PMCID: PMC5966219 DOI: 10.1259/bjr.20170577] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 10/09/2017] [Accepted: 10/11/2017] [Indexed: 01/28/2023] Open
Abstract
OBJECTIVE Application of whole body diffusion-weighted MRI (WB-DWI) for oncology are rapidly increasing within both research and routine clinical domains. However, WB-DWI as a quantitative imaging biomarker (QIB) has significantly slower adoption. To date, challenges relating to accuracy and reproducibility, essential criteria for a good QIB, have limited widespread clinical translation. In recognition, a UK workgroup was established in 2016 to provide technical consensus guidelines (to maximise accuracy and reproducibility of WB-MRI QIBs) and accelerate the clinical translation of quantitative WB-DWI applications for oncology. METHODS A panel of experts convened from cancer centres around the UK with subspecialty expertise in quantitative imaging and/or the use of WB-MRI with DWI. A formal consensus method was used to obtain consensus agreement regarding best practice. Questions were asked about the appropriateness or otherwise on scanner hardware and software, sequence optimisation, acquisition protocols, reporting, and ongoing quality control programs to monitor precision and accuracy and agreement on quality control. RESULTS The consensus panel was able to reach consensus on 73% (255/351) items and based on consensus areas made recommendations to maximise accuracy and reproducibly of quantitative WB-DWI studies performed at 1.5T. The panel were unable to reach consensus on the majority of items related to quantitative WB-DWI performed at 3T. CONCLUSION This UK Quantitative WB-DWI Technical Workgroup consensus provides guidance on maximising accuracy and reproducibly of quantitative WB-DWI for oncology. The consensus guidance can be used by researchers and clinicians to harmonise WB-DWI protocols which will accelerate clinical translation of WB-DWI-derived QIBs.
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Affiliation(s)
- Anna Barnes
- Centre for Medical Imaging, University College London,University College London, London, UK
| | - Roberto Alonzi
- Clinical Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Matthew Blackledge
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, Institute of Cancer Research,Institute of Cancer Research, Sutton, UK
| | | | | | | | - Glynn Coutts
- MR Physics, The Christie NHS Foundation Trust, The Christie NHS Foundation Trust, Manchester, UK
| | | | - Martin Graves
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust,Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Charles Kelly
- Department of Radiology, Northern Centre for CancerCare, Newcastle upon Tyne Hospitals, NHS Foundations Trust,Northern Centre for CancerCare, Newcastle upon Tyne Hospitals, NHS Foundations Trust, Newcastle upon Tyne, UK
| | | | - Hazel McCallum
- Department of Radiology, Northern Centre for CancerCare, Newcastle upon Tyne Hospitals, NHS Foundations Trust,Northern Centre for CancerCare, Newcastle upon Tyne Hospitals, NHS Foundations Trust, Newcastle upon Tyne, UK
| | | | | | - Anwar Padhani
- Paul Strickland Cancer Centre, Mount Vernon Cancer Centre, Northwood, UK
| | | | - Andrew Priest
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust,Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Andrea Rockall
- Department of Radiology, The Royal Marsden Hospital Foundation Trust,The Royal Marsden Hospital Foundation Trust, Surrey, UK
| | | | | | | | - Jan van der Meulen
- Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine,London School of Hygiene and Tropical Medicine, London, UK
| | - Darren Walls
- Institute Nuclear Medicine, University College London, London, UK
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261
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Wang R, Duan X, Shen C, Han D, Ma J, Wu H, Xu X, Qin T, Fan Q, Zhang Z, Shi W, Guo Y. A retrospective study of SPECT/CT scans using SUV measurement of the normal pelvis with Tc-99m methylene diphosphonate. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2018; 26:895-908. [PMID: 30103368 DOI: 10.3233/xst-180391] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
OBJECTIVE To perform quantitative measurement based on the standardized uptake value (SUV) of Tc-99m methylene diphosphonate (MDP) in the normal pelvis using a single-photon emission tomography (SPECT)/computed tomography (CT) scanner. MATERIAL AND METHODS This retrospective study was performed on 31 patients with cancer undergoing bone SPECT/CT scans with 99mTc-MDP. SUVmax and SUVmean of the normal pelvis were calculated based on the body weight. SUVmax and SUVmean of the bilateral anterior superior iliac spine, posterior superior iliac spine, facies auricularis ossis ilii, ischial tuberosity, and sacrum were also calculated. Furthermore, the correlation of SUVmax and SUVmean of all parts of pelvis with weight, height, and CT was assessed. RESULTS The data for 31 patients (20 women and 11 men; mean age 58.97±9.12 years; age range 37-87 years) were collected. SUVmax and SUVmean changed from 1.65±0.40 to 3.8±1.0 and from 1.15±0.25 to 2.07±0.58, respectively. The coefficient of variation of SUVmax and SUVmean ranged from 0.22 to 0.31. SUVmax and SUVmean had no statistically significant difference between men and women. SUVmax and SUVmean also showed no significant correlation with weight and height. However, part of SUVmax and SUVmean showed a significant correlation with CT. In addition, SUVmax and SUVmean of the bilateral ischial tuberosity showed a significant correlation with CT values. CONCLUSIONS Determination of the SUV value of the normal pelvis with 99m Tc-MDP SPECT/CT is feasible and highly reproducible. SUVs of the normal pelvis showed a relatively large variability. As a quantitative imaging biomarker, SUVs might require standardization with adequate reference data for the participant to minimize variability.
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Affiliation(s)
- Ruifeng Wang
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Xiaoyi Duan
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Cong Shen
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Dong Han
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Junchao Ma
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Hulin Wu
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Xiaotong Xu
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Tao Qin
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Qiuju Fan
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Zhaoguo Zhang
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Weihua Shi
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Youmin Guo
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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Pinkert MA, Salkowski LR, Keely PJ, Hall TJ, Block WF, Eliceiri KW. Review of quantitative multiscale imaging of breast cancer. J Med Imaging (Bellingham) 2018; 5:010901. [PMID: 29392158 PMCID: PMC5777512 DOI: 10.1117/1.jmi.5.1.010901] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2017] [Accepted: 12/19/2017] [Indexed: 12/12/2022] Open
Abstract
Breast cancer is the most common cancer among women worldwide and ranks second in terms of overall cancer deaths. One of the difficulties associated with treating breast cancer is that it is a heterogeneous disease with variations in benign and pathologic tissue composition, which contributes to disease development, progression, and treatment response. Many of these phenotypes are uncharacterized and their presence is difficult to detect, in part due to the sparsity of methods to correlate information between the cellular microscale and the whole-breast macroscale. Quantitative multiscale imaging of the breast is an emerging field concerned with the development of imaging technology that can characterize anatomic, functional, and molecular information across different resolutions and fields of view. It involves a diverse collection of imaging modalities, which touch large sections of the breast imaging research community. Prospective studies have shown promising results, but there are several challenges, ranging from basic physics and engineering to data processing and quantification, that must be met to bring the field to maturity. This paper presents some of the challenges that investigators face, reviews currently used multiscale imaging methods for preclinical imaging, and discusses the potential of these methods for clinical breast imaging.
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Affiliation(s)
- Michael A. Pinkert
- Morgridge Institute for Research, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Laboratory for Optical and Computational Instrumentation, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Medical Physics, Madison, Wisconsin, United States
| | - Lonie R. Salkowski
- University of Wisconsin–Madison, Department of Medical Physics, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Radiology, Madison, Wisconsin, United States
| | - Patricia J. Keely
- University of Wisconsin–Madison, Department of Cell and Regenerative Biology, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Biomedical Engineering, Madison, Wisconsin, United States
| | - Timothy J. Hall
- University of Wisconsin–Madison, Department of Medical Physics, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Biomedical Engineering, Madison, Wisconsin, United States
| | - Walter F. Block
- University of Wisconsin–Madison, Department of Medical Physics, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Radiology, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Biomedical Engineering, Madison, Wisconsin, United States
| | - Kevin W. Eliceiri
- Morgridge Institute for Research, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Laboratory for Optical and Computational Instrumentation, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Medical Physics, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Biomedical Engineering, Madison, Wisconsin, United States
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Larici AR, Farchione A, Franchi P, Ciliberto M, Cicchetti G, Calandriello L, del Ciello A, Bonomo L. Lung nodules: size still matters. Eur Respir Rev 2017; 26:26/146/170025. [DOI: 10.1183/16000617.0025-2017] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Accepted: 10/28/2017] [Indexed: 12/18/2022] Open
Abstract
The incidence of indeterminate pulmonary nodules has risen constantly over the past few years. Determination of lung nodule malignancy is pivotal, because the early diagnosis of lung cancer could lead to a definitive intervention. According to the current international guidelines, size and growth rate represent the main indicators to determine the nature of a pulmonary nodule. However, there are some limitations in evaluating and characterising nodules when only their dimensions are taken into account. There is no single method for measuring nodules, and intrinsic errors, which can determine variations in nodule measurement and in growth assessment, do exist when performing measurements either manually or with automated or semi-automated methods. When considering subsolid nodules the presence and size of a solid component is the major determinant of malignancy and nodule management, as reported in the latest guidelines. Nevertheless, other nodule morphological characteristics have been associated with an increased risk of malignancy. In addition, the clinical context should not be overlooked in determining the probability of malignancy. Predictive models have been proposed as a potential means to overcome the limitations of a sized-based assessment of the malignancy risk for indeterminate pulmonary nodules.
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Daniel M, Andrzejewski P, Sturdza A, Majercakova K, Baltzer P, Pinker K, Wadsak W, Mitterhauser M, Pötter R, Georg P, Helbich T, Georg D. Impact of hybrid PET/MR technology on multiparametric imaging and treatment response assessment of cervix cancer. Radiother Oncol 2017; 125:420-425. [DOI: 10.1016/j.radonc.2017.10.036] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Revised: 10/27/2017] [Accepted: 10/28/2017] [Indexed: 12/12/2022]
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Lecler A, Savatovsky J, Balvay D, Zmuda M, Sadik JC, Galatoire O, Charbonneau F, Bergès O, Picard H, Fournier L. Repeatability of apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0 Tesla in orbital lesions. Eur Radiol 2017; 27:5094-5103. [PMID: 28677061 PMCID: PMC5674133 DOI: 10.1007/s00330-017-4933-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Revised: 06/06/2017] [Accepted: 06/07/2017] [Indexed: 02/07/2023]
Abstract
OBJECTIVES To evaluate repeatability of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) parameters in the orbit. METHODS From December 2015 to March 2016, 22 patients were scanned twice using an IVIM sequence with 15b values (0-2,000 s/mm2) at 3.0T. Two readers independently delineated regions of interest in an orbital mass and in different intra-orbital and extra-orbital structures. Short-term test-retest repeatability and inter-observer agreement were assessed using the intra-class correlation coefficient (ICC), the coefficient of variation (CV) and Bland-Altman limits of agreements (BA-LA). RESULTS Test-retest repeatability of IVIM parameters in the orbital mass was satisfactory for ADC and D (mean CV 12% and 14%, ICC 95% and 93%), poor for f and D*(means CV 43% and 110%, ICC 90% and 65%). Inter-observer repeatability agreement was almost perfect in the orbital mass for all the IVIM parameters (ICC = 95%, 93%, 94% and 90% for ADC, D, f and D*, respectively). CONCLUSIONS IVIM appeared to be a robust tool to measure D in orbital lesions with good repeatability, but this approach showed a poor repeatability of f and D*. KEY POINTS • IVIM technique is feasible in the orbit. • IVIM has a good-acceptable repeatability of D (CV range 12-25 %). • IVIM interobserver repeatability agreement is excellent (ICC range 90-95 %). • f or D* provide higher test-retest and interobserver variabilities.
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Affiliation(s)
- Augustin Lecler
- Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 29 rue Manin, 75019, Paris, France.
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR-S970, Cardiovascular Research Centre - PARCC, Paris, France.
| | - Julien Savatovsky
- Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 29 rue Manin, 75019, Paris, France
| | - Daniel Balvay
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR-S970, Cardiovascular Research Centre - PARCC, Paris, France
| | - Mathieu Zmuda
- Department of Orbitopalpebral Surgery, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - Jean-Claude Sadik
- Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 29 rue Manin, 75019, Paris, France
| | - Olivier Galatoire
- Department of Orbitopalpebral Surgery, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - Frédérique Charbonneau
- Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 29 rue Manin, 75019, Paris, France
| | - Olivier Bergès
- Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 29 rue Manin, 75019, Paris, France
| | - Hervé Picard
- Clinical Research Unit, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - Laure Fournier
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR-S970, Cardiovascular Research Centre - PARCC, Paris, France
- Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Radiology Department, Université Paris Descartes Sorbonne Paris Cité, Paris, France
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Gavrielides MA, Berman BP, Supanich M, Schultz K, Li Q, Petrick N, Zeng R, Siegelman J. Quantitative assessment of nonsolid pulmonary nodule volume with computed tomography in a phantom study. Quant Imaging Med Surg 2017; 7:623-635. [PMID: 29312867 DOI: 10.21037/qims.2017.12.07] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Background To assess the volumetric measurement of small (≤1 cm) nonsolid nodules with computed tomography (CT), focusing on the interaction of state of the art iterative reconstruction (IR) methods and dose with nodule densities, sizes, and shapes. Methods Twelve synthetic nodules [5 and 10 mm in diameter, densities of -800, -630 and -10 Hounsfield units (HU), spherical and spiculated shapes] were scanned within an anthropomorphic phantom. Dose [computed tomography scan dose index (CTDIvol)] ranged from standard (4.1 mGy) to below screening levels (0.3 mGy). Data was reconstructed using filtered back-projection and two state-of-the-art IR methods (adaptive and model-based). Measurements were extracted with a previously validated matched filter-based estimator. Analysis of accuracy and precision was based on evaluation of percent bias (PB) and the repeatability coefficient (RC) respectively. Results Density had the most important effect on measurement error followed by the interaction of density with nodule size. The nonsolid -630 HU nodules had high accuracy and precision at levels comparable to solid (-10 HU) nonsolid, regardless of reconstruction method and with CTDIvol as low as 0.6 mGy. PB was <5% and <11% for the 10- and 5-mm in nominal diameter -630 HU nodules respectively, and RC was <5% and <12% for the same nodules. For nonsolid -800 HU nodules, PB increased to <11% and <30% for the 10- and 5-mm nodules respectively, whereas RC increased slightly overall but varied widely across dose and reconstruction algorithms for the 5-mm nodules. Model-based IR improved measurement accuracy for the 5-mm, low-density (-800, -630 HU) nodules. For other nodules the effect of reconstruction method was small. Dose did not affect volumetric accuracy and only affected slightly the precision of 5-mm nonsolid nodules. Conclusions Reasonable values of both accuracy and precision were achieved for volumetric measurements of all 10-mm nonsolid nodules, and for the 5-mm nodules with -630 HU or higher density, when derived from scans acquired with below screening dose levels as low as 0.6 mGy and regardless of reconstruction algorithm.
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Affiliation(s)
- Marios A Gavrielides
- Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, , Office of In Vitro Diagnostics and Radiological Health, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Benjamin P Berman
- Division of Radiological Health, Office of In Vitro Diagnostics and Radiological Health, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Mark Supanich
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Kurt Schultz
- Toshiba Medical Research Institute USA, Inc., Center for Medical Research and Development, Illinois, USA
| | - Qin Li
- Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, , Office of In Vitro Diagnostics and Radiological Health, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Nicholas Petrick
- Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, , Office of In Vitro Diagnostics and Radiological Health, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Rongping Zeng
- Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, , Office of In Vitro Diagnostics and Radiological Health, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Jenifer Siegelman
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachussetts, USA
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Abstract
Diffusion-weighted imaging (DWI) is increasingly incorporated into routine body magnetic resonance imaging protocols. DWI can assist with lesion detection and even in characterization. Quantitative DWI has exhibited promise in the discrimination between benign and malignant pathology, in the evaluation of the biologic aggressiveness, and in the assessment of the response to treatment. Unfortunately, inconsistencies in DWI acquisition parameters and analysis have hampered widespread clinical utilization. Focusing primarily on liver applications, this article will review the basic principles of quantitative DWI. In addition to standard mono-exponential fitting, the authors will discuss intravoxel incoherent motion and diffusion kurtosis imaging that involve more sophisticated approaches to diffusion quantification.
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Affiliation(s)
- Myles T Taffel
- Department of Radiology, New York University School of Medicine, New York, NY
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Abstract
OBJECTIVE The goals of this review are to provide background information on the definitions and applications of the general term "biomarker" and to highlight the specific roles of breast imaging biomarkers in research and clinical breast cancer care. A search was conducted of the main electronic biomedical databases (PubMed, Cochrane, Embase, MEDLINE [Ovid], Scopus, and Web of Science). The search was focused on review literature in general radiology and biomedical sciences and on reviews and primary research articles on biomarkers in breast imaging over the 15 years ending in June 2017. The keywords included "biomarker," "trial endpoints," "breast imaging," "breast cancer," "radiomics," and "precision medicine" in the titles and abstracts of the papers. CONCLUSION Clinical breast care and breast cancer-related research rely on imaging biomarkers for decision support. In the era of precision medicine and big data, the practice of radiology is likely to change. A closer integration of breast imaging with related biomedical fields and the creation of large integrated and shareable databases of clinical, molecular, and imaging biomarkers should allow the field to continue guiding breast cancer care and research.
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Fenwick AJ, Wevrett JL, Ferreira KM, Denis-Bacelar AM, Robinson AP. Quantitative imaging, dosimetry and metrology; Where do National Metrology Institutes fit in? Appl Radiat Isot 2017; 134:74-78. [PMID: 29158037 DOI: 10.1016/j.apradiso.2017.11.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Revised: 11/09/2017] [Accepted: 11/10/2017] [Indexed: 12/17/2022]
Abstract
In External Beam Radiotherapy, National Metrology Institutes (NMIs) play a critical role in the delivery of accurate absorbed doses to patients undergoing treatment. In contrast for nuclear medicine the role of the NMI is less clear and although significant work has been done in order to establish links for activity measurement, the calculation of administered absorbed doses is not traceable in the same manner as EBRT. Over recent decades the use of novel radiolabelled pharmaceuticals has increased dramatically. The limitation of secondary complications due to radiation damage to non-target tissue has historically been achieved by the use of activity escalation studies during clinical trials and this in turn has led to a chronic under dosing of the majority of patients. This paper looks to address the difficulties in combining clinical everyday practice with the grand challenges laid out by national metrology institutes to improve measurement capability in all walks of life. In the life sciences it can often be difficult to find the correct balance between pure research and practical solutions to measurement problems, and this paper is a discussion regarding these difficulties and how some NMIs have chosen to tackle these issues. The necessity of establishing strong links to underlying standards in the field of quantitative nuclear medicine imaging is highlighted. The difficulties and successes of current methods for providing traceability in nuclear medicine are discussed.
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Affiliation(s)
- A J Fenwick
- National Physical Laboratory, Hampton Road, Teddington, UK; Cardiff University, Cardiff, UK.
| | - J L Wevrett
- National Physical Laboratory, Hampton Road, Teddington, UK; University of Surrey, Guildford, UK; Royal Surrey County Hospital, Guildford, UK
| | - K M Ferreira
- National Physical Laboratory, Hampton Road, Teddington, UK
| | | | - A P Robinson
- National Physical Laboratory, Hampton Road, Teddington, UK; The University of Manchester, Manchester, UK; The Christie NHS Foundation Trust, Manchester, UK
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Weller A, Papoutsaki MV, Waterton JC, Chiti A, Stroobants S, Kuijer J, Blackledge M, Morgan V, deSouza NM. Diffusion-weighted (DW) MRI in lung cancers: ADC test-retest repeatability. Eur Radiol 2017; 27:4552-4562. [PMID: 28396997 PMCID: PMC6175053 DOI: 10.1007/s00330-017-4828-6] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Revised: 03/12/2017] [Accepted: 03/20/2017] [Indexed: 01/26/2023]
Abstract
PURPOSE To determine the test-retest repeatability of Apparent Diffusion Coefficient (ADC) measurements across institutions and MRI vendors, plus investigate the effect of post-processing methodology on measurement precision. METHODS Thirty malignant lung lesions >2 cm in size (23 patients) were scanned on two occasions, using echo-planar-Diffusion-Weighted (DW)-MRI to derive whole-tumour ADC (b = 100, 500 and 800smm-2). Scanning was performed at 4 institutions (3 MRI vendors). Whole-tumour volumes-of-interest were copied from first visit onto second visit images and from one post-processing platform to an open-source platform, to assess ADC repeatability and cross-platform reproducibility. RESULTS Whole-tumour ADC values ranged from 0.66-1.94x10-3mm2s-1 (mean = 1.14). Within-patient coefficient-of-variation (wCV) was 7.1% (95% CI 5.7-9.6%), limits-of-agreement (LoA) -18.0 to 21.9%. Lesions >3 cm had improved repeatability: wCV 3.9% (95% CI 2.9-5.9%); and LoA -10.2 to 11.4%. Variability for lesions <3 cm was 2.46 times higher. ADC reproducibility across different post-processing platforms was excellent: Pearson's R2 = 0.99; CoV 2.8% (95% CI 2.3-3.4%); and LoA -7.4 to 8.0%. CONCLUSION A free-breathing DW-MRI protocol for imaging malignant lung tumours achieved satisfactory within-patient repeatability and was robust to changes in post-processing software, justifying its use in multi-centre trials. For response evaluation in individual patients, a change in ADC >21.9% will reflect treatment-related change. KEY POINTS • In lung cancer, free-breathing DWI-MRI produces acceptable images with evaluable ADC measurement. • ADC repeatability coefficient-of-variation is 7.1% for lung tumours >2 cm. • ADC repeatability coefficient-of-variation is 3.9% for lung tumours >3 cm. • ADC measurement precision is unaffected by the post-processing software used. • In multicentre trials, 22% increase in ADC indicates positive treatment response.
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Affiliation(s)
- Alex Weller
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT, UK.
| | - Marianthi Vasiliki Papoutsaki
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT, UK
| | | | | | | | - Joost Kuijer
- Vrije Universiteit Medisch Centrum, Amsterdam, The Netherlands
| | - Matthew Blackledge
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT, UK
| | - Veronica Morgan
- Department of Medicine, Royal Marsden NHS Foundation Trust, London, UK
| | - Nandita M deSouza
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT, UK
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Pitre-Champagnat S, Coiffier B, Jourdain L, Benatsou B, Leguerney I, Lassau N. Toward a Standardization of Ultrasound Scanners for Dynamic Contrast-Enhanced Ultrasonography: Methodology and Phantoms. ULTRASOUND IN MEDICINE & BIOLOGY 2017; 43:2670-2677. [PMID: 28779957 DOI: 10.1016/j.ultrasmedbio.2017.06.032] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Revised: 06/28/2017] [Accepted: 06/30/2017] [Indexed: 06/07/2023]
Abstract
The standardization of ultrasound scanners for dynamic contrast-enhanced ultrasonography (DCE-US) is mandatory for evaluation of clinical multicenter studies. We propose a robust method using a phantom for measuring the variation of the harmonic signal intensity obtained from the area under the time-intensity curve versus various contrast-agent concentrations. The slope of this measured curve is the calibration parameter. We tested our method on two devices from the same manufacturer (AplioXV and Aplio500, Toshiba, Tokyo, Japan) using the same settings as defined for a French multicenter study. The Aplio500's settings were adjusted to match the slopes of the AplioXV, resulting in the following settings on the Aplio500: at 3.5 MHz: MI = 0.15; CG = 35 dB and at 8 MHz: MI = 0.10; CG = 32 dB. This calibration method is very important for future DCE-US multicenter studies.
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Affiliation(s)
| | - Bénédicte Coiffier
- University Paris-Sud CNRS, Université Paris-Saclay, Villejuif, France; Gustave Roussy, Villejuif, France
| | - Laurène Jourdain
- University Paris-Sud CNRS, Université Paris-Saclay, Villejuif, France
| | - Baya Benatsou
- University Paris-Sud CNRS, Université Paris-Saclay, Villejuif, France; Gustave Roussy, Villejuif, France
| | - Ingrid Leguerney
- University Paris-Sud CNRS, Université Paris-Saclay, Villejuif, France; Gustave Roussy, Villejuif, France
| | - Nathalie Lassau
- University Paris-Sud CNRS, Université Paris-Saclay, Villejuif, France; Gustave Roussy, Villejuif, France
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Cornelis FH, Martin M, Saut O, Buy X, Kind M, Palussiere J, Colin T. Precision of manual two-dimensional segmentations of lung and liver metastases and its impact on tumour response assessment using RECIST 1.1. Eur Radiol Exp 2017; 1:16. [PMID: 29708185 PMCID: PMC5909353 DOI: 10.1186/s41747-017-0015-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Accepted: 07/12/2017] [Indexed: 11/24/2022] Open
Abstract
Background Response evaluation criteria in solid tumours (RECIST) has significant limitations in terms of variability and reproducibility, which may not be independent. The aim of the study was to evaluate the precision of manual bi-dimensional segmentation of lung, liver metastases, and to quantify the uncertainty in tumour response assessment. Methods A total of 520 segmentations of metastases from six livers and seven lungs were independently performed by ten physicians and ten scientists on CT images, reflecting the variability encountered in clinical practice. Operators manually contoured the tumours, firstly independently according to the RECIST and secondly on a preselected slice. Diameters and areas were extracted from the segmentations. Mean standard deviations were used to build regression models and 95% confidence intervals (95% CI) were calculated for each tumour size and for limits of progressive disease (PD) and partial response (PR) derived from RECIST 1.1. Results Thirteen aberrant segmentations (2.5%) were observed without significant differences between the physicians and scientists; only the mean area of liver tumours (p = 0.034) and mean diameter of lung tumours (p = 0.021) differed significantly. No difference was observed between the methods. Inter-observer agreement was excellent (intra-class correlation >0.90) for all variables. In liver, overlaps of the 95% CI with the 95% CI of limits of PD or PR were observed for diameters above 22.7 and 37.9 mm, respectively. An overlap of 95% CIs was systematically observed for area. No overlaps were observed in lung. Conclusions Although the experience of readers might not affect the precision of segmentation in lung and liver, the results of manual segmentation performed for tumour response assessment remain uncertain for large liver metastases. Electronic supplementary material The online version of this article (doi:10.1186/s41747-017-0015-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- F H Cornelis
- 1University Bordeaux, IMB, UMR 5251; CNRS, IMB, UMR 5251; Bordeaux INP, IMB, UMR 5251, Talence, France.,2INRIA Bordeaux-sud-Ouest, team MONC, 200 Avenue de la Vieille Tour, 33405 Talence, France.,3Department de Radiologie, Hôpital Tenon, 4 rue de la Chine, 75020 Paris, France
| | - M Martin
- 1University Bordeaux, IMB, UMR 5251; CNRS, IMB, UMR 5251; Bordeaux INP, IMB, UMR 5251, Talence, France.,2INRIA Bordeaux-sud-Ouest, team MONC, 200 Avenue de la Vieille Tour, 33405 Talence, France
| | - O Saut
- 1University Bordeaux, IMB, UMR 5251; CNRS, IMB, UMR 5251; Bordeaux INP, IMB, UMR 5251, Talence, France.,2INRIA Bordeaux-sud-Ouest, team MONC, 200 Avenue de la Vieille Tour, 33405 Talence, France
| | - X Buy
- 4Départment de Radiologie, Institut Bergonié, 229 cours de l'Argonne, 33076 Bordeaux, France
| | - M Kind
- 4Départment de Radiologie, Institut Bergonié, 229 cours de l'Argonne, 33076 Bordeaux, France
| | - J Palussiere
- 4Départment de Radiologie, Institut Bergonié, 229 cours de l'Argonne, 33076 Bordeaux, France
| | - T Colin
- 1University Bordeaux, IMB, UMR 5251; CNRS, IMB, UMR 5251; Bordeaux INP, IMB, UMR 5251, Talence, France.,2INRIA Bordeaux-sud-Ouest, team MONC, 200 Avenue de la Vieille Tour, 33405 Talence, France
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Rydzak CE, Armato SG, Avila RS, Mulshine JL, Yankelevitz DF, Gierada DS. Quality assurance and quantitative imaging biomarkers in low-dose CT lung cancer screening. Br J Radiol 2017; 91:20170401. [PMID: 28830225 DOI: 10.1259/bjr.20170401] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
After years of assessment through controlled clinical trials, low-dose CT screening for lung cancer is becoming part of clinical practice. As with any cancer screening test, those undergoing lung cancer screening are not being evaluated for concerning signs or symptoms, but are generally in good health and proactively trying to prevent premature death. Given the resultant obligation to achieve the screening aim of early diagnosis while also minimizing the potential for morbidity from workup of indeterminate but ultimately benign screening abnormalities, careful implementation of screening with conformance to currently recognized best practices and a focus on quality assurance is essential. In this review, we address the importance of each component of the screening process to optimize the effectiveness of CT screening, discussing options for quality assurance at each step. We also discuss the potential added advantages, quality assurance requirements and current status of quantitative imaging biomarkers related to lung cancer screening. Finally, we highlight suggestions for improvements and needs for further evidence in evaluating the performance of CT screening as it transitions from the research trial setting into daily clinical practice.
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Affiliation(s)
- Chara E Rydzak
- 1 Mallinckrodt Institute of Radiology, Washington University School of Medicine , St. Louis, MO , USA
| | - Samuel G Armato
- 2 Department of Radiology, University of Chicago , Chicago, IL , USA
| | | | - James L Mulshine
- 4 Department of Internal Medicine, Rush University , Chicago, IL , USA
| | - David F Yankelevitz
- 5 Department of Radiology, Icahn School of Medicine at Mount Sinai , New York, NY , USA
| | - David S Gierada
- 1 Mallinckrodt Institute of Radiology, Washington University School of Medicine , St. Louis, MO , USA
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274
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Messroghli DR, Moon JC, Ferreira VM, Grosse-Wortmann L, He T, Kellman P, Mascherbauer J, Nezafat R, Salerno M, Schelbert EB, Taylor AJ, Thompson R, Ugander M, van Heeswijk RB, Friedrich MG. Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: A consensus statement by the Society for Cardiovascular Magnetic Resonance (SCMR) endorsed by the European Association for Cardiovascular Imaging (EACVI). J Cardiovasc Magn Reson 2017; 19:75. [PMID: 28992817 PMCID: PMC5633041 DOI: 10.1186/s12968-017-0389-8] [Citation(s) in RCA: 1126] [Impact Index Per Article: 140.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2017] [Accepted: 09/25/2017] [Indexed: 12/14/2022] Open
Abstract
Parametric mapping techniques provide a non-invasive tool for quantifying tissue alterations in myocardial disease in those eligible for cardiovascular magnetic resonance (CMR). Parametric mapping with CMR now permits the routine spatial visualization and quantification of changes in myocardial composition based on changes in T1, T2, and T2*(star) relaxation times and extracellular volume (ECV). These changes include specific disease pathways related to mainly intracellular disturbances of the cardiomyocyte (e.g., iron overload, or glycosphingolipid accumulation in Anderson-Fabry disease); extracellular disturbances in the myocardial interstitium (e.g., myocardial fibrosis or cardiac amyloidosis from accumulation of collagen or amyloid proteins, respectively); or both (myocardial edema with increased intracellular and/or extracellular water). Parametric mapping promises improvements in patient care through advances in quantitative diagnostics, inter- and intra-patient comparability, and relatedly improvements in treatment. There is a multitude of technical approaches and potential applications. This document provides a summary of the existing evidence for the clinical value of parametric mapping in the heart as of mid 2017, and gives recommendations for practical use in different clinical scenarios for scientists, clinicians, and CMR manufacturers.
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Affiliation(s)
- Daniel R. Messroghli
- Department of Internal Medicine and Cardiology, Deutsches Herzzentrum Berlin, Berlin, Germany
- Department of Internal Medicine and Cardiology, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Berlin, Augustenburger Platz 1, 13353 Berlin, Germany
| | - James C. Moon
- University College London and Barts Heart Centre, London, UK
| | - Vanessa M. Ferreira
- Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Lars Grosse-Wortmann
- Division of Cardiology in the Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON Canada
| | - Taigang He
- Cardiovascular Science Research Centre, St George’s, University of London, London, UK
| | | | - Julia Mascherbauer
- Department of Internal Medicine II, Division of Cardiology, Vienna, Austria
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA
| | - Michael Salerno
- Departments of Medicine Cardiology Division, Radiology and Medical Imaging, and Biomedical Engineering, University of Virginia Health System, Charlottesville, VA USA
| | - Erik B. Schelbert
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
- UPMC Cardiovascular Magnetic Resonance Center, Heart and Vascular Institute, Pittsburgh, PA USA
- Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA USA
| | - Andrew J. Taylor
- The Alfred Hospital, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Richard Thompson
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Martin Ugander
- Department of Clinical Physiology, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Ruud B. van Heeswijk
- Department of Radiology, Lausanne University Hospital (CHUV) and Lausanne University (UNIL), Lausanne, Switzerland
| | - Matthias G. Friedrich
- Departments of Medicine and Diagnostic Radiology, McGill University, Montréal, Québec Canada
- Department of Medicine, Heidelberg University, Heidelberg, Germany
- Département de radiologie, Université de Montréal, Montréal, Québec Canada
- Departments of Cardiac Sciences and Radiology, University of Calgary, Calgary, Canada
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275
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Park JE, Han K, Sung YS, Chung MS, Koo HJ, Yoon HM, Choi YJ, Lee SS, Kim KW, Shin Y, An S, Cho HM, Park SH. Selection and Reporting of Statistical Methods to Assess Reliability of a Diagnostic Test: Conformity to Recommended Methods in a Peer-Reviewed Journal. Korean J Radiol 2017; 18:888-897. [PMID: 29089821 PMCID: PMC5639154 DOI: 10.3348/kjr.2017.18.6.888] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Accepted: 07/28/2017] [Indexed: 12/13/2022] Open
Abstract
Objective To evaluate the frequency and adequacy of statistical analyses in a general radiology journal when reporting a reliability analysis for a diagnostic test. Materials and Methods Sixty-three studies of diagnostic test accuracy (DTA) and 36 studies reporting reliability analyses published in the Korean Journal of Radiology between 2012 and 2016 were analyzed. Studies were judged using the methodological guidelines of the Radiological Society of North America-Quantitative Imaging Biomarkers Alliance (RSNA-QIBA), and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) initiative. DTA studies were evaluated by nine editorial board members of the journal. Reliability studies were evaluated by study reviewers experienced with reliability analysis. Results Thirty-one (49.2%) of the 63 DTA studies did not include a reliability analysis when deemed necessary. Among the 36 reliability studies, proper statistical methods were used in all (5/5) studies dealing with dichotomous/nominal data, 46.7% (7/15) of studies dealing with ordinal data, and 95.2% (20/21) of studies dealing with continuous data. Statistical methods were described in sufficient detail regarding weighted kappa in 28.6% (2/7) of studies and regarding the model and assumptions of intraclass correlation coefficient in 35.3% (6/17) and 29.4% (5/17) of studies, respectively. Reliability parameters were used as if they were agreement parameters in 23.1% (3/13) of studies. Reproducibility and repeatability were used incorrectly in 20% (3/15) of studies. Conclusion Greater attention to the importance of reporting reliability, thorough description of the related statistical methods, efforts not to neglect agreement parameters, and better use of relevant terminology is necessary.
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Affiliation(s)
- Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Kyunghwa Han
- Department of Radiology, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul 03722, Korea
| | - Yu Sub Sung
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Mi Sun Chung
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul 06973, Korea
| | - Hyun Jung Koo
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Hee Mang Yoon
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Young Jun Choi
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Seung Soo Lee
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Kyung Won Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Youngbin Shin
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Suah An
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
| | - Hyo-Min Cho
- Korea Research Institute of Standards and Science, Daejeon 34113, Korea
| | - Seong Ho Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea
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276
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Sorace AG, Harvey S, Syed A, Yankeelov TE. Imaging Considerations and Interprofessional Opportunities in the Care of Breast Cancer Patients in the Neoadjuvant Setting. Semin Oncol Nurs 2017; 33:425-439. [PMID: 28927763 DOI: 10.1016/j.soncn.2017.08.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
OBJECTIVE To discuss standard-of-care and emerging imaging techniques employed for screening and detection, diagnosis and staging, monitoring response to therapy, and guiding cancer treatments. DATA SOURCES Published journal articles indexed in the National Library of Medicine database and relevant websites. CONCLUSION Imaging plays a fundamental role in the care of cancer patients and specifically, breast cancer patients in the neoadjuvant setting, providing an excellent opportunity for interprofessional collaboration between oncologists, researchers, radiologists, and oncology nurses. Quantitative imaging strategies to assess cellular, molecular, and vascular characteristics within the tumor is needed to better evaluate initial diagnosis and treatment response. IMPLICATIONS FOR NURSING PRACTICE Nurses caring for patients in all settings must continue to seek education on emerging imaging techniques. Oncology nurses provide education about the test, ensure the patient has appropriate pre-testing instructions, and manage patient expectations about timing of results availability.
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277
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Gold JE, Hallman DM, Hellström F, Björklund M, Crenshaw AG, Mathiassen SE, Barbe MF, Ali S. Systematic review of quantitative imaging biomarkers for neck and shoulder musculoskeletal disorders. BMC Musculoskelet Disord 2017; 18:395. [PMID: 28899384 PMCID: PMC5596923 DOI: 10.1186/s12891-017-1694-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Accepted: 07/24/2017] [Indexed: 01/04/2023] Open
Abstract
Background This study systematically summarizes quantitative imaging biomarker research in non-traumatic neck and shoulder musculoskeletal disorders (MSDs). There were two research questions: 1) Are there quantitative imaging biomarkers associated with the presence of neck and shoulder MSDs?, 2) Are there quantitative imaging biomarkers associated with the severity of neck and shoulder MSDs? Methods PubMed and SCOPUS were used for the literature search. One hundred and twenty-five studies met primary inclusion criteria. Data were extracted from 49 sufficient quality studies. Results Most of the 125 studies were cross-sectional and utilized convenience samples of patients as both cases and controls. Only half controlled for potential confounders via exclusion or in the analysis. Approximately one-third reported response rates. In sufficient quality articles, 82% demonstrated at least one statistically significant association between the MSD(s) and biomarker(s) studied. The literature synthesis suggested that neck muscle size may be decreased in neck pain, and trapezius myalgia and neck/shoulder pain may be associated with reduced vascularity in the trapezius and reduced trapezius oxygen saturation at rest and in response to upper extremity tasks. Reduced vascularity in the supraspinatus tendon may also be a feature in rotator cuff tears. Five of eight studies showed an association between a quantitative imaging marker and MSD severity. Conclusions Although research on quantitative imaging biomarkers is still in a nascent stage, some MSD biomarkers were identified. There are limitations in the articles examined, including possible selection bias and inattention to potentially confounding factors. Recommendations for future studies are provided. Electronic supplementary material The online version of this article (doi:10.1186/s12891-017-1694-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Judith E Gold
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden. .,Gold Standard Research Consulting, 830 Montgomery Ave, Bryn Mawr, PA, USA.
| | - David M Hallman
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden
| | - Fredrik Hellström
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden
| | - Martin Björklund
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden.,Department of Community Medicine and Rehabilitation, Physiotherapy, Umeå University, Umeå, Sweden
| | - Albert G Crenshaw
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden
| | - Svend Erik Mathiassen
- Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden
| | - Mary F Barbe
- Department of Anatomy and Cell Biology, Temple University Medical School, Philadelphia, PA, USA
| | - Sayed Ali
- Department of Radiology, Temple University Medical School, Philadelphia, PA, USA
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278
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A novel framework for evaluating the image accuracy of dynamic MRI and the application on accelerated breast DCE MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2017; 31:309-320. [DOI: 10.1007/s10334-017-0648-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2017] [Revised: 07/25/2017] [Accepted: 07/27/2017] [Indexed: 12/20/2022]
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279
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Chennubhotla C, Clarke LP, Fedorov A, Foran D, Harris G, Helton E, Nordstrom R, Prior F, Rubin D, Saltz JH, Shalley E, Sharma A. An Assessment of Imaging Informatics for Precision Medicine in Cancer. Yearb Med Inform 2017; 26:110-119. [PMID: 29063549 DOI: 10.15265/iy-2017-041] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Objectives: Precision medicine requires the measurement, quantification, and cataloging of medical characteristics to identify the most effective medical intervention. However, the amount of available data exceeds our current capacity to extract meaningful information. We examine the informatics needs to achieve precision medicine from the perspective of quantitative imaging and oncology. Methods: The National Cancer Institute (NCI) organized several workshops on the topic of medical imaging and precision medicine. The observations and recommendations are summarized herein. Results: Recommendations include: use of standards in data collection and clinical correlates to promote interoperability; data sharing and validation of imaging tools; clinician's feedback in all phases of research and development; use of open-source architecture to encourage reproducibility and reusability; use of challenges which simulate real-world situations to incentivize innovation; partnership with industry to facilitate commercialization; and education in academic communities regarding the challenges involved with translation of technology from the research domain to clinical utility and the benefits of doing so. Conclusions: This article provides a survey of the role and priorities for imaging informatics to help advance quantitative imaging in the era of precision medicine. While these recommendations were drawn from oncology, they are relevant and applicable to other clinical domains where imaging aids precision medicine.
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280
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Bretas EAS, Torres US, Torres LR, Bekhor D, Saito Filho CF, Racy DJ, Faggioni L, D'Ippolito G. Is liver perfusion CT reproducible? A study on intra- and interobserver agreement of normal hepatic haemodynamic parameters obtained with two different software packages. Br J Radiol 2017; 90:20170214. [PMID: 28830195 DOI: 10.1259/bjr.20170214] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE To evaluate the agreement between the measurements of perfusion CT parameters in normal livers by using two different software packages. METHODS This retrospective study was based on 78 liver perfusion CT examinations acquired for detecting suspected liver metastasis. Patients with any morphological or functional hepatic abnormalities were excluded. The final analysis included 37 patients (59.7 ± 14.9 y). Two readers (1 and 2) independently measured perfusion parameters using different software packages from two major manufacturers (A and B). Arterial perfusion (AP) and portal perfusion (PP) were determined using the dual-input vascular one-compartmental model. Inter-reader agreement for each package and intrareader agreement between both packages were assessed with intraclass correlation coefficients (ICC) and Bland-Altman statistics. RESULTS Inter-reader agreement was substantial for AP using software A (ICC = 0.82) and B (ICC = 0.85-0.86), fair for PP using software A (ICC = 0.44) and fair to moderate for PP using software B (ICC = 0.56-0.77). Intrareader agreement between software A and B ranged from slight to moderate (ICC = 0.32-0.62) for readers 1 and 2 considering the AP parameters, and from fair to moderate (ICC = 0.40-0.69) for readers 1 and 2 considering the PP parameters. CONCLUSION At best there was only moderate agreement between both software packages, resulting in some uncertainty and suboptimal reproducibility. Advances in knowledge: Software-dependent factors may contribute to variance in perfusion measurements, demanding further technical improvements. AP measurements seem to be the most reproducible parameter to be adopted when evaluating liver perfusion CT.
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Affiliation(s)
- Elisa Almeida Sathler Bretas
- 1 Department of Imaging, Universidade Federal de São Paulo, São Paulo, Brazil.,2 Department of Radiology, Grupo Fleury, São Paulo, Brazil
| | | | - Lucas Rios Torres
- 2 Department of Radiology, Grupo Fleury, São Paulo, Brazil.,3 Department of Imaging, Hospital Beneficência Portuguesa, São Paulo, Brazil
| | - Daniel Bekhor
- 1 Department of Imaging, Universidade Federal de São Paulo, São Paulo, Brazil
| | | | - Douglas Jorge Racy
- 3 Department of Imaging, Hospital Beneficência Portuguesa, São Paulo, Brazil
| | - Lorenzo Faggioni
- 4 Department of Diagnostic and Interventional Radiology, University Hospital of Pisa, Pisa, Italy
| | - Giuseppe D'Ippolito
- 1 Department of Imaging, Universidade Federal de São Paulo, São Paulo, Brazil.,2 Department of Radiology, Grupo Fleury, São Paulo, Brazil
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281
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Winfield JM, Tunariu N, Rata M, Miyazaki K, Jerome NP, Germuska M, Blackledge MD, Collins DJ, de Bono JS, Yap TA, deSouza NM, Doran SJ, Koh DM, Leach MO, Messiou C, Orton MR. Extracranial Soft-Tissue Tumors: Repeatability of Apparent Diffusion Coefficient Estimates from Diffusion-weighted MR Imaging. Radiology 2017; 284:88-99. [PMID: 28301311 PMCID: PMC6063352 DOI: 10.1148/radiol.2017161965] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Purpose To assess the repeatability of apparent diffusion coefficient (ADC) estimates in extracranial soft-tissue diffusion-weighted magnetic resonance imaging across a wide range of imaging protocols and patient populations. Materials and Methods Nine prospective patient studies and one prospective volunteer study, performed between 2006 and 2016 with research ethics committee approval and written informed consent from each subject, were included in this single-institution study. A total of 141 tumors and healthy organs were imaged twice (interval between repeated examinations, 45 minutes to 10 days, depending the on study) to assess the repeatability of median and mean ADC estimates. The Levene test was used to determine whether ADC repeatability differed between studies. The Pearson linear correlation coefficient was used to assess correlation between coefficient of variation (CoV) and the year the study started, study size, and volumes of tumors and healthy organs. The repeatability of ADC estimates from small, medium, and large tumors and healthy organs was assessed irrespective of study, and the Levene test was used to determine whether ADC repeatability differed between these groups. Results CoV aggregated across all studies was 4.1% (range for each study, 1.7%-6.5%). No correlation was observed between CoV and the year the study started or study size. CoV was weakly correlated with volume (r = -0.5, P = .1). Repeatability was significantly different between small, medium, and large tumors (P < .05), with the lowest CoV (2.6%) for large tumors. There was a significant difference in repeatability between studies-a difference that did not persist after the study with the largest tumors was excluded. Conclusion ADC is a robust imaging metric with excellent repeatability in extracranial soft tissues across a wide range of tumor sites, sizes, patient populations, and imaging protocol variations. Online supplemental material is available for this article.
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Affiliation(s)
- Jessica M Winfield
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Nina Tunariu
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Mihaela Rata
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Keiko Miyazaki
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Neil P Jerome
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Michael Germuska
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Matthew D Blackledge
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - David J Collins
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Johann S de Bono
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Timothy A Yap
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Nandita M deSouza
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Simon J Doran
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Dow-Mu Koh
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Martin O Leach
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Christina Messiou
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
| | - Matthew R Orton
- From the Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Division of Clinical Studies (J.S.d.B., T.A.Y.), the Institute of Cancer Research and Royal Marsden Hospital, London, England; MRI Unit (J.M.W., N.T., M.R., K.M., N.P.J., M.G., M.D.B., D.J.C., N.M.d.S., S.J.D., D.M.K., M.O.L., C.M., M.R.O.) and Drug Development Unit (J.S.d.B., T.A.Y.), the Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT, England
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Golay X. The long and winding road to translation for imaging biomarker development: the case for arterial spin labelling (ASL). Eur Radiol Exp 2017; 1:3. [PMID: 29708177 PMCID: PMC5909337 DOI: 10.1186/s41747-017-0004-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Accepted: 03/16/2017] [Indexed: 12/19/2022] Open
Abstract
Radiology is facing many challenges nowadays, and certainly needs to keep up with the fast pace of developments taking place in this field. This editorial aims at drawing the attention of the reader to the current establishment of quantitative imaging biomarkers, in particular through the efforts of the Quantitative Imaging Biomarker Alliance (QIBA) from the Radiological Society of North America (RSNA), as well as the European Imaging Biomarker Alliance (EIBALL) from the European Society of Radiology (ESR). The case of arterial spin labelling (ASL) is used as an example of the long and winding road to translate a good imaging technique into a clinically relevant imaging biomarker.
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Affiliation(s)
- Xavier Golay
- UCL Institute of Neurology, Queen Square 8-11, London, WC1N 3BG UK
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283
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J P Bray T, Vendhan K, Ambrose N, Atkinson D, Punwani S, Fisher C, Sen D, Ioannou Y, Hall-Craggs MA. Diffusion-weighted imaging is a sensitive biomarker of response to biologic therapy in enthesitis-related arthritis. Rheumatology (Oxford) 2017; 56:399-407. [PMID: 27994095 DOI: 10.1093/rheumatology/kew429] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Indexed: 11/14/2022] Open
Abstract
Objective The aim was to evaluate diffusion-weighted imaging (DWI) as a tool for measuring treatment response in adolescents with enthesitis-related arthropathy (ERA). Methods Twenty-two adolescents with ERA underwent routine MRI and DWI before and after TNF inhibitor therapy. Each patient's images were visually scored by two radiologists using the Spondyloarthritis Research Consortium of Canada system, and sacroiliac joint apparent diffusion coefficient (ADC) and normalized ADC (nADC) were measured for each patient. Therapeutic clinical response was defined as an improvement of ⩾ 30% physician global assessment and radiological response defined as ⩾ 2.5-point reduction in Spondyloarthritis Research Consortium of Canada score. We compared ADC and nADC changes in responders and non-responders using the Mann-Whitney-Wilcoxon test. Results For both radiological and clinical definitions of response, reductions in ADC and nADC after treatment were greater in responders than in non-responders (for radiological response: ADC: P < 0.01; nADC: P = 0.055; for clinical response: ADC: P = 0.33; nADC: P = 0.089). ADC and nADC could predict radiological response with a high level of sensitivity and specificity and were moderately sensitive and specific predictors of clinical response (the area under the receiver operating characteristic curves were as follows: ADC: 0.97, nADC: 0.82 for radiological response; and ADC: 0.67, nADC: 0.78 for clinical response). Conclusion DWI measurements reflect the response to TNF inhibitor treatment in ERA patients with sacroiliitis as defined using radiological criteria and may also reflect clinical response. DWI is more objective than visual scoring and has the potential to be automated. ADC/nADC could be used as biomarkers of sacroiliitis in the clinic and in clinical trials.
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Affiliation(s)
- Timothy J P Bray
- University College London Centre for Medical Imaging (Academic Radiology), NW1 2PG.,Arthritis Research UK Centre for Adolescent Rheumatology, University College London, London
| | - Kanimozhi Vendhan
- University College London Centre for Medical Imaging (Academic Radiology), NW1 2PG
| | - Nicola Ambrose
- Arthritis Research UK Centre for Adolescent Rheumatology, University College London, London
| | - David Atkinson
- University College London Centre for Medical Imaging (Academic Radiology), NW1 2PG
| | - Shonit Punwani
- University College London Centre for Medical Imaging (Academic Radiology), NW1 2PG
| | - Corinne Fisher
- Arthritis Research UK Centre for Adolescent Rheumatology, University College London, London
| | - Debajit Sen
- Arthritis Research UK Centre for Adolescent Rheumatology, University College London, London
| | - Yiannis Ioannou
- Arthritis Research UK Centre for Adolescent Rheumatology, University College London, London
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Eikefjord E, Andersen E, Hodneland E, Hanson EA, Sourbron S, Svarstad E, Lundervold A, Rørvik JT. Dynamic contrast-enhanced MRI measurement of renal function in healthy participants. Acta Radiol 2017; 58:748-757. [PMID: 27694276 DOI: 10.1177/0284185116666417] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background High repeatability, accuracy, and precision for renal function measurements need to be achieved to establish renal dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a clinically useful diagnostic tool. Purpose To investigate the repeatability, accuracy, and precision of DCE-MRI measured renal perfusion and glomerular filtration rate (GFR) using iohexol-GFR as the reference method. Material and Methods Twenty healthy non-smoking volunteers underwent repeated DCE-MRI and an iohexol-GFR within a period of 10 days. Single-kidney (SK) MRI measurements of perfusion (blood flow, Fb) and filtration (GFR) were derived from parenchymal intensity time curves fitted to a two-compartment filtration model. The repeatability of the SK-MRI measurements was assessed using coefficient of variation (CV). Using iohexol-GFR as reference method, the accuracy of total MR-GFR was determined by mean difference (MD) and precision by limits of agreement (LoA). Results SK-Fb (MR1, 345 ± 84; MR2, 371 ± 103 mL/100 mL/min) and SK-GFR (MR1, 52 ± 14; MR2, 54 ± 10 mL/min/1.73 m2) measurements achieved a repeatability (CV) in the range of 15-22%. With reference to iohexol-GFR, MR-GFR was determined with a low mean difference but high LoA (MR1, MD 1.5 mL/min/1.73 m2, LoA [-42, 45]; MR2, MD 6.1 mL/min/1.73 m2, LoA [-26, 38]). Eighty percent and 90% of MR-GFR measurements were determined within ± 30% of the iohexol-GFR for MR1 and MR2, respectively. Conclusion Good repeatability of SK-MRI measurements and good agreement between MR-GFR and iohexol-GFR provide a high clinical potential of DCE-MRI for renal function assessment. A moderate precision in MR-derived estimates indicates that the method cannot yet be used in clinical routine.
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Affiliation(s)
- Eli Eikefjord
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Erling Andersen
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Erlend Hodneland
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Christian Michelsen Research (CMR) AS, Bergen, Norway
| | - Erik A Hanson
- Department of Mathematics, University of Bergen, Bergen, Norway
| | - Steven Sourbron
- Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - Einar Svarstad
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Department of Medicine, Haukeland University Hospital, Bergen, Norway
| | - Arvid Lundervold
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Jarle T Rørvik
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
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DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic. Top Magn Reson Imaging 2017; 25:245-254. [PMID: 27748710 PMCID: PMC5081190 DOI: 10.1097/rmr.0000000000000103] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Multi-parametric magnetic resonance imaging (mpMRI) offers a unique insight into tumor biology by combining functional MRI techniques that inform on cellularity (diffusion-weighted MRI), vascular properties (dynamic contrast-enhanced MRI), and metabolites (magnetic resonance spectroscopy) and has scope to provide valuable information for prognostication and response assessment. Challenges in the application of mpMRI in the clinic include the technical considerations in acquiring good quality functional MRI data, development of robust techniques for analysis, and clinical interpretation of the results. This article summarizes the technical challenges in acquisition and analysis of multi-parametric MRI data before reviewing the key applications of multi-parametric MRI in clinical research and practice.
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Töger J, Sorensen T, Somandepalli K, Toutios A, Lingala SG, Narayanan S, Nayak K. Test-retest repeatability of human speech biomarkers from static and real-time dynamic magnetic resonance imaging. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2017; 141:3323. [PMID: 28599561 PMCID: PMC5436977 DOI: 10.1121/1.4983081] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Static anatomical and real-time dynamic magnetic resonance imaging (RT-MRI) of the upper airway is a valuable method for studying speech production in research and clinical settings. The test-retest repeatability of quantitative imaging biomarkers is an important parameter, since it limits the effect sizes and intragroup differences that can be studied. Therefore, this study aims to present a framework for determining the test-retest repeatability of quantitative speech biomarkers from static MRI and RT-MRI, and apply the framework to healthy volunteers. Subjects (n = 8, 4 females, 4 males) are imaged in two scans on the same day, including static images and dynamic RT-MRI of speech tasks. The inter-study agreement is quantified using intraclass correlation coefficient (ICC) and mean within-subject standard deviation (σe). Inter-study agreement is strong to very strong for static measures (ICC: min/median/max 0.71/0.89/0.98, σe: 0.90/2.20/6.72 mm), poor to strong for dynamic RT-MRI measures of articulator motion range (ICC: 0.26/0.75/0.90, σe: 1.6/2.5/3.6 mm), and poor to very strong for velocities (ICC: 0.21/0.56/0.93, σe: 2.2/4.4/16.7 cm/s). In conclusion, this study characterizes repeatability of static and dynamic MRI-derived speech biomarkers using state-of-the-art imaging. The introduced framework can be used to guide future development of speech biomarkers. Test-retest MRI data are provided free for research use.
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Affiliation(s)
- Johannes Töger
- Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Avenue, EEB 400, Los Angeles, California 90089-2560, USA
| | - Tanner Sorensen
- Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Avenue, EEB 400, Los Angeles, California 90089-2560, USA
| | - Krishna Somandepalli
- Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Avenue, EEB 400, Los Angeles, California 90089-2560, USA
| | - Asterios Toutios
- Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Avenue, EEB 400, Los Angeles, California 90089-2560, USA
| | - Sajan Goud Lingala
- Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Avenue, EEB 400, Los Angeles, California 90089-2560, USA
| | - Shrikanth Narayanan
- Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Avenue, EEB 400, Los Angeles, California 90089-2560, USA
| | - Krishna Nayak
- Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Avenue, EEB 400, Los Angeles, California 90089-2560, USA
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Quantitative effects of acquisition duration and temporal resolution on the measurement accuracy of prostate dynamic contrast-enhanced MRI data: a phantom study. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2017; 30:461-471. [DOI: 10.1007/s10334-017-0619-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Revised: 03/31/2017] [Accepted: 04/03/2017] [Indexed: 10/19/2022]
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Abstract
There is interest in identifying and quantifying tumor heterogeneity at the genomic, tissue pathology and clinical imaging scales, as this may help better understand tumor biology and may yield useful biomarkers for guiding therapy-based decision making. This review focuses on the role and value of using x-ray, CT, MRI and PET based imaging methods that identify, measure and map tumor heterogeneity. In particular we highlight the potential value of these techniques and the key challenges required to validate and qualify these biomarkers for clinical use.
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Affiliation(s)
- James P B O'Connor
- Institute of Cancer Sciences, University of Manchester, Manchester, UK; Department of Radiology, The Christie Hospital NHS Trust, Manchester, UK.
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Zhang J, Liu H, Tong H, Wang S, Yang Y, Liu G, Zhang W. Clinical Applications of Contrast-Enhanced Perfusion MRI Techniques in Gliomas: Recent Advances and Current Challenges. CONTRAST MEDIA & MOLECULAR IMAGING 2017; 2017:7064120. [PMID: 29097933 PMCID: PMC5612612 DOI: 10.1155/2017/7064120] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 02/23/2017] [Indexed: 01/12/2023]
Abstract
Gliomas possess complex and heterogeneous vasculatures with abnormal hemodynamics. Despite considerable advances in diagnostic and therapeutic techniques for improving tumor management and patient care in recent years, the prognosis of malignant gliomas remains dismal. Perfusion-weighted magnetic resonance imaging techniques that could noninvasively provide superior information on vascular functionality have attracted much attention for evaluating brain tumors. However, nonconsensus imaging protocols and postprocessing analysis among different institutions impede their integration into standard-of-care imaging in clinic. And there have been very few studies providing a comprehensive evidence-based and systematic summary. This review first outlines the status of glioma theranostics and tumor-associated vascular pathology and then presents an overview of the principles of dynamic contrast-enhanced MRI (DCE-MRI) and dynamic susceptibility contrast-MRI (DSC-MRI), with emphasis on their recent clinical applications in gliomas including tumor grading, identification of molecular characteristics, differentiation of glioma from other brain tumors, treatment response assessment, and predicting prognosis. Current challenges and future perspectives are also highlighted.
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Affiliation(s)
- Junfeng Zhang
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing 400042, China
| | - Heng Liu
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing 400042, China
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics & Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen 361102, China
| | - Haipeng Tong
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing 400042, China
| | - Sumei Wang
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Yizeng Yang
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Gang Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics & Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen 361102, China
| | - Weiguo Zhang
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing 400042, China
- Chongqing Clinical Research Center for Imaging and Nuclear Medicine, Chongqing 400042, China
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291
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O'Connor JPB, Aboagye EO, Adams JE, Aerts HJWL, Barrington SF, Beer AJ, Boellaard R, Bohndiek SE, Brady M, Brown G, Buckley DL, Chenevert TL, Clarke LP, Collette S, Cook GJ, deSouza NM, Dickson JC, Dive C, Evelhoch JL, Faivre-Finn C, Gallagher FA, Gilbert FJ, Gillies RJ, Goh V, Griffiths JR, Groves AM, Halligan S, Harris AL, Hawkes DJ, Hoekstra OS, Huang EP, Hutton BF, Jackson EF, Jayson GC, Jones A, Koh DM, Lacombe D, Lambin P, Lassau N, Leach MO, Lee TY, Leen EL, Lewis JS, Liu Y, Lythgoe MF, Manoharan P, Maxwell RJ, Miles KA, Morgan B, Morris S, Ng T, Padhani AR, Parker GJM, Partridge M, Pathak AP, Peet AC, Punwani S, Reynolds AR, Robinson SP, Shankar LK, Sharma RA, Soloviev D, Stroobants S, Sullivan DC, Taylor SA, Tofts PS, Tozer GM, van Herk M, Walker-Samuel S, Wason J, Williams KJ, Workman P, Yankeelov TE, Brindle KM, McShane LM, Jackson A, Waterton JC. Imaging biomarker roadmap for cancer studies. Nat Rev Clin Oncol 2017; 14:169-186. [PMID: 27725679 PMCID: PMC5378302 DOI: 10.1038/nrclinonc.2016.162] [Citation(s) in RCA: 740] [Impact Index Per Article: 92.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.
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Affiliation(s)
- James P B O'Connor
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Eric O Aboagye
- Department of Surgery and Cancer, Imperial College, London, UK
| | - Judith E Adams
- Department of Clinical Radiology, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Hugo J W L Aerts
- Department of Radiation Oncology, Harvard Medical School, Boston, MA
| | - Sally F Barrington
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - Ambros J Beer
- Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany
| | - Ronald Boellaard
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands
| | - Sarah E Bohndiek
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Michael Brady
- CRUK and EPSRC Cancer Imaging Centre, University of Oxford, Oxford, UK
| | - Gina Brown
- Radiology Department, Royal Marsden Hospital, London, UK
| | - David L Buckley
- Division of Biomedical Imaging, University of Leeds, Leeds, UK
| | | | | | | | - Gary J Cook
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - Nandita M deSouza
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | - John C Dickson
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Caroline Dive
- Clinical and Experimental Pharmacology, CRUK Manchester Institute, Manchester, UK
| | | | - Corinne Faivre-Finn
- Radiotherapy Related Research Group, University of Manchester, Manchester, UK
| | - Ferdia A Gallagher
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Fiona J Gilbert
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | | | - Vicky Goh
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - John R Griffiths
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Ashley M Groves
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Steve Halligan
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Adrian L Harris
- CRUK and EPSRC Cancer Imaging Centre, University of Oxford, Oxford, UK
| | - David J Hawkes
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Otto S Hoekstra
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
| | - Erich P Huang
- Biometric Research Program, National Cancer Institute, Bethesda, MD
| | - Brian F Hutton
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Edward F Jackson
- Department of Medical Physics, University of Wisconsin, Madison, WI
| | - Gordon C Jayson
- Institute of Cancer Sciences, University of Manchester, Manchester, UK
| | - Andrew Jones
- Medical Physics, The Christie Hospital NHS Foundation Trust, Manchester, UK
| | - Dow-Mu Koh
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | | | - Philippe Lambin
- Department of Radiation Oncology, University of Maastricht, Maastricht, Netherlands
| | - Nathalie Lassau
- Department of Imaging, Gustave Roussy Cancer Campus, Villejuif, France
| | - Martin O Leach
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | - Ting-Yim Lee
- Imaging Research Labs, Robarts Research Institute, London, Ontario, Canada
| | - Edward L Leen
- Department of Surgery and Cancer, Imperial College, London, UK
| | - Jason S Lewis
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Yan Liu
- EORTC Headquarters, EORTC, Brussels, Belgium
| | - Mark F Lythgoe
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Prakash Manoharan
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Ross J Maxwell
- Northern Institute for Cancer Research, Newcastle University, Newcastle, UK
| | - Kenneth A Miles
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Bruno Morgan
- Cancer Studies and Molecular Medicine, University of Leicester, Leicester, UK
| | - Steve Morris
- Institute of Epidemiology and Health, University College London, London, UK
| | - Tony Ng
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - Anwar R Padhani
- Paul Strickland Scanner Centre, Mount Vernon Hospital, London, UK
| | - Geoff J M Parker
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Mike Partridge
- CRUK and EPSRC Cancer Imaging Centre, University of Oxford, Oxford, UK
| | - Arvind P Pathak
- Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Andrew C Peet
- Institute of Cancer and Genomics, University of Birmingham, Birmingham, UK
| | - Shonit Punwani
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Andrew R Reynolds
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK
| | - Simon P Robinson
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | | | - Ricky A Sharma
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Dmitry Soloviev
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Sigrid Stroobants
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Daniel C Sullivan
- Department of Radiology, Duke University School of Medicine, Durham, NC
| | - Stuart A Taylor
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Paul S Tofts
- Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Gillian M Tozer
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
| | - Marcel van Herk
- Radiotherapy Related Research Group, University of Manchester, Manchester, UK
| | - Simon Walker-Samuel
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | | | - Kaye J Williams
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Paul Workman
- CRUK Cancer Therapeutics Unit, The Institute of Cancer Research, London, UK
| | - Thomas E Yankeelov
- Institute of Computational Engineering and Sciences, The University of Texas, Austin, TX
| | - Kevin M Brindle
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Lisa M McShane
- Biometric Research Program, National Cancer Institute, Bethesda, MD
| | - Alan Jackson
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - John C Waterton
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
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Obuchowski NA, Bullen J. Quantitative imaging biomarkers: Effect of sample size and bias on confidence interval coverage. Stat Methods Med Res 2017; 27:3139-3150. [PMID: 29298603 DOI: 10.1177/0962280217693662] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Introduction Quantitative imaging biomarkers (QIBs) are being increasingly used in medical practice and clinical trials. An essential first step in the adoption of a quantitative imaging biomarker is the characterization of its technical performance, i.e. precision and bias, through one or more performance studies. Then, given the technical performance, a confidence interval for a new patient's true biomarker value can be constructed. Estimating bias and precision can be problematic because rarely are both estimated in the same study, precision studies are usually quite small, and bias cannot be measured when there is no reference standard. Methods A Monte Carlo simulation study was conducted to assess factors affecting nominal coverage of confidence intervals for a new patient's quantitative imaging biomarker measurement and for change in the quantitative imaging biomarker over time. Factors considered include sample size for estimating bias and precision, effect of fixed and non-proportional bias, clustered data, and absence of a reference standard. Results Technical performance studies of a quantitative imaging biomarker should include at least 35 test-retest subjects to estimate precision and 65 cases to estimate bias. Confidence intervals for a new patient's quantitative imaging biomarker measurement constructed under the no-bias assumption provide nominal coverage as long as the fixed bias is <12%. For confidence intervals of the true change over time, linearity must hold and the slope of the regression of the measurements vs. true values should be between 0.95 and 1.05. The regression slope can be assessed adequately as long as fixed multiples of the measurand can be generated. Even small non-proportional bias greatly reduces confidence interval coverage. Multiple lesions in the same subject can be treated as independent when estimating precision. Conclusion Technical performance studies of quantitative imaging biomarkers require moderate sample sizes in order to provide robust estimates of bias and precision for constructing confidence intervals for new patients. Assumptions of linearity and non-proportional bias should be assessed thoroughly.
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Affiliation(s)
- Nancy A Obuchowski
- Quantitative Health Sciences /JJN3, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Jennifer Bullen
- Quantitative Health Sciences /JJN3, Cleveland Clinic Foundation, Cleveland, OH, USA
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293
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Ryu J, Jeong WK. Current status of musculoskeletal application of shear wave elastography. Ultrasonography 2017; 36:185-197. [PMID: 28292005 PMCID: PMC5494870 DOI: 10.14366/usg.16053] [Citation(s) in RCA: 120] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Revised: 02/03/2017] [Accepted: 02/04/2017] [Indexed: 12/31/2022] Open
Abstract
Ultrasonography (US) is a very powerful diagnostic modality for the musculoskeletal system due to the ability to perform real-time dynamic high-resolution examinations with the Doppler technique. In addition to acquiring morphologic data, we can now obtain biomechanical information by quantifying the elasticity of the musculoskeletal structures with US elastography. The earlier diagnosis of degeneration and the ability to perform follow-up evaluations of healing and the effects of treatment are possible. US elastography enables a transition from US-based inspection to US-based palpation in order to diagnose the characteristics of tissue. Shear wave elastography is considered the most suitable type of US elastography for the musculoskeletal system. It is widely used for tendons, ligaments, and muscles. It is important to understand practice guidelines in order to enhance reproducibility. Incorporating viscoelasticity and overcoming inconsistencies among manufacturers are future tasks for improving the capabilities of US elastography.
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Affiliation(s)
- JeongAh Ryu
- Department of Radiology, Hanyang University Guri Hospital, Hanyang University School of Medicine, Guri, Korea
| | - Woo Kyoung Jeong
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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294
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Bignotti B, Signori A, Valdora F, Rossi F, Calabrese M, Durando M, Mariscotto G, Tagliafico A. Evaluation of background parenchymal enhancement on breast MRI: a systematic review. Br J Radiol 2017; 90:20160542. [PMID: 27925480 PMCID: PMC5685112 DOI: 10.1259/bjr.20160542] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Revised: 11/18/2016] [Accepted: 12/05/2016] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE To perform a systematic review of the methods used for background parenchymal enhancement (BPE) evaluation on breast MRI. METHODS Studies dealing with BPE assessment on breast MRI were retrieved from major medical libraries independently by four reviewers up to 6 October 2015. The keywords used for database searching are "background parenchymal enhancement", "parenchymal enhancement", "MRI" and "breast". The studies were included if qualitative and/or quantitative methods for BPE assessment were described. RESULTS Of the 420 studies identified, a total of 52 articles were included in the systematic review. 28 studies performed only a qualitative assessment of BPE, 13 studies performed only a quantitative assessment and 11 studies performed both qualitative and quantitative assessments. A wide heterogeneity was found in the MRI sequences and in the quantitative methods used for BPE assessment. CONCLUSION A wide variability exists in the quantitative evaluation of BPE on breast MRI. More studies focused on a reliable and comparable method for quantitative BPE assessment are needed. Advances in knowledge: More studies focused on a quantitative BPE assessment are needed.
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Affiliation(s)
- Bianca Bignotti
- Department of Health Sciences, Institute of Statistics, University of Genoa, Genoa, Italy
| | - Alessio Signori
- Department of Experimental Medicine, Institute of Anatomy, University of Genoa, Genoa, Italy
| | | | - Federica Rossi
- Department of Health Sciences, University of Genova, Genoa, Italy
| | - Massimo Calabrese
- IRCCS AOU San Martino - IST Istituto Nazionale per la Ricerca sul Cancro, Genova, Italy
| | - Manuela Durando
- Department of Diagnostic Imaging and Radiotherapy, AOU Città della Salute e della Scienza of Turin, Breast Imaging Service, Division of Radiology, University of Turin, Turin, Italy
| | - Giovanna Mariscotto
- Department of Diagnostic Imaging and Radiotherapy, AOU Città della Salute e della Scienza of Turin, Breast Imaging Service, Division of Radiology, University of Turin, Turin, Italy
| | - Alberto Tagliafico
- Department of Experimental Medicine, Institute of Anatomy, University of Genoa, Genoa, Italy
- IRCCS AOU San Martino - IST Istituto Nazionale per la Ricerca sul Cancro, Genova, Italy
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295
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Priola AM, Priola SM, Gned D, Giraudo MT, Brundu M, Righi L, Veltri A. Diffusion-weighted quantitative MRI of pleural abnormalities: Intra- and interobserver variability in the apparent diffusion coefficient measurements. J Magn Reson Imaging 2017; 46:769-782. [PMID: 28117923 DOI: 10.1002/jmri.25633] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 12/28/2016] [Indexed: 12/14/2022] Open
Abstract
PURPOSE To assess intra- and interobserver variability in the apparent diffusion coefficient (ADC) measurements of pleural abnormalities. MATERIALS AND METHODS Diffusion-weighted magnetic resonance imaging was performed in 34 patients to characterize pleural abnormalities, with a 1.5T unit at b values of 0/150/500/800 sec/mm2 . In two sessions held 3 months apart, on perfusion-free ADC maps, two independent readers measured the ADC of pleural abnormalities (two readings for each reader in each case) using different methods of region-of-interest (ROI) positioning. In three methods, freehand ROIs were drawn within tumor boundaries to encompass the entire lesion on one or more axial slices (whole tumor volume [WTV], three slices observer-defined [TSOD], single-slice [SS]), while in two methods one or more ROIs were placed on the more restricted areas (multiple small round ROI [MSR], one small round ROI [OSR]). Measurement variability between readings by each reader (intraobserver repeatability) and between readers in first reading (interobserver repeatability) were assessed using intraclass correlation coefficient (ICC) and coefficient of variation (CoV). Analysis of variance (ANOVA) was performed to compare ADC values between the different methods. The measurement time of each case for all methods in first reading was recorded and compared between methods and readers. RESULTS All methods demonstrated good (MSR, OSR) and excellent (WTV, TSOD, SS) intra- and interreader agreement, with best and worst repeatability in WTV (lower ICC, 0.977; higher CoV, 3.5%) and OSR (lower ICC, 0.625; higher CoV, 22.8%), respectively. The lower 95% confidence interval of ICC resulted in fair to moderate agreement for OSR (up to 0.379) and in excellent agreement for WTV, TSV, and SS (up to 0.918). ADC values of OSR and MSR were significantly lower compared to other methods (P < 0.001). The OSR and SS required less measurement time (10 and 21/22 sec, respectively) compared to the others (P < 0.0001), while the WTV required the longest measurement time (132/134 sec) (P < 0.0001). CONCLUSION ADC measurements of pleural abnormalities are repeatable. The SS method has excellent repeatability, similar to WTV, but requires significantly less measurement time. Thus, its use should be preferred in clinical practice. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:769-782.
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Affiliation(s)
| | - Sandro Massimo Priola
- Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Orbassano (Torino), Italy
| | - Dario Gned
- Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Orbassano (Torino), Italy
| | | | - Maria Brundu
- Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Orbassano (Torino), Italy
| | - Luisella Righi
- Department of Pathology, San Luigi Gonzaga University Hospital, Orbassano (Torino), Italy
| | - Andrea Veltri
- Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Orbassano (Torino), Italy
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296
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Oei EHG. Quantitative musculoskeletal imaging biomarkers. Quant Imaging Med Surg 2017; 6:621-622. [PMID: 28090440 DOI: 10.21037/qims.2016.12.15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Edwin H G Oei
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center, 's-Gravendijkwal 230, 3015 CE Rotterdam, The Netherlands.
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Kishimoto R, Suga M, Koyama A, Omatsu T, Tachibana Y, Ebner DK, Obata T. Measuring shear-wave speed with point shear-wave elastography and MR elastography: a phantom study. BMJ Open 2017; 7:e013925. [PMID: 28057657 PMCID: PMC5223661 DOI: 10.1136/bmjopen-2016-013925] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVES To compare shear-wave speed (SWS) measured by ultrasound-based point shear-wave elastography (pSWE) and MR elastography (MRE) on phantoms with a known shear modulus, and to assess method validity and variability. METHODS 5 homogeneous phantoms of different stiffnesses were made. Shear modulus was measured by a rheometer, and this value was used as the standard. 10 SWS measurements were obtained at 4 different depths with 1.0-4.5 MHz convex (4C1) and 4.0-9.0 MHz linear (9L4) transducers using pSWE. MRE was carried out once per phantom, and SWSs at 5 different depths were obtained. These SWSs were then compared with those from a rheometer using linear regression analyses. RESULTS SWSs obtained with both pSWE as well as MRE had a strong correlation with those obtained by a rheometer (R2>0.97). The relative difference in SWS between the procedures was from -25.2% to 25.6% for all phantoms, and from -8.1% to 6.9% when the softest and hardest phantoms were excluded. Depth dependency was noted in the 9L4 transducer of pSWE and MRE. CONCLUSIONS SWSs from pSWE and MRE showed a good correlation with a rheometer-determined SWS. Although based on phantom studies, SWSs obtained with these methods are not always equivalent, the measurement can be thought of as reliable and these SWSs were reasonably close to each other for the middle range of stiffness within the measurable range.
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Affiliation(s)
- Riwa Kishimoto
- Hospital of the National Institute of Radiological Sciences, National Institutes of Quantum and Radiation Science and Technology, Chiba, Japan
| | - Mikio Suga
- Center for Frontier Medical Engineering, Chiba University, Chiba, Japan
| | - Atsuhisa Koyama
- Center for Frontier Medical Engineering, Chiba University, Chiba, Japan
| | - Tokuhiko Omatsu
- Hospital of the National Institute of Radiological Sciences, National Institutes of Quantum and Radiation Science and Technology, Chiba, Japan
| | - Yasuhiko Tachibana
- Hospital of the National Institute of Radiological Sciences, National Institutes of Quantum and Radiation Science and Technology, Chiba, Japan
| | - Daniel K Ebner
- Hospital of the National Institute of Radiological Sciences, National Institutes of Quantum and Radiation Science and Technology, Chiba, Japan
| | - Takayuki Obata
- Hospital of the National Institute of Radiological Sciences, National Institutes of Quantum and Radiation Science and Technology, Chiba, Japan
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Hatt M, Tixier F, Pierce L, Kinahan PE, Le Rest CC, Visvikis D. Characterization of PET/CT images using texture analysis: the past, the present… any future? Eur J Nucl Med Mol Imaging 2017; 44:151-165. [PMID: 27271051 PMCID: PMC5283691 DOI: 10.1007/s00259-016-3427-0] [Citation(s) in RCA: 342] [Impact Index Per Article: 42.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Accepted: 05/18/2016] [Indexed: 02/07/2023]
Abstract
After seminal papers over the period 2009 - 2011, the use of texture analysis of PET/CT images for quantification of intratumour uptake heterogeneity has received increasing attention in the last 4 years. Results are difficult to compare due to the heterogeneity of studies and lack of standardization. There are also numerous challenges to address. In this review we provide critical insights into the recent development of texture analysis for quantifying the heterogeneity in PET/CT images, identify issues and challenges, and offer recommendations for the use of texture analysis in clinical research. Numerous potentially confounding issues have been identified, related to the complex workflow for the calculation of textural features, and the dependency of features on various factors such as acquisition, image reconstruction, preprocessing, functional volume segmentation, and methods of establishing and quantifying correspondences with genomic and clinical metrics of interest. A lack of understanding of what the features may represent in terms of the underlying pathophysiological processes and the variability of technical implementation practices makes comparing results in the literature challenging, if not impossible. Since progress as a field requires pooling results, there is an urgent need for standardization and recommendations/guidelines to enable the field to move forward. We provide a list of correct formulae for usual features and recommendations regarding implementation. Studies on larger cohorts with robust statistical analysis and machine learning approaches are promising directions to evaluate the potential of this approach.
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Affiliation(s)
- Mathieu Hatt
- INSERM, UMR 1101, LaTIM, University of Brest IBSAM, Brest, France.
| | - Florent Tixier
- Nuclear Medicine, University Hospital, Poitiers, France
- Medical school, EE DACTIM, University of Poitiers, Poitiers, France
| | - Larry Pierce
- Imaging Research Laboratory, University of Washington, Seattle, WA, USA
| | - Paul E Kinahan
- Imaging Research Laboratory, University of Washington, Seattle, WA, USA
| | - Catherine Cheze Le Rest
- Nuclear Medicine, University Hospital, Poitiers, France
- Medical school, EE DACTIM, University of Poitiers, Poitiers, France
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Kubo T, Ohno Y, Seo JB, Yamashiro T, Kalender WA, Lee CH, Lynch DA, Kauczor HU, Hatabu H. Securing safe and informative thoracic CT examinations—Progress of radiation dose reduction techniques. Eur J Radiol 2017; 86:313-319. [DOI: 10.1016/j.ejrad.2016.10.012] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Revised: 10/08/2016] [Accepted: 10/12/2016] [Indexed: 12/16/2022]
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300
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Rocca MA, Battaglini M, Benedict RHB, De Stefano N, Geurts JJG, Henry RG, Horsfield MA, Jenkinson M, Pagani E, Filippi M. Brain MRI atrophy quantification in MS: From methods to clinical application. Neurology 2016; 88:403-413. [PMID: 27986875 DOI: 10.1212/wnl.0000000000003542] [Citation(s) in RCA: 188] [Impact Index Per Article: 20.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2016] [Accepted: 10/18/2016] [Indexed: 01/06/2023] Open
Abstract
Patients with the main clinical phenotypes of multiple sclerosis (MS) manifest varying degrees of brain atrophy beyond that of normal aging. Assessment of atrophy helps to distinguish clinically and cognitively deteriorating patients and predicts those who will have a less-favorable clinical outcome over the long term. Atrophy can be measured from brain MRI scans, and many technological improvements have been made over the last few years. Several software tools, with differing requirements on technical ability and levels of operator intervention, are currently available and have already been applied in research or clinical trial settings. Despite this, the measurement of atrophy in routine clinical practice remains an unmet need. After a short summary of the pathologic substrates of brain atrophy in MS, this review attempts to guide the clinician towards a better understanding of the methods currently used for quantifying brain atrophy in this condition. Important physiologic factors that affect brain volume measures are also considered. Finally, the most recent research on brain atrophy in MS is summarized, including whole brain and various compartments thereof (i.e., white matter, gray matter, selected CNS structures). Current methods provide sufficient precision for cohort studies, but are not adequate for confidently assessing changes in individual patients over the scale of months or a few years.
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Affiliation(s)
- Maria A Rocca
- From the Neuroimaging Research Unit (M.A.R., E.P., M.F.), Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan; Department of Medicine, Surgery and Neuroscience (M.B., N.D.S.), University of Siena, Italy; Department of Neurology (R.H.B.B.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York; Department of Anatomy and Neuroscience (J.J.G.G.), Section of Clinical Neuroscience, VUmc MS Center Amsterdam, VU University Medical Center, the Netherlands; Department of Neurology (R.G.H.), University of California, San Francisco; Xinapse Systems Ltd. (M.A.H.), Colchester, Essex, UK; and FMRIB Centre (M.J.), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Marco Battaglini
- From the Neuroimaging Research Unit (M.A.R., E.P., M.F.), Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan; Department of Medicine, Surgery and Neuroscience (M.B., N.D.S.), University of Siena, Italy; Department of Neurology (R.H.B.B.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York; Department of Anatomy and Neuroscience (J.J.G.G.), Section of Clinical Neuroscience, VUmc MS Center Amsterdam, VU University Medical Center, the Netherlands; Department of Neurology (R.G.H.), University of California, San Francisco; Xinapse Systems Ltd. (M.A.H.), Colchester, Essex, UK; and FMRIB Centre (M.J.), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Ralph H B Benedict
- From the Neuroimaging Research Unit (M.A.R., E.P., M.F.), Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan; Department of Medicine, Surgery and Neuroscience (M.B., N.D.S.), University of Siena, Italy; Department of Neurology (R.H.B.B.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York; Department of Anatomy and Neuroscience (J.J.G.G.), Section of Clinical Neuroscience, VUmc MS Center Amsterdam, VU University Medical Center, the Netherlands; Department of Neurology (R.G.H.), University of California, San Francisco; Xinapse Systems Ltd. (M.A.H.), Colchester, Essex, UK; and FMRIB Centre (M.J.), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Nicola De Stefano
- From the Neuroimaging Research Unit (M.A.R., E.P., M.F.), Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan; Department of Medicine, Surgery and Neuroscience (M.B., N.D.S.), University of Siena, Italy; Department of Neurology (R.H.B.B.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York; Department of Anatomy and Neuroscience (J.J.G.G.), Section of Clinical Neuroscience, VUmc MS Center Amsterdam, VU University Medical Center, the Netherlands; Department of Neurology (R.G.H.), University of California, San Francisco; Xinapse Systems Ltd. (M.A.H.), Colchester, Essex, UK; and FMRIB Centre (M.J.), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Jeroen J G Geurts
- From the Neuroimaging Research Unit (M.A.R., E.P., M.F.), Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan; Department of Medicine, Surgery and Neuroscience (M.B., N.D.S.), University of Siena, Italy; Department of Neurology (R.H.B.B.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York; Department of Anatomy and Neuroscience (J.J.G.G.), Section of Clinical Neuroscience, VUmc MS Center Amsterdam, VU University Medical Center, the Netherlands; Department of Neurology (R.G.H.), University of California, San Francisco; Xinapse Systems Ltd. (M.A.H.), Colchester, Essex, UK; and FMRIB Centre (M.J.), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Roland G Henry
- From the Neuroimaging Research Unit (M.A.R., E.P., M.F.), Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan; Department of Medicine, Surgery and Neuroscience (M.B., N.D.S.), University of Siena, Italy; Department of Neurology (R.H.B.B.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York; Department of Anatomy and Neuroscience (J.J.G.G.), Section of Clinical Neuroscience, VUmc MS Center Amsterdam, VU University Medical Center, the Netherlands; Department of Neurology (R.G.H.), University of California, San Francisco; Xinapse Systems Ltd. (M.A.H.), Colchester, Essex, UK; and FMRIB Centre (M.J.), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Mark A Horsfield
- From the Neuroimaging Research Unit (M.A.R., E.P., M.F.), Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan; Department of Medicine, Surgery and Neuroscience (M.B., N.D.S.), University of Siena, Italy; Department of Neurology (R.H.B.B.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York; Department of Anatomy and Neuroscience (J.J.G.G.), Section of Clinical Neuroscience, VUmc MS Center Amsterdam, VU University Medical Center, the Netherlands; Department of Neurology (R.G.H.), University of California, San Francisco; Xinapse Systems Ltd. (M.A.H.), Colchester, Essex, UK; and FMRIB Centre (M.J.), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Mark Jenkinson
- From the Neuroimaging Research Unit (M.A.R., E.P., M.F.), Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan; Department of Medicine, Surgery and Neuroscience (M.B., N.D.S.), University of Siena, Italy; Department of Neurology (R.H.B.B.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York; Department of Anatomy and Neuroscience (J.J.G.G.), Section of Clinical Neuroscience, VUmc MS Center Amsterdam, VU University Medical Center, the Netherlands; Department of Neurology (R.G.H.), University of California, San Francisco; Xinapse Systems Ltd. (M.A.H.), Colchester, Essex, UK; and FMRIB Centre (M.J.), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit (M.A.R., E.P., M.F.), Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan; Department of Medicine, Surgery and Neuroscience (M.B., N.D.S.), University of Siena, Italy; Department of Neurology (R.H.B.B.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York; Department of Anatomy and Neuroscience (J.J.G.G.), Section of Clinical Neuroscience, VUmc MS Center Amsterdam, VU University Medical Center, the Netherlands; Department of Neurology (R.G.H.), University of California, San Francisco; Xinapse Systems Ltd. (M.A.H.), Colchester, Essex, UK; and FMRIB Centre (M.J.), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Massimo Filippi
- From the Neuroimaging Research Unit (M.A.R., E.P., M.F.), Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan; Department of Medicine, Surgery and Neuroscience (M.B., N.D.S.), University of Siena, Italy; Department of Neurology (R.H.B.B.), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York; Department of Anatomy and Neuroscience (J.J.G.G.), Section of Clinical Neuroscience, VUmc MS Center Amsterdam, VU University Medical Center, the Netherlands; Department of Neurology (R.G.H.), University of California, San Francisco; Xinapse Systems Ltd. (M.A.H.), Colchester, Essex, UK; and FMRIB Centre (M.J.), Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
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