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Goodkin O, Pemberton HG, Vos SB, Prados F, Das RK, Moggridge J, De Blasi B, Bartlett P, Williams E, Campion T, Haider L, Pearce K, Bargallό N, Sanchez E, Bisdas S, White M, Ourselin S, Winston GP, Duncan JS, Cardoso J, Thornton JS, Yousry TA, Barkhof F. Clinical evaluation of automated quantitative MRI reports for assessment of hippocampal sclerosis. Eur Radiol 2020; 31:34-44. [PMID: 32749588 PMCID: PMC7755617 DOI: 10.1007/s00330-020-07075-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 05/07/2020] [Accepted: 07/15/2020] [Indexed: 02/07/2023]
Abstract
OBJECTIVES Hippocampal sclerosis (HS) is a common cause of temporal lobe epilepsy. Neuroradiological practice relies on visual assessment, but quantification of HS imaging biomarkers-hippocampal volume loss and T2 elevation-could improve detection. We tested whether quantitative measures, contextualised with normative data, improve rater accuracy and confidence. METHODS Quantitative reports (QReports) were generated for 43 individuals with epilepsy (mean age ± SD 40.0 ± 14.8 years, 22 men; 15 histologically unilateral HS; 5 bilateral; 23 MR-negative). Normative data was generated from 111 healthy individuals (age 40.0 ± 12.8 years, 52 men). Nine raters with different experience (neuroradiologists, trainees, and image analysts) assessed subjects' imaging with and without QReports. Raters assigned imaging normal, right, left, or bilateral HS. Confidence was rated on a 5-point scale. RESULTS Correct designation (normal/abnormal) was high and showed further trend-level improvement with QReports, from 87.5 to 92.5% (p = 0.07, effect size d = 0.69). Largest magnitude improvement (84.5 to 93.8%) was for image analysts (d = 0.87). For bilateral HS, QReports significantly improved overall accuracy, from 74.4 to 91.1% (p = 0.042, d = 0.7). Agreement with the correct diagnosis (kappa) tended to increase from 0.74 ('fair') to 0.86 ('excellent') with the report (p = 0.06, d = 0.81). Confidence increased when correctly assessing scans with the QReport (p < 0.001, η2p = 0.945). CONCLUSIONS QReports of HS imaging biomarkers can improve rater accuracy and confidence, particularly in challenging bilateral cases. Improvements were seen across all raters, with large effect sizes, greatest for image analysts. These findings may have positive implications for clinical radiology services and justify further validation in larger groups. KEY POINTS • Quantification of imaging biomarkers for hippocampal sclerosis-volume loss and raised T2 signal-could improve clinical radiological detection in challenging cases. • Quantitative reports for individual patients, contextualised with normative reference data, improved diagnostic accuracy and confidence in a group of nine raters, in particular for bilateral HS cases. • We present a pre-use clinical validation of an automated imaging assessment tool to assist clinical radiology reporting of hippocampal sclerosis, which improves detection accuracy.
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Affiliation(s)
- Olivia Goodkin
- Centre for Medical Image Computing (CMIC), University College London, London, UK. .,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Hugh G Pemberton
- Centre for Medical Image Computing (CMIC), University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sjoerd B Vos
- Centre for Medical Image Computing (CMIC), University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Epilepsy Society MRI Unit, Chalfont St Peter, UK
| | - Ferran Prados
- Centre for Medical Image Computing (CMIC), University College London, London, UK.,Universitat Oberta de Catalunya, Barcelona, Spain
| | - Ravi K Das
- Clinical, Educational and Health Psychology, University College London, London, UK
| | - James Moggridge
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Bianca De Blasi
- Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Philippa Bartlett
- Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK
| | - Elaine Williams
- Wellcome Trust Centre for Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Thomas Campion
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Lukas Haider
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Vienna, Austria.,NMR Research Unit, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Kirsten Pearce
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Nuria Bargallό
- Radiology Department, Hospital Clínic de Barcelona and Magnetic Resonance Image Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Esther Sanchez
- Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Sotirios Bisdas
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Mark White
- Digital Services, University College London Hospital, London, UK
| | - Sebastien Ourselin
- Department of Medical Physics and Bioengineering, University College London, London, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Gavin P Winston
- Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK.,Department of Medicine, Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - John S Duncan
- Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK
| | - Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - John S Thornton
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Tarek A Yousry
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK.,Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
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Caverzasi E, Henry RG, Vitali P, Lobach IV, Kornak J, Bastianello S, Dearmond SJ, Miller BL, Rosen HJ, Mandelli ML, Geschwind MD. Application of quantitative DTI metrics in sporadic CJD. NEUROIMAGE-CLINICAL 2014; 4:426-35. [PMID: 24624328 PMCID: PMC3950558 DOI: 10.1016/j.nicl.2014.01.011] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2013] [Revised: 12/13/2013] [Accepted: 01/17/2014] [Indexed: 11/28/2022]
Abstract
Diffusion Weighted Imaging is extremely important for the diagnosis of probable sporadic Jakob-Creutzfeldt disease, the most common human prion disease. Although visual assessment of DWI MRI is critical diagnostically, a more objective, quantifiable approach might more precisely identify the precise pattern of brain involvement. Furthermore, a quantitative, systematic tracking of MRI changes occurring over time might provide insights regarding the underlying histopathological mechanisms of human prion disease and provide information useful for clinical trials. The purposes of this study were: 1) to describe quantitatively the average cross-sectional pattern of reduced mean diffusivity, fractional anisotropy, atrophy and T1 relaxation in the gray matter (GM) in sporadic Jakob-Creutzfeldt disease, 2) to study changes in mean diffusivity and atrophy over time and 3) to explore their relationship with clinical scales. Twenty-six sporadic Jakob-Creutzfeldt disease and nine control subjects had MRIs on the same scanner; seven sCJD subjects had a second scan after approximately two months. Cortical and subcortical gray matter regions were parcellated with Freesurfer. Average cortical thickness (or subcortical volume), T1-relaxiation and mean diffusivity from co-registered diffusion maps were calculated in each region for each subject. Quantitatively on cross-sectional analysis, certain brain regions were preferentially affected by reduced mean diffusivity (parietal, temporal lobes, posterior cingulate, thalamus and deep nuclei), but with relative sparing of the frontal and occipital lobes. Serial imaging, surprisingly showed that mean diffusivity did not have a linear or unidirectional reduction over time, but tended to decrease initially and then reverse and increase towards normalization. Furthermore, there was a strong correlation between worsening of patient clinical function (based on modified Barthel score) and increasing mean diffusivity.
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Affiliation(s)
- E Caverzasi
- Department of Neurology, University of California, San Francisco (UCSF), San Francisco, CA, USA ; Department of Neuroradiology, C. Mondino National Neurological Institute, Pavia. University of Pavia, Italy
| | - R G Henry
- Department of Neurology, University of California, San Francisco (UCSF), San Francisco, CA, USA ; Graduate Group in Bioengineering, UCSF, San Francisco, CA, USA ; Department of Radiology and Biomedical Imaging, UCSF, San Francisco, CA, USA
| | - P Vitali
- Brain MRI 3T Mondino Research Center C. Mondino National Neurological Institute, Pavia, Italy
| | - I V Lobach
- Department of Neurology, University of California, San Francisco (UCSF), San Francisco, CA, USA
| | - J Kornak
- Department of Epidemiology and Biostatistics, UCSF, San Francisco, CA, USA
| | - S Bastianello
- Department of Neuroradiology, C. Mondino National Neurological Institute, Pavia. University of Pavia, Italy
| | - S J Dearmond
- Institute for Neurodegenerative Diseases, University of California, San Francisco (UCSF), USA ; Department of Pathology, University of California, San Francisco (UCSF), USA
| | - B L Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, (UCSF), USA
| | - H J Rosen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, (UCSF), USA
| | - M L Mandelli
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, (UCSF), USA
| | - M D Geschwind
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, (UCSF), USA
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Hirai T, Sasaki M, Maeda M, Ida M, Katsuragawa S, Sakoh M, Takano K, Arai S, Hirano T, Kai Y, Kakeda S, Murakami R, Ikeda R, Fukuoka H, Sasao A, Yamashita Y. Diffusion-weighted imaging in ischemic stroke: effect of display method on observers' diagnostic performance. Acad Radiol 2009; 16:305-12. [PMID: 19201359 DOI: 10.1016/j.acra.2008.09.012] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2008] [Revised: 09/14/2008] [Accepted: 09/14/2008] [Indexed: 10/21/2022]
Abstract
RATIONALE AND OBJECTIVES When evaluating ischemic stroke on diffusion-weighted magnetic resonance imaging (DWI), the display method has not been investigated. The purpose of this study was to determine whether standardization of the display method for DWI affects observers' diagnostic performance in detecting ischemic stroke on DWI. MATERIALS AND METHODS Twenty-six observers evaluated 40 DWI studies in 20 patients with acute (< 6 hours) middle cerebral arterial strokes and 20 controls for the presence of hyperintense lesions in 10 areas using the Alberta Stroke Programme Early CT Score (ASPECTS) system and one area in the corona radiata using a modified version of the ASPECTS system (ASPECTS-DWI). The images were reviewed using a standardized display method (SDM) and a conventional display method (CDM). The reading time was recorded for each session. The observers' performance was evaluated with receiver-operating characteristic analysis. RESULTS In all observers with ASPECTS-DWI scores of < or = 8 points, the value of the mean average area under the receiver-operating characteristic curve was slightly higher for the SDM than the CDM, but the difference was not statistically significant. In the insular ribbon, diagnostic accuracy was significantly higher with the SDM than the CDM (P = .036). In the other locations, there were no significant differences. With the SDM, the mean reading time was reduced by 7.5 seconds (P = .024). CONCLUSION The SDM improved diagnostic accuracy for the insular ribbon and shortened the reading time, although it did not improve observers' performance with the ASPECTS-DWI system.
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Fulbright RK, Hoffmann C, Lee H, Pozamantir A, Chapman J, Prohovnik I. MR imaging of familial Creutzfeldt-Jakob disease: a blinded and controlled study. AJNR Am J Neuroradiol 2008; 29:1638-43. [PMID: 18635614 DOI: 10.3174/ajnr.a1217] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE The E200K mutation of the PRNP (prion protein) gene is the most common cause of familial Creutzfeldt-Jakob disease (fCJD), which has imaging and clinical features that are similar to the sporadic form. The purpose of this study was to conduct a controlled and blinded evaluation of the sensitivity and specificity of MR imaging in this unique population. MATERIALS AND METHODS We compared the MR imaging characteristics of 15 early stage familial CJD patients (age, 60 +/- 7 years) with a group of 22 healthy subjects from the same families (age, 61 +/- 8 years). MR imaging included diffusion-weighted imaging (DWI), T2-weighted fast spin-echo imaging, and a fluid-attenuated inversion recovery (FLAIR) sequence. The scans were rated for abnormalities by an experienced neuroradiologist blind to diagnosis, group assignment, age, and sex. RESULTS Thirteen of 15 fCJD subjects had abnormal MR imaging. FLAIR signal intensity abnormality in the caudate or putamen nuclei demonstrated a sensitivity of 87% and specificity of 91%. DWI abnormality in the caudate nucleus showed a sensitivity of 73% and a specificity of 100%. Abnormalities in the thalamus (6 patients), cingulate gyrus (6 patients), frontal lobes (4 patients), and occipital lobes (3 patients) were best detected with DWI. No signal intensity abnormalities were demonstrated in the cerebellum. T2-weighted and T1-weighted sequences were uninformative. CONCLUSIONS FLAIR and DWI abnormalities in the caudate nucleus and putamen offer the best sensitivity and specificity for diagnosing fCJD. Our findings support recent recommendations that MR imaging should be added to the diagnostic evaluation of CJD.
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Affiliation(s)
- R K Fulbright
- Department of Radiology, Yale University School of Medicine, New Haven, CT 06520- 8043, USA.
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