Sina C Rosenkranz1,2, Barbara Kaulen1,2, Hanna G Zimmermann3,4, Ava K Bittner5,6, Michael Dorr7, Jan-Patrick Stellmann1,2,8,9. 1. Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie, Hamburg, Germany. 2. Klinik und Poliklinik für Neurologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany. 3. Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany. 4. NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany. 5. College of Optometry, Nova Southeastern University, Fort Lauderdale, FL, United States. 6. Department of Ophthalmology, Stein Eye Institute, University of California, Los Angeles, Los Angeles, CA, United States. 7. Adaptive Sensory Technology, Lübeck, Germany. 8. APHM, Hôpital de la Timone, CEMEREM, Marseille, France. 9. Aix Marseille Université, CRMBM, CNRS UMR 7339, Marseille, France.
Abstract
BACKGROUND: Impairment of visual function is one of the major symptoms of people with multiple sclerosis (pwMS). A multitude of disease effects including inflammation and neurodegeneration lead to structural impairment in the visual system. However, the gold standard of disability quantification, the expanded disability status scale (EDSS), relies on visual assessment charts. A more comprehensive assessment of visual function is the full contrast sensitivity function (CSF), but most tools are time consuming and not feasible in clinical routine. The quantitative CSF (qCSF) test is a computerized test to assess the full CSF. We have already shown a better correlation with visual quality of life (QoL) than for classical high and low contrast charts in multiple sclerosis (MS). OBJECTIVE: To study the precision, test duration, and repeatability of the qCSF in pwMS. In order to evaluate the discrimination ability, we compared the data of pwMS to healthy controls. METHODS: We recruited two independent cohorts of MS patients. Within the precision cohort (n = 54), we analyzed the benefit of running 50 instead of 25 qCSF trials. The repeatability cohort (n = 44) was assessed by high contrast vision charts and qCSF assessments twice and we computed repeatability metrics. For the discrimination ability we used the data from all pwMS without any previous optic neuritis and compared the area under the log CSF (AULCSF) to an age-matched healthy control data set. RESULTS: We identified 25 trials of the qCSF algorithm as a sufficient amount for a precise estimate of the CSF. The median test duration for one eye was 185 s (range 129-373 s). The AULCSF had better test-retest repeatability (Mean Average Precision, MAP) than visual acuity measured by standard high contrast visual acuity charts or CSF acuity measured with the qCSF (0.18 vs. 0.11 and 0.17, respectively). Even better repeatability (MAP = 0.19) was demonstrated by a CSF-derived feature that was inspired by low-contrast acuity charts, i.e., the highest spatial frequency at 25% contrast. When compared to healthy controls, the MS patients showed reduced CSF (average AULCSF 1.21 vs. 1.42, p < 0.01). CONCLUSION: High precision, usability, repeatability, and discrimination support the qCSF as a tool to assess contrast vision in pwMS.
BACKGROUND: Impairment of visual function is one of the major symptoms of people with multiple sclerosis (pwMS). A multitude of disease effects including inflammation and neurodegeneration lead to structural impairment in the visual system. However, the gold standard of disability quantification, the expanded disability status scale (EDSS), relies on visual assessment charts. A more comprehensive assessment of visual function is the full contrast sensitivity function (CSF), but most tools are time consuming and not feasible in clinical routine. The quantitative CSF (qCSF) test is a computerized test to assess the full CSF. We have already shown a better correlation with visual quality of life (QoL) than for classical high and low contrast charts in multiple sclerosis (MS). OBJECTIVE: To study the precision, test duration, and repeatability of the qCSF in pwMS. In order to evaluate the discrimination ability, we compared the data of pwMS to healthy controls. METHODS: We recruited two independent cohorts of MS patients. Within the precision cohort (n = 54), we analyzed the benefit of running 50 instead of 25 qCSF trials. The repeatability cohort (n = 44) was assessed by high contrast vision charts and qCSF assessments twice and we computed repeatability metrics. For the discrimination ability we used the data from all pwMS without any previous optic neuritis and compared the area under the log CSF (AULCSF) to an age-matched healthy control data set. RESULTS: We identified 25 trials of the qCSF algorithm as a sufficient amount for a precise estimate of the CSF. The median test duration for one eye was 185 s (range 129-373 s). The AULCSF had better test-retest repeatability (Mean Average Precision, MAP) than visual acuity measured by standard high contrast visual acuity charts or CSF acuity measured with the qCSF (0.18 vs. 0.11 and 0.17, respectively). Even better repeatability (MAP = 0.19) was demonstrated by a CSF-derived feature that was inspired by low-contrast acuity charts, i.e., the highest spatial frequency at 25% contrast. When compared to healthy controls, the MS patients showed reduced CSF (average AULCSF 1.21 vs. 1.42, p < 0.01). CONCLUSION: High precision, usability, repeatability, and discrimination support the qCSF as a tool to assess contrast vision in pwMS.
Authors: C Heesen; R Haase; S Melzig; J Poettgen; M Berghoff; F Paul; U Zettl; M Marziniak; K Angstwurm; R Kern; T Ziemssen; J P Stellmann Journal: Acta Neurol Scand Date: 2017-12-03 Impact factor: 3.209
Authors: Amy Kalia; Luis Andres Lesmes; Michael Dorr; Tapan Gandhi; Garga Chatterjee; Suma Ganesh; Peter J Bex; Pawan Sinha Journal: Proc Natl Acad Sci U S A Date: 2014-01-21 Impact factor: 11.205
Authors: E M Mowry; M J Loguidice; A B Daniels; D A Jacobs; C E Markowitz; S L Galetta; M L Nano-Schiavi; G R Cutter; M G Maguire; L J Balcer Journal: J Neurol Neurosurg Psychiatry Date: 2009-02-23 Impact factor: 10.154
Authors: Laura J Balcer; Jenelle Raynowska; Rachel Nolan; Steven L Galetta; Raju Kapoor; Ralph Benedict; Glenn Phillips; Nicholas LaRocca; Lynn Hudson; Richard Rudick Journal: Mult Scler Date: 2017-02-16 Impact factor: 6.312