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411 results on '"Pfau, Maximilian"'

2. ABCA4 c.5461-6T>C Causes Stargardt Disease Through Exon Skipping

Author

Quinodoz, Mathieu, Iglesias-Romero, Ana Belén, Cancellieri, Francesca, Kaminska, Karolina, Scholl, Hendrik P. N., Pfau, Maximilian, Rivolta, Carlo, Dong, Haidong, Series Editor, Radeke, Heinfried H., Series Editor, Rezaei, Nima, Series Editor, Steinlein, Ortrud, Series Editor, Xiao, Junjie, Series Editor, Rosenhouse-Dantsker, Avia, Series Editor, Gerlai, Robert, Series Editor, Bowes Rickman, Catherine, editor, Grimm, Christian, editor, Anderson, Robert E., editor, Ash, John D., editor, Pierce, Eric, editor, and Hollyfield, Joe G., editor

Published
2025
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8. Choriocapillaris Flow Signal Impairment in Sorsby Fundus Dystrophy

Author

Hess, Kristina, Raming, Kristin, Gliem, Martin, Issa, Peter Charbel, Herrmann, Philipp, Holz, Frank G., and Pfau, Maximilian

Subjects
Physics - Medical Physics, Quantitative Biology - Tissues and Organs
Abstract

Purpose: To quantify choriocapillaris flow alterations in early Sorsby Fundus Dystrophy (SFD) and to investigate the relationship of choriocapillaris flow with the choroidal and outer retinal microstructure. Methods: In this prospective case-control study, 18 eyes of 11 patients with early SFD and 32 eyes of 32 controls without ocular pathology underwent multimodal imaging including spectral-domain optical coherence tomography (OCT)followed by deep-learning-based layer segmentation. OCT-angiography (OCT-A) was performed to quantify choriocapillaris flow signal deficits (FDs). Differences in choriocapillaris flow area percentage between SFD patients and controls were determined and a structure-function correlation with outer retinal layer thicknesses were analyzed based on mixed model analysis. Results: SFD patients exhibited a significantly greater choriocapillaris FDs area percentage than controls (estimate [95% CI] 32.05% [24.31-39.80] vs. 23.36% [20.64-26.09], P<0.001), even when adjusting for age. Choroidal thickness was a structural OCT surrogate of the choriocapillaris FD area percentage (-0.82% per 100 micrometer, P=0.017), whereas retinal-pigment-epithelium-drusen-complex thickness was not informative regarding choriocapillaris FDs (P=0.932). The choriocapillaris FD area percentage was associated with an altered microstructure of the overlying photoreceptors (outer-segments, inner-segments and outer-nuclear-layer thinning of -0.31, -0.12 and -0.47 $\mu$m per %FD, respectively, P<0.001). Conclusions: Patients with early SFD exhibit pronounced abnormalities of choriocapillaris flow signal on OCT-A, which are not limited to areas of sub-RPE deposits seen in OCT imaging. Thus, analysis of the choriocapillaris flow may enable clinical trials at earlier disease stages in SFD and possibly in mimicking diseases with an impaired Bruchs membrane including age-related macular degeneration., Comment: 5 Figures, 0 Tables, 2 supplementary figures

Published
2021

9. Genotype–Phenotype Association in ABCA4-Associated Retinopathy

Author

Pfau, Maximilian, Zein, Wadih M., Huryn, Laryssa A., Cukras, Catherine A., Jeffrey, Brett G., Hufnagel, Robert B., Brooks, Brian P., Crusio, Wim E., Series Editor, Dong, Haidong, Series Editor, Radeke, Heinfried H., Series Editor, Rezaei, Nima, Series Editor, Steinlein, Ortrud, Series Editor, Xiao, Junjie, Series Editor, Ash, John D., editor, Pierce, Eric, editor, Anderson, Robert E., editor, Bowes Rickman, Catherine, editor, Hollyfield, Joe G., editor, and Grimm, Christian, editor

Published
2023
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13. Autofluoreszenz-Imaging

Author

Fleckenstein, Monika, primary, Holz, Frank G., additional, Pfau, Maximilian, additional, and Schmitz-Valckenberg, Steffen, additional

Published
2023
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14. Looking outside the box with a pathology aware AI approach for analyzing OCT retinal images in Stargardt disease.

Author

Khateri, Parisa, Koottungal, Tiana, Wong, Damon, Strauss, Rupert W., Janeschitz-Kriegl, Lucas, Pfau, Maximilian, Schmetterer, Leopold, and Scholl, Hendrik P. N.

Subjects
STARGARDT disease, MEDICAL sciences, OPTICAL coherence tomography, RETINAL imaging, VISION disorders, DEEP learning
Abstract

Stargardt disease type 1 (STGD1) is a genetic disorder that leads to progressive vision loss, with no approved treatments currently available. The development of effective therapies faces the challenge of identifying appropriate outcome measures that accurately reflect treatment benefits. Optical Coherence Tomography (OCT) provides high-resolution retinal images, serving as a valuable tool for deriving potential outcome measures, such as retinal thickness. However, automated segmentation of OCT images, particularly in regions disrupted by degeneration, remains complex. In this study, we propose a deep learning-based approach that incorporates a pathology-aware loss function to segment retinal sublayers in OCT images from patients with STGD1. This method targets relatively unaffected regions for sublayer segmentation, ensuring accurate boundary delineation in areas with minimal disruption. In severely affected regions, identified by a box detection model, the total retina is segmented as a single layer to avoid errors. Our model significantly outperforms standard models, achieving an average Dice coefficient of for total retina and for retinal sublayers. The most substantial improvement was in the segmentation of the photoreceptor inner segment, with Dice coefficient increasing by . This approach provides a balance between granularity and reliability, making it suitable for clinical application in tracking disease progression and evaluating therapeutic efficacy. [ABSTRACT FROM AUTHOR]

Published
2025
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16. OCT Signs of Early Atrophy in Age-Related Macular Degeneration: Interreader Agreement: Classification of Atrophy Meetings Report 6

Author

Wu, Zhichao, Pfau, Maximilian, Blodi, Barbara A., Holz, Frank G., Jaffe, Glenn J., Liakopoulos, Sandra, Sadda, Srinivas R., Staurenghi, Giovanni, Bjelopera, Elvira, Brown, Tyler, Chang, Petrus, Choong, John, Corradetti, Giulia, Corvi, Federico, Domalpally, Amitha, Hurtenbach, Cynthia, Nittala, Muneeswar Gupta, Olson, Anthony, Pak, Jeong W., Pappe, Judith, Saßmannshausen, Marlene, Skalak, Cindy, Thiele, Sarah, Guymer, Robyn H., and Schmitz-Valckenberg, Steffen

Published
2022
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18. Widespread subclinical cellular changes revealed across a neural-epithelial-vascular complex in choroideremia using adaptive optics

Author

Aguilera, Nancy, Liu, Tao, Bower, Andrew J., Li, Joanne, Abouassali, Sarah, Lu, Rongwen, Giannini, John, Pfau, Maximilian, Bender, Chelsea, Smelkinson, Margery G., Naik, Amelia, Guan, Bin, Schwartz, Owen, Volkov, Andrei, Dubra, Alfredo, Liu, Zhuolin, Hammer, Daniel X., Maric, Dragan, Fariss, Robert, Hufnagel, Robert B., Jeffrey, Brett G., Brooks, Brian P., Zein, Wadih M., Huryn, Laryssa A., and Tam, Johnny

Published
2022
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23. Fundus autofluorescence imaging

Author

Schmitz-Valckenberg, Steffen, Pfau, Maximilian, Fleckenstein, Monika, Staurenghi, Giovanni, Sparrow, Janet R., Bindewald-Wittich, Almut, Spaide, Richard F., Wolf, Sebastian, Sadda, Srinivas R., and Holz, Frank G.

Published
2021
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25. Test–retest variability of mesopic microperimetry‐associated parameters in patients with retinitis pigmentosa: REPEAT Study Report No. 2.

Author

Karuntu, Jessica S., Pfau, Maximilian, Jolly, Jasleen K., and Boon, Camiel J. F.

Subjects
*RETINITIS pigmentosa, *VISUAL acuity, *PERIMETRY, *COHORT analysis, *LONGITUDINAL method
Abstract

Purpose Methods Results Conclusions Understanding test–retest variability (TRV) of mesopic microperimetry is critical for defining meaningful treatment effects in retinitis pigmentosa (RP) trials. This study uniquely evaluates intra‐ and intervisit TRV and coefficients of repeatability (CoRs) for microperimetry parameters in RP patients with varying best‐corrected visual acuity (BCVA) levels.In this single‐centre prospective cohort study, RP patients were assessed on two visits, 14.0 days apart. Patients were grouped by BCVA: low (≤20/50 Snellen; ≥0.4 logMAR) or moderate (>20/50 Snellen; <0.4 logMAR). Using Bland–Altman analyses, the CoRs for intra‐ and intervisit variability were determined for pointwise (dB), mean (dB), and volume sensitivity (dB*deg2) on mesopic microperimetry.Intravisit CoRs for mean, volume, and pointwise sensitivity were 1.7 dB, 353.2 dB*deg2, and 8.6 dB, respectively, in the low‐BCVA group (n = 32), and 0.9 dB, 254.5 dB*deg2, and 7.3 dB in the moderate‐BCVA group (n = 15).Intervisit CoRs for mean, volume, and pointwise sensitivity were 2.4 dB, 355.2 dB*deg2, and 10.2 dB in the low‐BCVA group (n = 31). The moderate‐BCVA group (n = 16) showed smaller CoRs of 1.6 dB, 386.8 dB*deg2, and 7.7 dB for mean, volume, and pointwise sensitivity. BCVA and mean sensitivity, but not fixation stability, are predictors of TRV for volume sensitivity.Due to significant TRV, pointwise sensitivity is an unreliable endpoint for RP patients, irrespective of BCVA. Mean sensitivity is suitable as an endpoint when BCVA is relatively preserved.Volume sensitivity provides additional spatial information, and shows promise as a clinical endpoint for assessing macular sensitivity changes on mesopic microperimetry in patients with RP. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Human selection bias drives the linear nature of the more ground truth effect in explainable deep learning optical coherence tomography image segmentation

Author

Maloca, Peter M; https://orcid.org/0000-0002-4794-5859, Pfau, Maximilian, Janeschitz‐Kriegl, Lucas, Reich, Michael, Goerdt, Lukas, Holz, Frank G, Müller, Philipp L, Valmaggia, Philippe, Fasler, Katrin; https://orcid.org/0000-0002-0348-961X, Keane, Pearse A; https://orcid.org/0000-0002-9239-745X, Zarranz‐Ventura, Javier, Zweifel, Sandrine; https://orcid.org/0000-0001-7431-1774, Wiesendanger, Jonas, Kaiser, Pascal, Enz, Tim J; https://orcid.org/0000-0002-5211-7855, Rothenbuehler, Simon P, Hasler, Pascal W, Juedes, Marlene, Freichel, Christian, Egan, Catherine, Tufail, Adnan; https://orcid.org/0000-0002-0965-4890, Scholl, Hendrik P N, Denk, Nora, Maloca, Peter M; https://orcid.org/0000-0002-4794-5859, Pfau, Maximilian, Janeschitz‐Kriegl, Lucas, Reich, Michael, Goerdt, Lukas, Holz, Frank G, Müller, Philipp L, Valmaggia, Philippe, Fasler, Katrin; https://orcid.org/0000-0002-0348-961X, Keane, Pearse A; https://orcid.org/0000-0002-9239-745X, Zarranz‐Ventura, Javier, Zweifel, Sandrine; https://orcid.org/0000-0001-7431-1774, Wiesendanger, Jonas, Kaiser, Pascal, Enz, Tim J; https://orcid.org/0000-0002-5211-7855, Rothenbuehler, Simon P, Hasler, Pascal W, Juedes, Marlene, Freichel, Christian, Egan, Catherine, Tufail, Adnan; https://orcid.org/0000-0002-0965-4890, Scholl, Hendrik P N, and Denk, Nora

Abstract

Supervised Deep Learning (DL) algorithms are highly dependent on training data for which human graders are assigned, e.g. for optical coherence tomography (OCT) image annotation. Despite the tremendous success of DL, due to human judgement, these ground truth labels can be inaccurate and/or ambiguous and cause a human selection bias. We therefore investigated the impact of the size of the ground truth and variable numbers of graders on the predictive performance of the same DL architecture and repeated each experiment 3 times. The largest training dataset delivered a prediction performance close to that of human experts. All DL systems utilized were highly consistent. Nevertheless, the DL under‐performers could not achieve any further autonomous improvement even after repeated training. Furthermore, a quantifiable linear relationship between ground truth ambiguity and the beneficial effect of having a larger amount of ground truth data was detected and marked as the more‐ground‐truth effect.This article is protected by copyright. All rights reserved.

Published
2024

32. Pseudoxanthoma elasticum – Genetics, pathophysiology, and clinical presentation

Author

Zorgeenheid Oogheelkunde Medisch, MS Oogheelkunde, Infection & Immunity, Pfau, Kristina, Lengyel, Imre, Ossewaarde-van Norel, Jeannette, van Leeuwen, Redmer, Risseeuw, Sara, Leftheriotis, Georges, Scholl, Hendrik P.N., Feltgen, Nicolas, Holz, Frank G., Pfau, Maximilian, Zorgeenheid Oogheelkunde Medisch, MS Oogheelkunde, Infection & Immunity, Pfau, Kristina, Lengyel, Imre, Ossewaarde-van Norel, Jeannette, van Leeuwen, Redmer, Risseeuw, Sara, Leftheriotis, Georges, Scholl, Hendrik P.N., Feltgen, Nicolas, Holz, Frank G., and Pfau, Maximilian

Published
2024

34. Multicenter normative data for mesopic microperimetry

Author

Pfau, Maximilian, primary, Jolly, Jasleen K, additional, Charng, Jason, additional, von der Emde, Leon, additional, Mueller, Philipp L., additional, Ansari, Georg, additional, Pfau, Kristina, additional, Chen, Fred K, additional, and Wu, Zhichao, additional

Published
2024
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42. The Optical Coherence Tomography and Microperimetry Biomarker Evaluation in Patients with Geographic Atrophy (OMEGA) Study: Design and Baseline Characteristics (OMEGA report 1)

Author

Ansari, Georg, primary, Schärer, Nils, additional, Camenzind Zuche, Hanna, additional, Gabrani, Chrysoula, additional, Anders, Philipp, additional, Pfau, Kristina, additional, Valmaggia, Philippe, additional, Giani, Andrea, additional, Esmaeelpour, Marieh, additional, Chingning Yamaguchi, Taffeta, additional, Prünte, Christian F., additional, Maloca, Peter M., additional, Schmetterer, Leopold, additional, Scholl, Hendrik P.N., additional, and Pfau, Maximilian, additional

Published
2023
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43. Human selection bias drives the linear nature of the more ground truth effect in explainable deep learning optical coherence tomography image segmentation

Author

Maloca, Peter M., primary, Pfau, Maximilian, additional, Janeschitz‐Kriegl, Lucas, additional, Reich, Michael, additional, Goerdt, Lukas, additional, Holz, Frank G., additional, Müller, Philipp L., additional, Valmaggia, Philippe, additional, Fasler, Katrin, additional, Keane, Pearse A., additional, Zarranz‐Ventura, Javier, additional, Zweifel, Sandrine, additional, Wiesendanger, Jonas, additional, Kaiser, Pascal, additional, Enz, Tim J., additional, Rothenbuehler, Simon P., additional, Hasler, Pascal W., additional, Juedes, Marlene, additional, Freichel, Christian, additional, Egan, Catherine, additional, Tufail, Adnan, additional, Scholl, Hendrik P. N., additional, and Denk, Nora, additional

Published
2023
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48. Comparison of Novel Volumetric Microperimetry Metrics in Intermediate Age-Related Macular Degeneration: PINNACLE Study Report 3

Author

Anders, Philipp, primary, Traber, Ghislaine L., additional, Pfau, Maximilian, additional, Riedl, Sophie, additional, Hagag, Ahmed M., additional, Camenzind, Hanna, additional, Mai, Julia, additional, Kaye, Rebecca, additional, Bogunović, Hrvoje, additional, Fritsche, Lars G., additional, Rueckert, Daniel, additional, Schmidt-Erfurth, Ursula, additional, Sivaprasad, Sobha, additional, Lotery, Andrew J., additional, and Scholl, Hendrik P. N., additional

Published
2023
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