Automated Retinal Topographic Maps Measured With Magnetic Resonance Imaging

Beenakker, Jan-Willem M.; Shamonin, Denis P; Webb, Andrew; Luyten, Gregorius P M; Stoel, Berend C.

doi:10.1167/iovs.14-15161

Cited by 32 publications

(34 citation statements)

References 36 publications

(45 reference statements)

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“…By taking advantage of the good coil filling factor and non-isotropic sampling (e.g., thick slices), fine resolution images, approaching those in rodents, but in humans without sedation is possible using a cuedblinking procedure (Beenakker et al, 2013(Beenakker et al, , 2015Berkowitz et al, 2001;Berkowitz et al, 2013;Lindner et al, 2014;Sirin et al, 2015;Zhang et al, 2011). For example, we recently published human images collected at 58 mm axial resolution .…”

Section: Addressing Concerns About Memri and Mrimentioning

confidence: 99%

MRI of rod cell compartment-specific function in disease and treatment in vivo

Berkowitz

Bissig

Roberts

2016

Progress in Retinal and Eye Research

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Rod cell oxidative stress is a major pathogenic factor in retinal disease, such as diabetic retinopathy (DR) and retinitis pigmentosa (RP). Personalized, non-destructive, and targeted treatment for these diseases remains elusive since current imaging methods cannot analytically measure treatment efficacy against rod cell compartment-specific oxidative stress in vivo. Over the last decade, novel MRI-based approaches that address this technology gap have been developed. This review summarizes progress in the development of MRI since 2006 that enables earlier evaluation of the impact of disease on rod cell compartment-specific function and the efficacy of anti-oxidant treatment than is currently possible with other methods. Most of the new assays of rod cell compartment-specific function are based on endogenous contrast mechanisms, and this is expected to facilitate their translation into patients with DR and RP, and other oxidative stress-based retinal diseases.

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Section: Addressing Concerns About Memri and Mrimentioning

confidence: 99%

MRI of rod cell compartment-specific function in disease and treatment in vivo

Berkowitz

Bissig

Roberts

2016

Progress in Retinal and Eye Research

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“…In this context, the existence of a robust and accurate segmentation tool for eye MR images would offer an unprecedented opportunity for multimodal patient specific eye modeling. That is, combining modalities such as Fundus imaging, US with MRI for treatment planning of the eye [10][11][12] .…”

Section: Introductionmentioning

confidence: 99%

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma

Ciller

Zanet

Rüegsegger

et al. 2015

International Journal of Radiation Oncology*Biology*Physics

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Summary:The diagnosis and treatment of retinoblastoma requires often the laborious task of segmenting the eye anatomy in 3D magnetic resonance images (MRI). Statistical Shape Modeling (SSM) techniques are successful tools for modeling anatomical shapes in medical imaging. This work introduces the first fully automatic segmentation of the eye evaluated on 24 MRI children eyes, yielding overlap measures of 94.90±2.12% for the sclera and cornea, 94.72±1.89% for the vitreous humor and 85.16±4.91% for the lens. Abstract:Purpose: Proper delineation of ocular anatomy in 3D imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic Resonance Imaging (MRI) is nowadays utilized in clinical practice for the diagnosis confirmation and treatment planning of retinoblastoma in infants, where it serves as a source of information, complementary to the Fundus or Ultrasound imaging. Here we present a framework to fully automatically segment the eye anatomy in the MRI based on 3D Active Shape Models (ASM), we validate the results and present a proof of concept to automatically segment pathological eyes.Material and Methods: Manual and automatic segmentation were performed on 24 images of healthy children eyes (3.29±2.15 years). Imaging was performed using a 3T MRI scanner. The ASM comprises the lens, the vitreous humor, the sclera and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens and the optic nerve, then aligning the model and fitting it to the patient. We validated our segmentation method using a leave-one-out cross validation. The segmentation results were evaluated by measuring the overlap using the Dice Similarity Coefficient (DSC) and the mean distance error.Results: We obtained a DSC of 94.90±2.12% for the sclera and the cornea, 94.72±1.89% for the vitreous humor and 85.16±4.91% for the lens. The mean distance error was 0.26±0.09mm. The entire process took 14s on average per eye.Conclusion: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor and the lens using MRI. We additionally present a proof of concept for fully automatically segmenting pathological eyes. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

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“…From Eq. (8), this corresponds to a fraction F = 27%. Based on a simple proportions, the fraction for the vertical meridian (θ 2 = 60°) is approximately 23%.…”

Section: Mri Image Analysismentioning

confidence: 99%

“…Recent research has pointed to retinal shape being an important consideration in myopia development [1][2][3]. There have been a few studies of retinal shape using magnetic resonance imaging [4][5][6][7][8]. The technique suffers from high cost of up to AUD $500/scan, long testing time of 2-3 minutes per image, and low resolution of approximately 0.15 mm [9].…”

Section: Introductionmentioning

confidence: 99%

Validation of a partial coherence interferometry method for estimating retinal shape

Verkicharla

Suheimat

Pope

et al. 2015

Biomed. Opt. Express

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Abstract:To validate a simple partial coherence interferometry (PCI) based retinal shape method, estimates of retinal shape were determined in 60 young adults using off-axis PCI, with three stages of modeling using variants of the Le Grand model eye, and magnetic resonance imaging (MRI). Stage 1 and 2 involved a basic model eye without and with surface ray deviation, respectively and Stage 3 used model with individual ocular biometry and ray deviation at surfaces. Considering the theoretical uncertainty of MRI (12-14%), the results of the study indicate good agreement between MRI and all three stages of PCI modeling with <4% and <7% differences in retinal shapes along horizontal and vertical meridians, respectively. Stage 2 and Stage 3 gave slightly different retinal co-ordinates than Stage 1 and we recommend the intermediate Stage 2 as providing a simple and valid method of determining retinal shape from PCI data.

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Automated Retinal Topographic Maps Measured With Magnetic Resonance Imaging

Cited by 32 publications

References 36 publications

MRI of rod cell compartment-specific function in disease and treatment in vivo

MRI of rod cell compartment-specific function in disease and treatment in vivo

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma

Validation of a partial coherence interferometry method for estimating retinal shape

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