AI in Ophthalmology | Startup Landscape

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  • Artificial intelligence in ophthalmologyBusiness and startup landscape

    Petteri Teikari, PhD

    version Mon 12 September 2016

  • Introduction Shallow introduction for ophthalmologic / healthcare market in a dense


    Mainly meant for people with machine learning background with little knowledge to the healthcare sector

    Best to be read from a tablet (or similar device with easy zoom in/out), do not work very well for project despite the slide format.

    Purpose of the presentation to illustrate the non-technical complexities related to healthcare ventures which not be that obvious from start.

    Not sufficient necessarily to have technically sophisticated AI solutions if no one is willing to pay for it, and you don't know understand how to bring value to the clinicians.

  • Ophthalmic Imaging

  • What modality is the best for diagnosis?

    From old school methods (visual field, fundus photograph and SD-OCT), the SD-OCT seems to offer clearly the best diagnostic capability

    Results:Among the four specialists, the interobserver agreement across the three diagnostic tests was poor for VF and photos, with kappa ( ) values of 0.13 and 0.16, respectively, and moderate for OCT, with value of 0.40. Using panel consensus as reference standard, OCT had the highest discriminative ability, with an area under the curve (AUC) of 0.99 (95% 0.961.0) compared to photograph AUC 0.85 (95% 0.730.96) and VF AUC 0.86 (95% 0.760.96), suggestive of closer performance to that of a group of glaucoma specialists. Blumberg et al. (2016)

    Retinal Diseases Signs In One

    + Bone spicule pigments (BSP) in Retinitis pigmentosa (RP), Chorioretinal Atrophy, Congenital hypertrophy of the retinal pigment epithelium (CHRPE), Asteroid hyalosis, Haemangioma, Choroidal neovascularization (CNV), Retinoschisis, etc.

    For more detailed

    analysis see

  • Future of OCT and retinal biomarkers From Schmidt-Erfurth et al. (2016): The therapeutic efficacy of VEGF inhibition in combination with the potential

    of OCT-based quantitative biomarkers to guide individualized treatment may shift the medical need from CNV treatment towards other and/or additional treatment modalities. Future therapeutic approaches will likely focus on early and/or disease-modifying interventions aiming to protect the functional and structural integrity of the morphologic complex that is primarily affected in AMD, i.e. the choriocapillary - RPE photoreceptor unit. Obviously, new biomarkers tailored towards early detection of the specific changes in this functional unit will be required as well as follow-up features defining the optimal therapeutic goal during extended therapy, i.e. life-long in neovascular AMD. Three novel additions to the OCT armamentarium are particularly promising in their capability to identify the biomarkers of the future:

    Polarization-sensitive OCT OCT angiography Adaptive optics imaging

    this modality is particularly appropriate to highlight early features during the pathophysiological development of neovascular AMD

    Findings from studies using adaptive optics implied that decreased photoreceptor function in early AMD may be possible, suggesting that eyes with pseudodrusen appearance may experience decreased retinal (particularly scotopic) function in AMD independent of CNV or RPE atrophy.

    ...the specific patterns of RPE plasticity including RPE atrophy, hypertrophy, and migration can be assessed and quantified). Moreover, polarization-sensitiv e OCT allows precise quantification of RPE-driven disease at the early stage of drusen,

    Angiographic OCT with its potential to capture choriocapillary, RPE, and neuroretinal fetures provides novel types of biomarkers identifying disease pathophysiology rather than late consecutive features during advanced neovascular AMD.

    Schlanitz et al. (2011) also Leitgeb et al. (2014)

    Zayit-Soudry et al. (2013)

  • Future Multispectral Imaging

    Absorption spectra for the major absorbing elements of the eye. Note that some of the spectra change with relatively small changes in wavelength. Maximizing the differential visibility requires utilizing small spectral slices. Melanin is the dominant absorber beyond 600 nm.

    Zimmer et al. (2014)

    Zimmer et al. (2014)

    The Annidis RHA system combines advanced multispectral imaging (MSI) technology with multi-image software processing for early detection of ocular pathologies such as age

    related macular degeneration, diabetic retinopathy and glaucoma.

  • OCT towards handheld devices by 5410.1038/nphoton.2016.141

    Here, we report the design and operation of a handheld probe that can perform both scanning laser ophthalmoscopy and optical coherence tomography of the parafoveal photoreceptor structure in infants and children without the need for adaptive optics. The probe, featuring a compact optical design weighing only 94 g, was able to quantify packing densities of parafoveal cone photoreceptors and visualize cross-sectional photoreceptor substructure in children with ages ranging from 14 months to 12 years.,5&hl=en

  • Fundus handheld, Cited by 22 articles,5&hl=en

  • OCT Example report from Zeiss Cirrus

  • OCT Device Comparison

    Comparison of images obtained with 3 different spectral-domain OCT devices (Topcon 3D OCT-1000, Zeiss Cirrus, Heidelberg Spectralis) of both eyes of the same patient with early AMD changes taken just minutes apart.

    Comparison of images obtained with 3 different spectral-domain OCTs (Heidelberg Spectralis, Optovue RTVue, Topcon 3D OCT-1000) and with 1 time-domain OCT (Zeiss Stratus) of both eyes of the same patient with a history of central serous chorioretinopathy in both eyes.

    The same set of images as shown above in pseudocolor.

    Comparison of horizontal B-scan images and 3D images of a patient with neovascular age-related macular degeneration obtained with Heidelberg Spectralis, Zeiss Cirrus, Topcon 3D OCT-1000.

    Spectral-domain Optical Coherence Tomography: A Real-world ComparisonIRENE A. BARBAZETTO, MD SANDRINE A. ZWEIFEL, MD MICHAEL ENGELBERT, MD, PhD K. BAILEY FREUND, MD JASON S. SLAKTER, MD

  • Typical volumetric medical formatsDICOM NIFTI .NII

    NEMA standard PS3, and as ISO standard 12052:2006

    Practically outdated but still used

    The Nifti format has rapidly replaced the Analyze in neuroimaging research, being adopted as the default format by some of the most widespread public domain software packages, as, FSL [12], SPM [13], and AFNI [14]. The format is supported by many viewers and image analysis software like 3D Slicer [15], ImageJ [16], and OsiriX, as well as other emerging software like R [17] and Nibabel [18], besides various conversion utilities.

    An update version of the standard, the Nifti-2, developed to manage larger data set has been defined in the 2011. This new version encode each of the dimensions of an image matrix with a 64-bit integer instead of a 16-bit as in the Nifti-1, eliminating the restriction of having a size limit of 32,767. This updated version maintains almost all the characteristics of the Nifti-1 but, as reserve for some header fields the double precision, comes with a header of 544 bytes [19].



    This project aims to offer easy ac