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The Notal Vision Home Optical Coherence Tomography (OCT) System is an Artificial Intelligence (AI)-based Home Use device indicated for visualization of intraretinal and subretinal hypo-reflective spaces in a 10 by 10-degrees area centered on the point of fixation of eyes diagnosed with neovascular age-related macular degeneration (NV-AMD). In addition, it provides segmentation and an estimation of the volume of hyporeflective spaces. The Notal Home OCT device is intended for imaging at home between regularly scheduled clinic assessments and not intended to be used to make treatment decisions or replace standard-of care regularly scheduled examinations and clinical testing as needed, including in-office imaging and assessments for changes in vision, by an ophthalmologist.

The NVHO System is a device that consists of two elements:

• . Notal Home OCT device: patients use this to self-image their eyes using Spectral-Domain OCT: At the end of each scanning session the data is transmitted via a secured wireless communication to the Notal Health Cloud.
• Notal Health Cloud: cluster of servers and analysis units on which the Notal OCT . Analyzer (NOA) analyzes the scans received from the Notal Home OCT device. Processed data are presented on a dedicated interactive web-application, the Notal Home OCT Web Viewer.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

Acceptance Criteria and Device Performance

The core acceptance criteria for the Notal Vision Home OCT System revolve around its ability to:

1. Accurately visualize intraretinal (IRO) and subretinal (SRO) hypo-reflective spaces (HRS), often referred to as intraretinal fluid (IRF) and subretinal fluid (SRF) in the clinical studies.
2. Provide segmentation and estimation of the volume of these hypo-reflective spaces (TRO).
3. Perform as intended in a home-use setting, including successful self-imaging.

The studies focused on the agreement in visualization of these spaces and the agreement/precision of volume quantification.

Table of Acceptance Criteria and Reported Device Performance

• Evaluate agreement between NVHO and RC-graded in-office OCT macular scans in the visualization of retinal fluid (TRO, SRO, IRO) in the central 3x3-mm area.
• Evaluate the ability of participants to successfully self-image with the NVHO device (success rate of setup, success rate for self-imaging attempts). | 001 Study (Visualization Agreement):
• PPA (Positive Percent Agreement) for TRO: 0.864 (86.4%) (95% CI 0.802, 0.926; p=0.043 for H0: PPA ≤ 0.8). This met the statistical threshold for PPA.
• NPA (Negative Percent Agreement) for TRO: 0.849 (84.9%) (95% CI 0.792, 0.907; p=0.094 for H0: NPA ≤ 0.8). This did not meet the statistical threshold (p > 0.05).
• Initial NVHO setup success rate: 86.7% (95% CI 80.8% - 91.3%; 156/180).
• NVHO self-imaging success rate: 96.1% (95% CI 92.2% - 98.4%).
• Successful transmission rate to Cloud (any self-imaging): Study eyes: 97.2% (95% CI, 93.6% - 99.1%); Fellow eyes: 94.9% (95% CI, 89.8% - 97.9%). |
  | Clinical Performance (006 Study):
• Evaluate agreement in estimated retinal fluid volume between manually segmented CIRRUS HD-OCT scans and NOA algorithm analyzing NVHO scans (TRO volume).
• Estimate repeatability and reproducibility of the TRO parameter.
• Evaluate amount of overlap in segmentation of IRF and SRF between NOA and manual graders (using Dice coefficient and NPA).
• Visual Acuity of patients: 20/320 or better. | 006 Study (Volume Quantification & Segmentation):
• Repeatability %CV for TRO: 10 VU: 5.9% to 25.0%.
• Reproducibility %CV for TRO: 10 VU: 11.4% to 33.4%.
• Agreement (Bland-Altman LOAs) and Deming regression analyses were conducted for volume estimates but specific numerical results for agreement with CIRRUS are not detailed in the provided text beyond stating the analysis method.
• Segmentation Overlap (Dice Coefficient - Mean ± SD):
  • NOA vs. Grader 1 TRO: 0.5819 ± 0.2958
  • NOA vs. Grader 2 TRO: 0.5655 ± 0.3203
  • NOA vs. Grader 3 TRO: 0.5196 ± 0.3182
  • For comparison, Grader-Grader TRO Dice varied (e.g., Grader 1 vs Grader 2: 0.6222 ± 0.2754)
• Segmentation Negative Percent Agreement (NPA - NOA vs. Graders):
  • TRO: Ranges from 0.734 to 0.787 (e.g., NOA vs Grader 1: 0.734 (58/79))
  • SRO: Ranges from 0.764 to 0.856 (e.g., NOA vs Grader 1: 0.764 (123/161))
  • IRO: Ranges from 0.946 to 0.966 (e.g., NOA vs Grader 1: 0.946 (176/186))
• Patient Visual Acuity: Mean logMAR (Snellen) for mVAP in 001 study was 0.281 (20/38.2). Max logMAR was 1.04 (20/219.3). In 006 study, Mean logMAR was 0.350 (20/44.8). Max logMAR was 1.20 (20/320.0). The study populations included patients with VA up to 20/320, consistent with the indication for use limit. |
  | Non-clinical performance (bench testing): Verify technical specifications, spatial characteristics, sensitivity, diopter range, image quality, field of view, resolution. | Bench performance verification (Table 2): Passed all tests including axial resolution, lateral resolution, axial range, lateral range, device sensitivity, and diopter range. Specific numerical criteria (b)(4) were not provided, but the results are "Passed". |
  | Human Factors Validation: Demonstrate intended users can correctly use the device (patient & HCP interfaces). | Human Factors Studies: Two summative studies conducted for patient and HCP interfaces. Found that the patient interface (NVHO device, labeling) and the physician interface (Web Viewer, labeling) were safe and effective for intended users, uses, and environments. No use errors were observed on critical tasks. |
  | Biocompatibility: Patient-contacting components are biocompatible. | Biocompatibility Evaluation: Conducted for five patient-contacting components according to ISO 10993-1. Found to be acceptable. |
  | Software Verification, Validation & Hazard Analysis: Software operates as specifications, protected from cyber threats, addresses risks. | Software Documentation & Testing: Detailed description of inputs/outputs, modules, and interactions provided. All components controlled by software. Training and testing data described. Verification and validation testing addressed hazards with satisfactory results. Cybersecurity information demonstrated protection from cyber vulnerability threats. Adequate and met standards. |
  | Optical Radiation Safety: Provide acceptable light hazard protection. | Optical Radiation Safety Testing: Conducted in accordance with ANSI Z80.36:2021. Test report, descriptions, measurement procedures, and justification for worst-case scenarios were found to be acceptable. |
  | EMC, Wireless Coexistence, Electrical Safety: Performance testing demonstrates safety. | EMC & Electrical Safety Testing: Performed per IEC 60601-1, IEC 60601-1-11, and IEC 60601-1-2. Results support electrical safety and electromagnetic compatibility. |

Study Details:

1. Sample Sizes for Test Sets and Data Provenance:

• 001 Study (Visualization Agreement):
  • Test Set (mVAP cohort): 160 participants.
  • Data Provenance: Prospective, longitudinal study conducted at seven sites in the United States.
• 006 Study (Volume Quantification & Segmentation):
  • Test Set (Fluid Precision Analysis Population, Fluid Agreement Analysis Population): 331 participants.
  • Test Set (Dice Analysis Population): 336 participants.
  • Data Provenance: Prospective, cross-sectional, observational, single-visit study conducted at six sites in the United States.

2. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

• 001 Study: Ground truth was established by expert graders at a third-party reading center (RC). The specific number and qualifications of these experts are not explicitly stated beyond "expert graders."
• 006 Study: Ground truth (manual segmentation of hypo-reflective spaces) was performed by three independent, masked graders from a third-party reading center (RC). Their specific qualifications are not explicitly stated beyond being "independent, masked graders."

3. Adjudication Method for the Test Set:

• 001 Study: For visualization of retinal fluid, "Disagreements between graders were adjudicated." The specific method (e.g., 2+1, 3+1) is not explicitly detailed, but resolution of disagreements by adjudication is stated.
• 006 Study: For manual segmentation, graders were masked to each other's determinations. The text does not explicitly state an adjudication method for segmentation disagreements between the three graders; instead, it compares the NOA's performance against each grader acting as the "reference standard" and also provides grader-to-grader agreement. However, for the primary outcome of agreement in estimated retinal fluid volume, it notes "Independent, masked graders from a third-party reading center (RC) performed manual segmentation... Graders were masked to each others' determinations..." The process for resolving discrepancies or creating a single "ground truth" through adjudication before comparing with the AI is implied by the term "reference standard" but not explicitly detailed as 2+1, etc.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• The provided text does not describe an MRMC comparative effectiveness study designed to evaluate how much human readers improve with AI vs. without AI assistance.
• The studies instead focus on the device's standalone performance (NOA algorithm) compared to expert human grading or clinic-based OCT, and the patient's ability to self-image using the device. The 001 study evaluated the agreement of the NVHO device's visualization with expert-graded in-office OCT, not an AI-assisted human reading task. The 006 study evaluated the agreement and precision of the automated volume quantification with expert manual segmentation.

5. Standalone Performance (Algorithm Only without Human-in-the-Loop):

• Yes, standalone performance was evaluated extensively.
• The Notal OCT Analyzer (NOA), which is the AI algorithmic module, operates on the Notal Health Cloud and processes the volume scans. Its purpose is to segment and calculate the volume of SRO and IRO.
• The 001 Study's primary effectiveness endpoints were the Positive and Negative Percent Agreements (PPA, NPA) of the NVHO's visualization (implying the NOA's interpretation of the scans) with RC-graded CIRRUS HD-OCT scans. This is a direct measure of the device's standalone performance in detecting fluid.
• The 006 Study directly evaluated the agreement between NOA-based volume estimates and manually segmented CIRRUS-based volume estimates, as well as the Dice coefficients (segmentation overlap) and NPAs between the NOA and individual graders. These are all measures of the standalone algorithmic performance.

6. Type of Ground Truth Used:

• For the clinical studies (001 and 006), the ground truth for fluid presence/absence and volume/segmentation was established by expert consensus/grading from a third-party reading center based on in-office Spectral-Domain OCT images (CIRRUS HD-OCT).
  • In the 001 study, "RC graders were masked to each other's determinations, to the source device, and to the participant ID number. Ordering of the scans was randomized. Disagreements between graders were adjudicated."
  • In the 006 study, "Independent, masked graders from a third-party reading center (RC) performed manual segmentation of hypo-reflective spaces on the central 3×3-mm area of acceptable CIRRUS macular scans. Graders were masked to each others' determinations and to the participant ID number. Ordering of the scans was randomized."

7. Sample Size for the Training Set:

• The provided text states: "A detailed description of data used to train and test the algorithms was provided, including cases, sources, demographics and reference standards." However, the specific sample size for the training set is not explicitly listed in the provided document. The clinical studies (001 and 006) are described as "pivotal clinical studies" for evaluating clinical performance data, implying them as test sets, rather than training sets.

8. How the Ground Truth for the Training Set Was Established:

• Similar to the training set size, the document confirms that a "description of the data used to train... algorithms" was provided by the sponsor. However, the specific methods for establishing ground truth for the training set are not detailed in this public summary. It can be inferred that it likely involved similar expert grading processes as those used for the test sets, but the document does not confirm this.

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The PreView PHP™ is intended for use in the detection and monitoring the progression of Agerelated Macular Degeneration (AMD) including, but not limited to, the detection of choroidal neovascularization (CNV).

The PreView Preferential Hyperacuity Perimeter (PreView PHP™) is intended for use in The detection and characterization of central and paracentral metamorphopsia (visual distortion) in patients with age-related macular degeneration , as an aid in monitoring progression of disease factors causing metamorphopsia including but not limited to progression of assouse ration (CNV). It is intended to be used in the office of a licensed eye care practitioner in patients with stable fixation.

The PreView PHP™ system is an interactive software driven device that provides a series of horizontal and vertical linear images to the macular region of the eye to detect abnormalities of the central and paracentral visual field that will detect and monitor progression of age related macular degeneration including detection of choroidal neovascularization. The changes in macular and near macular function are identified by the device thus enabling the reader to detect intermediate and advancing changes in macular degeneration and associated diseases to provide the capability for earlier intervention.

The PreView PHP™ is a specialized perimeter, and applies the concept of the static and automated permeter in the detection of visual field defects. The device incorporates the theory of hyperacuity to address more highly specific central and paracentral visual fields. Because of hyperacuity, perception of more finite relative spatial localization. Hyperacuity is defined as the ability to perceive a difference in the relative spatial localization of points on the central field, more specific distortions or misalignments within the central and paracentral field can be mapped with greater accuracy. The device monitors and manages the progressive changes associated with advancing macular degeneration and differentiates the different stages of AMD including but not limited to choroidal neovascularization.

The PreView PHP™ system is designed for use with standard off-the-shelf PC units in the office of the practitioner. It is aimed to detect advancing changes of AMD-related lesions including but not limited to choroidal neovascularlization.

Here's a breakdown of the acceptance criteria and study details for the PreView PHP™ device, based on the provided text:

Acceptance Criteria and Device Performance

Study Details:

1. Sample Size used for the test set and data provenance:

   • The document does not explicitly state the sample size of the test set patients. However, it does mention that the study was a "prospective, comparative, concurrent, non-randomized multicenter study."
   • Data Provenance: The document states the manufacturer is Notal Vision, Inc. from Tel Aviv, Israel, and the clinical investigation was also conducted in Israel. Based on the mention of "multicenter study," it suggests data was collected from multiple sites.

2. Number of experts used to establish the ground truth for the test set and qualifications of those experts:

   • The document does not provide information on the specific number of experts or their qualifications that established the ground truth for the test set.

3. Adjudication method for the test set:

   • The document does not specify an adjudication method.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done. If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • The provided text does not describe an MRMC comparative effectiveness study where human readers' performance with and without AI assistance was evaluated. The study focused on the standalone performance of the PreView PHP™ device.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

   • Yes, a standalone study was done. The clinical investigation assessed the ability of the Preferential Hyperacuity Perimeter (PreView PHP™) itself to detect recent onset of choroidal neovascularization (CNV) and differentiate it from an intermediate stage of AMD. The reported sensitivity and specificity are for the device's performance directly.

6. The type of ground truth used:

   • The ground truth for the test set was based on untreated CNV from AMD diagnosed within the last 60 days or an intermediate stage of AMD (at least 1 large druse or at least 20 medium-size drusen) with no evidence of geographic atrophy or other macular diseases. This implies a clinical diagnosis by ophthalmologists, likely supported by other diagnostic methods (which are not explicitly detailed in the provided text for ground truth establishment, though the referenced predicate devices include technologies like the Heidelberg Retina Angiograph FA/ICGA).

7. The sample size for the training set:

   • The document does not specify a separate training set or its sample size. The clinical investigation appears to be a validation study.

8. How the ground truth for the training set was established:

   • As no separate training set is explicitly mentioned, how its ground truth was established is not provided. The device likely predates or was developed concurrently with modern machine learning paradigms requiring distinct training and test sets in the same way.

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The Notal Vision Macular Computerized Psychophysical Test (MCPT) is indicated for The early detection of central and paracentral irregularities (vision abnormalities) in the visual field, most commonly associated with macular degeneration.

The device is a computerized interactive software device that provides the user with a series of images oriented in vertical and horizontal planes on a imaging screen that is designed to identify irregularities in the central and paracentral macular field of the human visual system. The device analyzes the image presentation in the process of identifying visual field abnormalities and stores the analysis in a computer server. The device is housed in a PC computer.

The Notal Vision Macular Computerized Psychophysical Test (MCPT) is indicated for the early detection of central and paracentral irregularities (vision abnormalities) in the visual field, most commonly associated with macular degeneration.

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state quantitative "acceptance criteria" for the MCPT in terms of specific sensitivity or specificity targets. Instead, the study's primary objective was to demonstrate that MCPT is equal to or better than the Amsler grid in detecting AMD-related retinal abnormalities. The reported performance compared the MCPT directly against the Amsler Grid.

Note: While the overall P-value for sensitivity strongly favors MCPT, the P-value for Category 1 (healthy subjects) shows MCPT having significantly lower specificity compared to the Amsler Grid.

2. Sample Size Used for the Test Set and Data Provenance:

• Test Set Sample Size: The document does not explicitly state a total sample size for the test set. However, a breakdown of categories is provided:
  • Category 1 (Healthy): 33 subjects
  • Category 2 (AMD): 51 subjects
  • Category 3 (AMD): 20 subjects
  • Category 4 (AMD): 27 subjects
  • Category 5 (AMD): 19 subjects
  • Total subjects across all categories = 150 subjects.
• Data Provenance: The study was a "prospective single blinded randomized clinical investigation conducted at multiple investigational sites." The document does not specify the country of origin of the data.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

The document does not provide information on the number of experts used to establish ground truth or their qualifications. The categories are described as "individuals with defined age-related macular degeneration (AMD) at different stages, and the control subjects were those with normal healthy eyes," implying a clinical diagnosis as ground truth, but not the specific experts or their process.

4. Adjudication Method for the Test Set:

The document does not describe any specific adjudication method for the test set. The categories (AMD at different stages and healthy controls) were "defined," suggesting a pre-established clinical diagnosis, but the process of reaching that definition is not detailed.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

Yes, a comparative effectiveness study was done. The study compared the MCPT to the Amsler Grid.

• Effect Size of Human Readers Improve with AI vs. without AI assistance: This study compares an automated device (MCPT) against a traditional manual test (Amsler grid), not the improvement of human readers with AI assistance versus without AI assistance. Therefore, an effect size of human improvement cannot be determined from this document as it's not a reader study with AI assistance. The study focuses on the standalone performance of the MCPT and the Amsler grid themselves.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

Yes, a standalone study was performed. The "MCPT" (Macular Computerized Psychophysical Test) is described as an "interactive software device" that "analyzes the image presentation in the process of identifying visual field abnormalities." The results presented for MCPT are its direct performance, acting as an algorithm-only assessment, which is then compared against the Amsler grid.

7. Type of Ground Truth Used:

The ground truth used was clinical diagnosis/classification of "defined age-related macular degeneration (AMD) at different stages" and "normal healthy eyes." This falls under clinical diagnosis rather than pathology or outcomes data specifically.

8. Sample Size for the Training Set:

The document does not mention a separate training set or its sample size. The clinical investigation described appears to be for validation/testing.

9. How the Ground Truth for the Training Set Was Established:

Since no training set is described, information on how its ground truth was established is not available in the provided document.

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