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Rapid is an image processing software package to be used by trained professionals, including but not limited to physicians (medical analysis and decision making) and medical technicians (administrative case processing). The software runs on a standard off-the-shelf computer or a virtual platform, such as VMware, and can be used to perform image viewing, processing, and analysis of images. Data and images are acquired through DICOM compliant imaging devices. Rapid is indicated for use in Adults only.

Rapid provides both viewing and analysis capabilities for functional and dynamic imaging datasets acquired with CT, CT Perfusion (CTP), CT Angiography (CTA), C-arm CT Perfusion and MRI including a Diffusion Weighted MRI (DWI) Module and a Dynamic Analysis Module (dynamic contrast-enhanced imaging data for MRI, CT, and C-arm CT).

Rapid C-arm CT Perfusion can be used to qualitatively assess cerebral hemodynamics in the angiography suite.

The CT analysis includes NCCT maps showing areas of hypodense and hyperdense tissue.

The DWI Module is used to visualize local water diffusion properties from the analysis of diffusion - weighted MRI data.

The Dynamic Analysis Module is used for visualization and analysis of dynamic imaging data, showing properties of changes in contrast over time. This functionality includes calculation of parameters related to tissue flow (perfusion) and tissue blood volume.

Rapid CT Perfusion and Rapid MR Perfusion can be used by physicians to aid in the selection of acute stroke patients (with known occlusion of the intracranial internal carotid artery or proximal middle cerebral artery). Instructions for the use of contrast agents for this indication can be found in Appendix A of the User's Manual. Additional information for safe and effective drug use is available in the product-specific iodinated CT and gadolinium-based MR contrast drug labeling.

In addition to the Rapid imaging criteria, patients must meet the clinical requirements for thrombectomy, as assessed by the physician, and have none of the following contraindications or exclusions:

· Bolus Quality: absent or inadequate bolus.

· Patient Motion: excessive motion leading to artifacts that make the scan technically inadequate.

· Presence of hemorrhage.

· C-Arm CTP is not to be used in the Rapid Thrombectomy indication criteria, other modalities should be consulted.

Cautions:

· C-Arm CTP provides qualitative data only, review other modalities prior to diagnosis. CBV and CBT are not absolute and CBT, CBV, MTT and Tmax are supported for qualitative interpretation of the perfusion maps only.

Rapid is a software package that provides for the visualization and study of changes in tissue using digital images captured by diagnostic imaging systems including CT (Computed Tomography) and MRI (Magnetic Image Resonance), as an aid to physician diagnosis.

Rapid can be installed on a customer's Server or it can be accessed online as a virtual system. It provides viewing, quantification, analysis and reporting capabilities.

Rapid works with the following types of (DICOM compliant) medical image data:

• CT (Computed Tomography)
• MRI(Magnetic Image Resonance) ●

Rapid acquires (DICOM compliant) medical image data from the following sources:

• . DICOM file
• DICOM CD-R ●
• Network using DICOM protocol. ●

Rapid provides tools for performing the following types of analysis:

• selection of acute stroke patients for endovascular thrombectomy ●
• volumetry of thresholded maps
• time intensity plots for dynamic time courses
• measurement of mismatch between labeled volumes on co-registered image ● volumes
• large vessel density. ●

Rapid is a Software as a Medical Device (SaMD) consisting of one or more Rapid Servers (dedicated or virtual). The Rapid Server is an image processing engine that connects to a hospital LAN, or inside the Hospital Firewall. It can be a dedicated Rapid Server or a VM Rapid appliance, which is a virtualized Rapid Server that runs on a dedicated server.

Rapid is designed to streamline medical image processing tasks that are time consuming and fatiguing in routine patient workup. Once Rapid is installed it operates with minimal user interaction. Once the CT [NCCT, CT, CTA, C-arm CT(CBCT)] or MR (MR, MRA) data are acquired, the CT or MRI console operator selects Rapid as the target for the DICOM images, and then the operator selects which study/series data to be sent to Rapid. Based on the type of incoming DICOM data, Rapid will identify the data set scanning modality and determine the suitable processing module. The Rapid Platform is a central unit which coordinates the execution image processing modules which support various analysis methods used in clinical practice today:

• Rapid CTP/MRP/C-arm CTP, DWI, Dynamic Analysis (Original: K121447, Updated ● with K172477, K182130, K213165, K233512 and K233582)
• Rapid CTA (K172477) ●
• Rapid ASPECTS (K200760, K232156)
• Rapid ICH (K193087, K221456)
• Rapid LVO (K200941, K221248)
• Rapid NCCT Stroke (K222884)
• . Rapid RV/LV (K223396)
• Rapid PETN (K220499)
• Rapid ANRTN (K230074) ●
• Rapid SDH (K232436) ●

The iSchemaView Server is a dedicated server that provides a central repository for Rapid data. All iSchemaView Server data is stored on encrypted hard disks. It also provides a user interface for accessing Rapid data. It connects to a firewalled Data Center Network and has its own firewall for additional cyber/data security. The iSchemaView Server connects to one or more Rapid Servers via WAN. Available types of connection include VPN (Virtual Private Network - RFC2401 and RFC4301 Standards) Tunnel and SSH (Secure Shell).

The provided text describes the iSchemaView Rapid device, an image processing software package. The document focuses on its 510(k) submission (K233582) and demonstrates its substantial equivalence to a previously cleared predicate device (K213165). The new submission primarily extends the device's functionality to include C-arm CT for qualitative cerebral hemodynamics assessment and qualitative analysis of perfusion parameters.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly present a "table of acceptance criteria" with corresponding "reported device performance" in the format typically used for performance studies with specific metrics and thresholds (e.g., sensitivity, specificity, accuracy). Instead, it states that the device was validated to provide "accurate representation of key processing parameters" and "met all design requirements and specifications."

The key performance claims and their validation are described qualitatively:

2. Sample size used for the test set and the data provenance

The document states that iSchemaView conducted "extensive phantom validation testing" and "software verification and validation testing of the Rapid system" using "the use of phantoms and case data." However, it does not specify the sample size for the test set (number of phantoms or cases).

The data provenance is stated as:

• Phantoms: Used for characterizing perfusion imaging performance.
• Case Data: Used for validating the Rapid System performance.

The document does not explicitly mention the country of origin of the data or whether it was retrospective or prospective.

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

The document does not specify the number of experts used to establish ground truth for the test set or their specific qualifications. It mentions that the device is "to be used by trained professionals, including but not limited to physicians (medical analysis and decision making) and medical technicians (administrative case processing)" and that "Rapid C-arm CT Perfusion can be used to qualitatively assess cerebral hemodynamics in the angiography suite." While this indicates the intended users, it does not explicitly detail the experts involved in establishing ground truth for the validation studies.

4. Adjudication method for the test set

The document does not mention any adjudication method (e.g., 2+1, 3+1) used for establishing ground truth in the test set.

5. 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 document does not describe an MRMC comparative effectiveness study where human readers' performance with and without AI assistance was evaluated. The current submission focuses on demonstrating substantial equivalence and the performance of the device itself (including its new feature for C-arm CT) rather than its direct comparative effectiveness with human readers.

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

The provided text only discusses "extensive phantom validation testing" and "software verification and validation testing." The results presented ("accurate representation of key processing parameters," "met all design requirements and specifications," and "comparable with small biases") appear to be from an algorithm-only (standalone) performance assessment, particularly for the software's ability to process and represent data from phantoms and cases, and the comparability of C-arm CT processing to conventional CT. There is no mention of human-in-the-loop performance in the context of these validation studies.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

For the "phantom validation testing," the ground truth would inherently be known physical and temporal parameters designed into the phantoms.
For the "case data," the document does not explicitly state the type of ground truth. Given the nature of a software processing and analysis system, it likely relies on a combination of:

• Established interpretations from other modalities or clinical diagnoses, particularly for "selecting acute stroke patients."
• Quantitative measurements derived from advanced imaging, which the software aims to replicate or analyze.

8. The sample size for the training set

The document does not specify the sample size for the training set. It details the device's functionality and validation rather than its development or machine learning training specifics.

9. How the ground truth for the training set was established

Since the document does not mention the sample size for the training set, it also does not describe how the ground truth for the training set was established. The focus is on the validation of the developed software, which includes algorithms, some of which may be AI/ML-based as indicated by "Mixed Traditional and AI/ML" under Software in Table 1 (page 10). However, the specifics of ML model training, including data and ground truth establishment, are not detailed in this summary.

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Rapid NCCT Stroke is a radiological computer aided triage and notification software indicated for use in the analysis of (1) nonenhanced head CT (NCCT) images. The device is intended to assist hospital networks and trained clinicians in workflow triage by flagging and communicating suspected positive findings of (1) head CT images for Intracranial Hemorrhage (ICH) and (2) NCCT large vessel occlusion (LVO) of the ICA and MCA-M1.

Rapid NCCT Stroke uses an artificial intelligence algorithm to analyze images and highlight cases with detected (1) ICH or (2) NCCT LVO on the Rapid server on premise or in the cloud in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected ICH or LVO findings via PACS, email or mobile device. Notifications include compressed preview images that are meant for informational purposes only, and are not intended for diagnostic use beyond notification.

The device does not alter the original medical image, and it is not intended to be used as a primary diagnostic device. The results of Rapid NCCT Stroke are intended to be used in conjunction with other patient information and based on professional judgment to assist with triage/prioritization of medical images. Notified clinicians are ultimately responsible for reviewing full images per the standard of care. Rapid NCCT Stroke is for Adults only.

Rapid NCCT Stroke (RNS) is a radiological computer-assisted triage and notification software device. RNS is a non-enhanced CT (NCCT) processing module which operates within the integrated Rapid Platform to provide triage and notification of suspected intracranial hemorrhage (ICH) and NCCT Large Vessel Occlusion (LVO) of the ICA and MCA-M1. The RNS is an AI/ML SaMD. The output of the module is a priority notification to clinicians indicating the suspicion of ICH or NCCT LVO. ICH analysis uses the ICH Algorithm to identify findings within the ICH algorithm; and the NCCT LVO suspicion uses the combined analysis of the ASPECTS and Hyperdense Vessel Sign (HVS) algorithms. The RNS module uses the basic services supplied by the Rapid Platform including DICOM processing, job management, imaging module execution and imaging output including the notification and compressed image.

The Rapid NCCT Stroke device is a radiological computer-aided triage and notification software for detecting intracranial hemorrhage (ICH) and large vessel occlusion (LVO) on non-enhanced head CT (NCCT) images.

Here's an analysis of its acceptance criteria and the study that proves it:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Sizes and Data Provenance

• Test Set Sample Size: 254 cases. These cases included:
  • ICH Positive: 26
  • LVO Positive: 115
  • Negative for ICH and LVO: 103
  • Excluded: 10 (due to age and technical inadequacy)
• Data Provenance: The study was a "retrospective, blinded, multicenter, multinational study." This indicates that the data was collected from multiple centers in various countries and that the analysis was performed on existing, pre-collected data. Specific countries are not mentioned.

3. Number of Experts and Qualifications for Ground Truth

• Ground Truth Establishment: The document mentions "expert reader truthing of the data." The specific number of experts is not explicitly stated for the ground truth establishment, but it is implied that multiple experts were involved given "expert reader truthing."
• Qualifications of Experts: The document refers to "human readers" including "neuroradiologists and general radiologists" in the context of the secondary clinical endpoints. This suggests that the experts involved in establishing ground truth would likely possess similar qualifications in radiology, with expertise in neurological imaging, to accurately identify ICH and LVO.

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method like 2+1 or 3+1. It states that the ground truth was established by "expert reader truthing." This implies that a consensus or a well-defined process was used by the experts to determine the definitive diagnoses, but the specific mechanics of that process (e.g., number of readers, tie-breaking rules) are not detailed.

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

Yes, a form of MRMC comparative effectiveness study was done for LVO.

• Effect Size of Human Readers' Improvement with AI vs. without AI Assistance: The study did not directly assess how much human readers improve with AI assistance. Instead, it compared the standalone performance of the Rapid NCCT Stroke device to the performance of human readers (both general radiologists and a broader group of "all readers," which included experts) in identifying LVO.
  • Expert Non-inferiority: The device demonstrated non-inferiority to "overall readers" (experts and non-experts). The device's sensitivity was 0.635, while the sensitivity for "all readers" was 0.436. The difference in sensitivity (device vs. all readers) was 0.199 (95% CI: 0.055-0.34), indicating the device performed better than the overall human readers.
  • Non-expert Superiority: The device demonstrated superiority to "general radiologists". The device's sensitivity was 0.635, while the sensitivity for general radiologists was 0.409. The difference in sensitivity (device vs. general radiologists) was 0.226 (95% CI: 0.071-0.381), indicating the device performed better than general radiologists.
  • These results show that the standalone device performed better than human readers in terms of sensitivity for LVO detection. The study design doesn't provide an effect size for human reader improvement with AI assistance (i.e., a human-in-the-loop scenario).

6. Standalone (Algorithm Only) Performance Study

Yes, an algorithm-only standalone performance study was done.

• The reported sensitivities and specificities for ICH (Se: 0.962, Sp: 0.974) and LVO (Se: 0.635, Sp: 0.951) refer to the standalone performance of the Rapid NCCT Stroke device.
• The ICH algorithm's performance was noted to be "consistent with the ICH standalone module performance (K221456)," further confirming standalone evaluation.
• The comparison against human readers (secondary clinical endpoints) also used the device's standalone output for comparison.

7. Type of Ground Truth Used

The ground truth used was expert consensus (referred to as "expert reader truthing of the data").

8. Sample Size for the Training Set

The document does not provide the sample size for the training set. It only describes the test set used for performance validation.

9. How Ground Truth for the Training Set Was Established

The document does not provide information on how the ground truth for the training set was established. It focuses solely on the validation study and the ground truth for its test set.

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