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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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