Cruxi
FDA record research
The acquired FDA endpoint has no selected substantially-equivalent K-number decisions under primary product code QEK during 2021–2025. Its latest selected record across the endpoint is dated 2019-12-09. Use that dated record only as historical context. Check the recorded scope and current route separately; these data do not provide a recent timing benchmark. The complete-year window has 0 decisions; the separate all-observed-date count is 2. These denominators describe different date ranges.
Evidence retrieved 2026-10-07. Source versions and topic-specific limits are listed below.
An exact FDA-record regulation_number match to one acquired Title 21 section. Records with the same normalized scope definition, class, regulation and recorded submission/GMP flags are grouped. Sparse definitions and generic exemption boilerplate do not qualify. No text-similarity equivalence or legal applicability is inferred.
An angiographic coronary vascular physiologic simulation software device is intended to aid in the identification of functionally significant cardiovascular disease.
Compare the proposed indication, user, anatomy, technology and operating principle with this actual scope; record differences and unresolved facts.
§ 870.1415 Coronary vascular physiologic simulation software device. (a) Identification. A coronary vascular physiologic simulation software device is a prescription device that provides simulated functional assessment of blood flow in the coronary vascular system using data extracted from medical device imaging to solve algorithms and yield simulated metrics of physiologic information ( e.g., blood flow, coronary flow reserve, fractional flow reserve, myocardial perfusion). A coronary vascular physiologic simulation software device is intended to generate results for use and review by a qualified clinician. (b) Classification. Class II (special controls). The special controls for this device are: (1) Adequate software verification and validation based on comprehensive hazard analysis, with identification of appropriate mitigations, must be performed, including: (i) Full characterization of the technical parameters of the software, including: (A) Any proprietary algorithm(s) used to model the vascular anatomy; and (B) Adequate description of the expected impact of all applicable image acquisition hardware features and characteristics on performance and any associated minimum specifications; (ii) Adequate consideration of privacy and security issues in the system design; and (iii) Adequate mitigation of the impact of failure of any subsystem components ( e.g., signal detection and analysis, data storage, system communications and cybersecurity) with respect to incorrect patient reports and operator failures. (2) Adequate non-clinical performance testing must be provided to demonstrate the validity of computational modeling methods for flow measurement; and (3) Clinical data supporting the proposed intended use must be provided, including the following: (i) Output measure(s) must be compared to a clinically acceptable method and must adequately represent the simulated measure(s) the device provides in an accurate and reproducible manner; (ii) Clinical utility of the device measurement accuracy must be demonstrated by comparison to that of other available diagnostic tests ( e.g., from literature analysis); (iii) Statistical performance of the device within clinical risk strata ( e.g., age, relevant comorbidities, disease stability) must be reported; (iv) The dataset must be adequately representative of the intended use population for the device ( e.g., patients, range of vessel sizes, imaging device models). Any selection criteria or limitations of the samples must be fully described and justified; (v) Statistical methods must consider the predefined endpoints: (A) Estimates of probabilities of incorrect results must be provided for each endpoint, (B) Where multiple samples from the same patient are used, statistical analysis must not assume statistical independence without adequate justification, and (C) The report must provide appropriate confidence intervals for each performance metric; (vi) Sensitivity and specificity must be characterized across the range of available measurements; (vii) Agreement of the simulated measure(s) with clinically acceptable measure(s) must be assessed across the full range of measurements; (viii) Comparison of the measurement performance must be provided across the range of intended image acquisition hardware; and (ix) If the device uses a cutoff threshold or operates across a spectrum of disease, it must be established prior to validation, and it must be justified as to how it was determined and clinically validated; (4) Adequate validation must be performed and controls implemented to characterize and ensure consistency ( i.e., repeatability and reproducibility) of measurement outputs: (i) Acceptable incoming image quality control measures and the resulting image rejection rate for the clinical data must be specified, and (ii) Data must be provided within the clinical validation study or using equivalent datasets demonstrating the consistency ( i.e., repeatability and reproducibility) of the output that is representative of the range of data quality likely to be encountered in the intended use population and relevant use conditions in the intended use environment; (A) Testing must be performed using multiple operators meeting planned qualification criteria and using the procedure that will be implemented in the production use of the device, and (B) The factors ( e.g., medical imaging dataset, operator) must be identified regarding which were held constant and which were varied during the evaluation, and a description must be provided for the computations and statistical analyses used to evaluate the data; (5) Human factors evaluation and validation must be provided to demonstrate adequate performance of the user interface to allow for users to accurately measure intended parameters, particularly where parameter settings that have impact on measurements require significant user intervention; and (6) Device labeling must be provided that adequately describes the following: (i) The device's intended use, including the type of imaging data used, what the device measures and outputs to the user, whether the measure is qualitative or quantitative, the clinical indications for which it is to be used, and the specific population for which the device use is intended; (ii) Appropriate warnings specifying the intended patient population, identifying anatomy and image acquisition factors that may impact measurement results, and providing cautionary guidance for interpretation of the provided measurements; (iii) Key assumptions made in the calculation and determination of simulated measurements; (iv) The measurement performance of the device for all presented parameters, with appropriate confidence intervals, and the supporting evidence for this performance. Per-vessel clinical performance, including where applicable localized performance according to vessel and segment, must be included as well as a characterization of the measurement error across the expected range of measurement for key parameters based on the clinical data; (v) A detailed description of the patients studied in the clinical validation ( e.g., age, gender, race or ethnicity, clinical stability, current treatment regimen) as well as procedural details of the clinical study ( e.g., scanner representation, calcium scores, use of beta-blockers or nitrates); and (vi) Where significant human interface is necessary for accurate analysis, adequately detailed description of the analysis procedure using the device and any data features that could affect accuracy of results. [80 FR 63673, Oct. 21, 2015]
Read the identification, classification, conditions and referenced limitations in the cited section. A numeric reference match is not a buyer classification or exemption determination.
Historical FDA comparison
All statistics in this section use decisions dated 2021-01-01 to 2025-12-31. The partial 2026 update below is excluded from these distributions.
There are 0 valid recent date pairs. Distribution summaries require at least 20; older records are not substituted for a current benchmark.
Statistical source: FDA openFDA 510(k) decision dataset. Partition 1 Download the identified records and dates (CSV).
Deduplicate by official submission ID across the complete current manifest partitions. Select exact primary product code, K-number format and the stated SE decision codes with valid dates. Recent distributions use the five complete calendar years preceding the latest valid endpoint decision year. Partial-year counts compare equal January-to-cutoff periods. Quartiles use linear interpolation at (n-1)*p and are withheld below 20 valid date pairs. The analysis n describes only its declared complete-year window; selected_se_n separately counts all selected recorded dates through the cutoff.
2 selected records across all observed dates; 0 other/invalid identifier or decision-date records excluded. 0 missing or invalid date pairs in the five-year window.
Date fields: date_received → decision_date. Quantiles: Hyndman–Fan type 7: linear interpolation at (n − 1) × p; displayed to one decimal; n ≥ 20 valid pairs.
Receipt-to-decision calendar elapsed time includes time outside active FDA review; it is not FDA review time, a promised project timeline or an estimate of future clearance. This selected recorded cohort does not include all applications or establish a success probability, predicate suitability, market size, current market availability or legal authorization for another product.
Calculation fda-buyer-research-3 · database cutoff 2026-09-27. CSV rows identify each official K-number, cohort, date pair, exclusion reason and source version.
Separate partial-year update
0 selected decisions from 2026-01-01 to 2026-09-27. The equivalent previous-year period contains 0 decisions through 2025-09-27. These counts describe the records; they are not market growth or submission success rates.
Named records to investigate
These dated records may come from 2026 or earlier years. They are a separate investigation list, not the five-year statistical cohort. Compare the actual indications and technology before considering a record as a comparator.
Supporting documents actually acquired
Read the source context, then compare the evidence with your design. Topic locations below are text matches, including possible limitations or negative statements; they are not a mandatory test list.
The documents are a bounded sample of acquired summaries, not complete evidence coverage of the cohort.
Known context: US. Match the intended use and design with the recorded category before treating it as applicable.
| Source fact | Recorded value |
|---|---|
| FDA product code | QEK [1] |
| Generic device category | Angiographic Coronary Vascular Physiologic Simulation Software [1] |
| Recorded scope | An angiographic coronary vascular physiologic simulation software device is intended to aid in the identification of functionally significant cardiovascular disease. [1] |
| Recorded class | 2 [1] |
| Regulation | 870.1415 [1] |
| Medical specialty | Cardiovascular [1] |
Use this checklist to gather your business or product details before speaking with a specialist. The items below explain what to record and suggest useful supporting documents. You can add your own answers in the editable project brief.
Put your proposed label and design beside the quoted definition. Record matching facts, differences and missing facts separately; naming the category alone cannot resolve scope.
Useful evidence: Proposed indication/design and a definition-to-product comparison with source locators.
Record the applicable paragraph, conditions and cross-referenced limitations after specialist review. Keep a claimed exemption separate from actual establishment, listing and quality-system responsibilities.
Useful evidence: Dated classification/route rationale and the current provisions relied on, with unresolved conditions.
No selected decision falls in the complete-year window. Any named records shown are separately dated historical or current-year research. Obtain their actual indications and assess the current route before using a comparator; the absence of a recent record does not establish an exemption or a route.
Useful evidence: Proposed indication/design, the dated named record if available, and a current route/comparator research rationale.
For each comparison, record the different materials, hardware, software functions and operating conditions. Link each difference to existing evidence or an unresolved evaluation task.
Useful evidence: A three-column matrix: comparator fact / your design fact / evidence or unresolved gap.
This recent cohort has fewer than 20 valid date pairs, so it supplies no median or percentile benchmark. Ask for a schedule based on actual preparation, evidence gaps, interactions and response assumptions; keep any historical decision context separately dated.
Useful evidence: Document/test readiness, unresolved route/evidence tasks and the assumptions behind the specialist’s proposed sequence.
Read the official document in context. The audit details identify the precise locators and preserved versions used for this page.
2026-10-05 · retrieved 2026-10-06
Source key D01 · snapshot 936de5f5d47b9293b702fc32512a79173969fb788c74a63d9b91abe73f3b86a5
2026-10-05 · retrieved 2026-10-06
Source key D01 · snapshot 5a86994ba49a37e71e09be96803fd51981c6c43eaa96caab41aea2b188bfe002
Tue, 07 Jan 2020 16:00:06 GMT · retrieved 2026-10-07
Source key D02 · snapshot 413bf4a9b6b5ea1fe8acd1aba63706f831f64145514f51848ebdbe61d4e4d644
Tue, 08 Jan 2019 17:12:04 GMT · retrieved 2026-10-07
Source key D02 · snapshot 8829ccf9f0c2f4cfed00cdc5c409c784ef4cbd854d02c3558e05cdeaec725f9d
Thu, 01 Oct 2026 22:01:48 GMT · retrieved 2026-10-06
Source key D04 · snapshot 2fb992918a3879de132b47a33c856da2b3234ee3d96cfd79fab03acf30512496
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