FDA record research

Lung Computed Tomography System, Computer-Aided Detection (OEB) — FDA decisions, comparisons and evidence

The 2021–2025 analysis contains 8 selected substantially-equivalent FDA decisions under primary product code OEB. Use it to compare documented submissions and evidence with your product. A separate 2026 update contains 1 decisions through 2026-09-27. The latest selected decision across the acquired endpoint is dated 2026-05-27. Neither set establishes a suitable predicate or the route for your device. The complete-year window has 8 decisions; the separate all-observed-date count is 20. These denominators describe different date ranges.

Evidence retrieved 2026-10-07. Source versions and topic-specific limits are listed below.

Recorded scope and its declared regulatory reference

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.

What scope does the FDA record describe?

To assist radiologists in the review of multi-slice computed tomography (msct) exams of the chest and highlight potential nodules that the radiologist should review. A computer aided diagnosis, lung computed tomography system is a class 3 device under product code NRR.

Compare the proposed indication, user, anatomy, technology and operating principle with this actual scope; record differences and unresolved facts.

Cited source

Which current section does the record cite?

§ 892.2050 Medical image management and processing system. (a) Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements. (b) Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern). [63 FR 23387, Apr. 29, 1998, as amended at 86 FR 20284, Apr. 19, 2021]

Read the identification, classification, conditions and referenced limitations in the cited section. A numeric reference match is not a buyer classification or exemption determination.

Cited source

Historical FDA comparison

2021–2025: five complete calendar years

Primary code OEB

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.

8Selected decisions in these five years

WithheldMedian receipt-to-decision calendar days

8Valid date pairs in the distribution

There are 8 valid recent date pairs. Distribution summaries require at least 20; older records are not substituted for a current benchmark.

20212

20221

20232

20240

20253

Statistical source: FDA openFDA 510(k) decision dataset. Partition 1 Download the identified records and dates (CSV).

Filters, exclusions and reproducible calculation

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.

20 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

2026 decisions through 2026-09-27

1 selected decisions from 2026-01-01 to 2026-09-27. The equivalent previous-year period contains 2 decisions through 2025-09-27. These counts describe the records; they are not market growth or submission success rates.

Named records to investigate

Latest decisions across the database

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.

Official record / device	Recorded applicant	Decision	Recorded type	Calendar days
K254075 ↗Synapse Lung Nodule AI	Fujifilm Corporation	2026-05-27	Traditional	160
K251203 ↗AVIEW Lung Nodule CAD	Coreline Soft Co., Ltd.	2025-12-03	Traditional	229
K240554 ↗InferRead Lung CT.AI	Infervision Medical Technology Co., Ltd.	2025-05-16	Traditional	443
K242919 ↗V5med Lung AI	V5med, Inc.	2025-03-27	Traditional	184
K231157 ↗syngo.CT Lung CAD (Version VD30)	Siemens Healthcare GmbH	2023-07-19	Traditional	86
K221592 ↗AVIEW Lung Nodule CAD	Coreline Soft Co., Ltd.	2023-02-24	Traditional	267
K221612 ↗ClearRead CT	Riverain Technologies, Inc.	2022-12-05	Traditional	185
K203258 ↗syngo.CT Lung CAD	Siemens Healthcare GmbH	2021-03-31	Traditional	146

Supporting documents actually acquired

Go beyond the database row

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.

K254075 · official summary PDF ↗

Term mention: Clinical performance · PDF page 14 Term occurrence only; read the original passage, including limitations and negation.
Term mention: Performance testing · PDF page 16 Term occurrence only; read the original passage, including limitations and negation.
Term mention: Cybersecurity · PDF page 16 Term occurrence only; read the original passage, including limitations and negation.

K251203 · official summary PDF ↗

Term mention: Software verification · PDF page 6 Term occurrence only; read the original passage, including limitations and negation.
Term mention: Cybersecurity · PDF page 6 Term occurrence only; read the original passage, including limitations and negation.

K240554 · official summary PDF ↗

Term mention: Performance testing · PDF page 8 Term occurrence only; read the original passage, including limitations and negation.
Term mention: Software verification · PDF page 10 Term occurrence only; read the original passage, including limitations and negation.
Term mention: Cybersecurity · PDF page 10 Term occurrence only; read the original passage, including limitations and negation.

The documents are a bounded sample of acquired summaries, not complete evidence coverage of the cohort.

Recorded classification context

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	OEB [1]
Generic device category	Lung Computed Tomography System, Computer-Aided Detection [1]
Recorded scope	To assist radiologists in the review of multi-slice computed tomography (msct) exams of the chest and highlight potential nodules that the radiologist should review. A computer aided diagnosis, lung computed tomography system is a class 3 device under product code NRR. [1]
Recorded class	2 [1]
Regulation	892.2050 [1]
Medical specialty	Radiology [1]

Build a comparison that explains the differences

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.

Which specific part of the recorded scope fits or differs?
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.
Have the cited section and its limitations been reviewed?
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.
Compare your intended use with a named decision
Choose a named record above. Put your proposed claim beside its actual indications-for-use statement. Record different patients, users, anatomy, settings and output claims; do not treat a shared code as proof of equivalence.
Useful evidence: Your draft indications for use + the selected official summary and its exact page.
Explain the technology and evidence differences
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.
Prepare a scope-based schedule without a sparse timing benchmark
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.

Work packages and dependencies

Conditional: FDA 510(k) Submission Services — Review the supplied facts and evidence gaps before confirming the service scope.
Optional: Find FDA US Agent Services | Compare & Get Quotes — Include only if your product, actor and delivery needs justify this additional scope. Confirm the responsibility and evidence handoff with the coordinating specialist.
Optional: FDA QMSR Transition & Inspection Readiness (ISO 13485 Alignment) — Include only if your product, actor and delivery needs justify this additional scope. Confirm the responsibility and evidence handoff with the coordinating specialist.

What needs to happen first

FDA 510(k) Submission Services → Find FDA US Agent Services | Compare & Get Quotes: Confirm the main product/actor scope and evidence gaps before deciding whether to commission this additional service.
FDA 510(k) Submission Services → FDA QMSR Transition & Inspection Readiness (ISO 13485 Alignment): Confirm the main product/actor scope and evidence gaps before deciding whether to commission this additional service.

Questions for providers

Which of the named OEB decisions are actually comparable to our proposed indications and technology, and which would you exclude?
Which evidence differences prevent us from using the comparison yet, and what deliverable resolves each one?
Does your schedule separate submission preparation, testing, FDA interactions and customer response time? What assumptions change it?

Sources and data dates

Read the official document in context. The audit details identify the precise locators and preserved versions used for this page.