Rule2025-10789
Medical Devices; Radiology Devices; Classification of the Radiological Computer-Assisted Detection and Diagnosis Software
Primary source
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Published
June 13, 2025
Effective
June 13, 2025
Issuing agencies
Health and Human Services DepartmentFood and Drug Administration
Abstract
The Food and Drug Administration (FDA, the Agency, or we) is classifying the radiological computer-assisted detection and diagnosis software into class II (special controls). The special controls that apply to the device type are identified in this order and will be part of the codified language for the radiological computer-assisted detection and diagnosis software's classification. We are taking this action because we have determined that classifying the device into class II (special controls) will provide a reasonable assurance of safety and effectiveness of the device. We believe this action will also enhance patients' access to beneficial innovative devices, in part by reducing regulatory burdens.
Full Text
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<title>Federal Register, Volume 90 Issue 113 (Friday, June 13, 2025)</title>
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[Federal Register Volume 90, Number 113 (Friday, June 13, 2025)]
[Rules and Regulations]
[Pages 24969-24971]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2025-10789]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration
21 CFR Part 892
[Docket No. FDA-2025-N-1529]
Medical Devices; Radiology Devices; Classification of the
Radiological Computer-Assisted Detection and Diagnosis Software
AGENCY: Food and Drug Administration, HHS.
ACTION: Final amendment; final order.
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SUMMARY: The Food and Drug Administration (FDA, the Agency, or we) is
classifying the radiological computer-assisted detection and diagnosis
software into class II (special controls). The special controls that
apply to the device type are identified in this order and will be part
of the codified language for the radiological computer-assisted
detection and diagnosis software's classification. We are taking this
action because we have determined that classifying the device into
class II (special controls) will provide a reasonable assurance of
safety and effectiveness of the device. We believe this action will
also enhance patients' access to beneficial innovative devices, in part
by reducing regulatory burdens.
DATES: This order is effective June 13, 2025. The classification was
applicable on May 24, 2018.
FOR FURTHER INFORMATION CONTACT: Dina Jerebitski, Center for Devices
and Radiological Health, Food and Drug Administration, 10903 New
Hampshire Ave., Bldg. 66, Rm. 3574, Silver Spring, MD 20993-0002, 301-
796-2411, <a href="/cdn-cgi/l/email-protection#eeaa87808fc0a48b9c8b8c879a9d8587ae888a8fc086869dc0898198"><span class="__cf_email__" data-cfemail="36725f5857187c534453545f42455d5f76505257185e5e4518515940">[email protected]</span></a>.
SUPPLEMENTARY INFORMATION:
I. Background
Upon request, FDA has classified radiological computer-assisted
detection and diagnosis software as class II (special controls), which
we have determined will provide a reasonable assurance of safety and
effectiveness. In addition, we believe this action will enhance
patients' access to beneficial innovation, in part by reducing
regulatory burdens by placing the device into a lower device class than
the automatic class III assignment.
The automatic assignment of class III occurs by operation of law
and without any action by FDA, regardless of the level of risk posed by
the new device. Any device that was not in commercial distribution
before May 28, 1976, is automatically classified as, and remains
within, class III and requires premarket approval unless and until FDA
takes an action to classify or reclassify the device (see 21 U.S.C.
360c(f)(1)). We refer to these devices as ``postamendments devices''
because they were not in commercial distribution prior to the date of
enactment of the Medical Device Amendments of 1976, which amended the
Federal Food, Drug, and Cosmetic Act (FD&C Act).
FDA may take a variety of actions in appropriate circumstances to
classify or reclassify a device into class I or II. We may issue an
order finding a new device to be substantially equivalent under section
513(i) of the FD&C Act (21 U.S.C. 360c(i)) to a predicate device that
does not require premarket approval. We determine whether a new device
is substantially equivalent to a predicate device by means of the
procedures for premarket notification under section 510(k) of the FD&C
Act (21 U.S.C. 360(k)) and part 807 (21 CFR part 807).
FDA may also classify a device through ``De Novo'' classification,
a common name for the process authorized under section 513(f)(2) of the
FD&C Act (see also part 860, subpart D (21 CFR part 860, subpart D)).
Section 207 of the Food and Drug Administration Modernization Act of
1997 (Pub. L. 105-115) established the first procedure for De Novo
classification. Section 607 of the Food and Drug Administration Safety
and Innovation Act (Pub. L. 112-144) modified the De Novo application
process by adding a second procedure. A device sponsor may utilize
either procedure for De Novo classification.
Under the first procedure, the person submits a 510(k) for a device
that has not previously been classified. After receiving an order from
FDA classifying the device into class III under section 513(f)(1) of
the FD&C Act, the person then requests a classification under section
513(f)(2).
Under the second procedure, rather than first submitting a 510(k)
and then a request for classification, if the person determines that
there is no legally marketed device upon which to base a determination
of substantial equivalence, that person requests a classification under
section 513(f)(2) of the FD&C Act.
Under either procedure for De Novo classification, FDA is required
to classify the device by written order within 120 days. The
classification will be according to the criteria under section
513(a)(1) of the FD&C Act. Although the device was automatically placed
within class III, the De Novo classification is considered to be the
initial classification of the device.
We believe this De Novo classification will enhance patients'
access to beneficial innovation, in part by reducing regulatory
burdens. When FDA classifies a device into class I or II via the De
Novo process, the device can serve as a predicate for future devices of
that type, including for 510(k)s (see section 513(f)(2)(B)(i) of the
FD&C Act). As a result, other device sponsors do not have to submit a
De Novo request or premarket approval application to market a
substantially equivalent device (see section 513(i) of the FD&C Act,
defining ``substantial equivalence''). Instead, sponsors can use the
less burdensome 510(k) process, when necessary, to market their device.
II. De Novo Classification
On February 5, 2018, FDA received Imagen Technologies, Inc.'s
request for De Novo classification of the OsteoDetect. FDA reviewed the
request in order to classify the device under the criteria for
classification set forth in section 513(a)(1) of the FD&C Act.
We classify devices into class II if general controls by themselves
are insufficient to provide reasonable assurance of safety and
effectiveness, but there is sufficient information to establish special
controls that, in combination with the general controls, provide
reasonable assurance of the safety and effectiveness of the device for
its intended use (see section 513(a)(1)(B) of the FD&C Act). After
review of the information submitted in the request, we determined that
the device can be classified into class II with the establishment of
special controls. FDA has determined that these special controls, in
addition to the general controls, will provide reasonable assurance of
the safety and effectiveness of the device.
[[Page 24970]]
Therefore, on May 24, 2018, FDA issued an order to the requester
classifying the device into class II. FDA is codifying the
classification of the device by adding 21 CFR 892.2090.\1\ We have
named the generic type of device ``radiological computer-assisted
detection and diagnosis software,'' and it is identified as an image
processing device intended to aid in the detection, localization, and
characterization of fracture, lesions, or other disease-specific
findings on acquired medical images (e.g., radiography, magnetic
resonance, computed tomography). The device detects, identifies, and
characterizes findings based on features or information extracted from
images, and provides information about the presence, location, and
characteristics of the findings to the user. The analysis is intended
to inform the primary diagnostic and patient management decisions that
are made by the clinical user. The device is not intended as a
replacement for a complete clinician's review or their clinical
judgment that takes into account other relevant information from the
image or patient history.
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\1\ FDA notes that the ACTION caption for this final order is
styled as ``Final amendment; final order,'' rather than ``Final
order.'' Beginning in December 2019, this editorial change was made
to indicate that the document ``amends'' the Code of Federal
Regulations. The change was made in accordance with the Office of
Federal Register's (OFR) interpretations of the Federal Register Act
(44 U.S.C. chapter 15), its implementing regulations (1 CFR 5.9 and
parts 21 and 22), and the Document Drafting Handbook.
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FDA has identified the following risks to health associated
specifically with this type of device and the measures required to
mitigate these risks in table 1.
Table 1--Radiological Computer-Assisted Detection and Diagnosis Software
Risks and Mitigation Measures
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Identified risks to health Mitigation measures
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False positive results.................... General controls and special
controls (1) (21 CFR
892.2090(b)(1)) and (2) (21
CFR 892.2090(b)(2)).
False negative results.................... General controls and special
controls (1) (21 CFR
892.2090(b)(1)) and (2) (21
CFR 892.2090(b)(2)).
Device misuse (analyzing images from General controls and special
unintended patient population or of an controls (1) (21 CFR
unintended anatomical site; or images 892.2090(b)(1)) and (2) (21
acquired with an unintended modality, CFR 892.2090(b)(2)).
incompatible imaging hardware, or
incompatible image acquisition
parameters) resulting in lower device
performance (inappropriate detection/
diagnosis information being displayed to
the end user).
Device failure leading to absence of General controls and special
results, delay of results, or incorrect controls (1) (21 CFR
results, leading to delayed or inaccurate 892.2090(b)(1)) and (2) (21
patient diagnosis. CFR 892.2090(b)(2)).
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FDA has determined that special controls, in combination with the
general controls, address these risks to health and provide reasonable
assurance of safety and effectiveness. For a device to fall within this
classification, and thus avoid automatic classification in class III,
it would have to comply with the special controls named in this final
order. The necessary special controls appear in the regulation codified
by this final order. This device is subject to premarket notification
requirements under section 510(k) of the FD&C Act.
III. Analysis of Environmental Impact
The Agency has determined under 21 CFR 25.34(b) that this action is
of a type that does not individually or cumulatively have a significant
effect on the human environment. Therefore, neither an environmental
assessment nor an environmental impact statement is required.
IV. Paperwork Reduction Act of 1995
This final order establishes special controls that refer to
previously approved collections of information found in other FDA
regulations and guidance. These collections of information are subject
to review by the Office of Management and Budget (OMB) under the
Paperwork Reduction Act of 1995 (44 U.S.C. 3501-3521). The collections
of information in part 860, subpart D, regarding De Novo Classification
have been approved under OMB control number 0910-0844; the collections
of information in 21 CFR part 814, subpart A through E, regarding
premarket approval have been approved under OMB control number 0910-
0231; the collections of information in part 807, subpart E, regarding
premarket notification submissions have been approved under OMB control
number 0910-0120; the collections of information in 21 CFR part 820
regarding quality system regulation have been approved under OMB
control number 0910-0073; and the collections of information in 21 CFR
part 801 regarding labeling have been approved under OMB control number
0910-0485.
List of Subjects in 21 CFR Part 892
Medical devices, Radiation protection, X-rays.
Therefore, under the Federal Food, Drug, and Cosmetic Act and under
authority delegated to the Commissioner of Food and Drugs, 21 CFR part
892 is amended as follows:
PART 892--RADIOLOGY DEVICES
0
1. The authority citation for part 892 continues to read as follows:
Authority: 21 U.S.C. 351, 360, 360c, 360e, 360j, 360l, 371.
0
2. Add Sec. 892.2090 to subpart B to read as follows:
Sec. 892.2090 Radiological computer-assisted detection and diagnosis
software.
(a) Identification. A radiological computer-assisted detection and
diagnostic software is an image processing device intended to aid in
the detection, localization, and characterization of fracture, lesions,
or other disease-specific findings on acquired medical images (e.g.,
radiography, magnetic resonance, computed tomography). The device
detects, identifies, and characterizes findings based on features or
information extracted from images, and provides information about the
presence, location, and characteristics of the findings to the user.
The analysis is intended to inform the primary diagnostic and patient
management decisions that are made by the clinical user. The device is
not intended as a replacement for a complete clinician's review or
their clinical judgment that takes into account other relevant
information from the image or patient history.
[[Page 24971]]
(b) Classification. Class II (special controls). The special
controls for this device are:
(1) Design verification and validation must include:
(i) A detailed description of the image analysis algorithm,
including a description of the algorithm inputs and outputs, each major
component or block, how the algorithm and output affects or relates to
clinical practice or patient care, and any algorithm limitations.
(ii) A detailed description of pre-specified performance testing
protocols and dataset(s) used to assess whether the device will provide
improved assisted-read detection and diagnostic performance as intended
in the indicated user population(s), and to characterize the standalone
device performance for labeling. Performance testing includes
standalone test(s), side-by-side comparison(s), and/or a reader study,
as applicable.
(iii) Results from standalone performance testing used to
characterize the independent performance of the device separate from
aided user performance. The performance assessment must be based on
appropriate diagnostic accuracy measures (e.g., receiver operator
characteristic plot, sensitivity, specificity, positive and negative
predictive values, and diagnostic likelihood ratio). Devices with
localization output must include localization accuracy testing as a
component of standalone testing. The test dataset must be
representative of the typical patient population with enrichment made
only to ensure that the test dataset contains a sufficient number of
cases from important cohorts (e.g., subsets defined by clinically
relevant confounders, effect modifiers, concomitant disease, and
subsets defined by image acquisition characteristics) such that the
performance estimates and confidence intervals of the device for these
individual subsets can be characterized for the intended use population
and imaging equipment.
(iv) Results from performance testing that demonstrate that the
device provides improved assisted-read detection and/or diagnostic
performance as intended in the indicated user population(s) when used
in accordance with the instructions for use. The reader population must
be comprised of the intended user population in terms of clinical
training, certification, and years of experience. The performance
assessment must be based on appropriate diagnostic accuracy measures
(e.g., receiver operator characteristic plot, sensitivity, specificity,
positive and negative predictive values, and diagnostic likelihood
ratio). Test datasets must meet the requirements described in paragraph
(b)(1)(iii) of this section.
(v) Appropriate software documentation, including device hazard
analysis, software requirements specification document, software design
specification document, traceability analysis, system level test
protocol, pass/fail criteria, testing results, and cybersecurity
measures.
(2) Labeling must include the following:
(i) A detailed description of the patient population for which the
device is indicated for use.
(ii) A detailed description of the device instructions for use,
including the intended reading protocol and how the user should
interpret the device output.
(iii) A detailed description of the intended user, and any user
training materials or programs that address appropriate reading
protocols for the device, to ensure that the end user is fully aware of
how to interpret and apply the device output.
(iv) A detailed description of the device inputs and outputs.
(v) A detailed description of compatible imaging hardware and
imaging protocols.
(vi) Warnings, precautions, and limitations must include situations
in which the device may fail or may not operate at its expected
performance level (e.g., poor image quality or for certain
subpopulations), as applicable.
(vii) A detailed summary of the performance testing, including test
methods, dataset characteristics, results, and a summary of sub-
analyses on case distributions stratified by relevant confounders, such
as anatomical characteristics, patient demographics and medical
history, user experience, and imaging equipment.
Dated: June 9, 2025.
Grace R. Graham,
Deputy Commissioner for Policy, Legislation, and International Affairs.
[FR Doc. 2025-10789 Filed 6-12-25; 8:45 am]
BILLING CODE 4164-01-P
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