AI-Rad Companion (Pulmonary) is image processing software that provides quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the evaluation and assessment of disease of the lungs.

It provides the following functionality:

· Segmentation and measurements of complete lung and lung lobes

· Identification of areas with lower Hounsfield values in comparison to a predefined threshold for complete lung and lung lobes
· Providing an interface to external Medical Device syngo.CT Lung CAD
· Segmentation and measurements of solid lung nodules
· Dedication of found lung nodules to corresponding lung lobe
· Correlation of segmented lung nodules of current scan with known priors and quantitative assessment of changes of the correlated data.
· Identification of areas with elevated Hounsfield values, where areas with elevated versus high opacities are distinguished.

The software has been validated for data from Siemens (filtered backprojection and iterative reconstruction), GE Healthcare (filtered backprojection reconstruction), and Philips (filtered backprojection reconstruction).

Only DICOM images of adult patients are considered to be valid input.

Device Description

AI-Rad Companion (Pulmonary) SW version VA20 is an enhancement to the previously cleared device AI-Rad Companion (Pulmonary) K183271 that utilizes machine and deep learning algorithms to provide quantitative and qualitative analysis to computed tomography DICOM images to support qualified clinicians in the evaluation and assessment of disease of the thorax.

As an update to the previously cleared device, the following modifications have been made:

Modified Indications for Use Statement The indications for use statement was updated to include descriptive text for the lung lesion follow feature.
Updated Subject Device Claims List The claims list was updated to include claim pertaining to the lung lesion follow up feature.
Lung Lesion Follow-up Assessment of current and prior lesions This feature provides the possibility to compare currently segmented lung lesions with corresponding priors and changes to the correlated data are assessed quantitatively.
Pulmonary Density Assessment

This feature provides the possibility to segment opacity regions inside the lung using an AI algorithm. AI-Rad Companion (Pulmonary) counts image voxels inside opacity regions and calculates the percentages of these voxels relative to the total number of voxels per lobe. lung and in total. Afterwards, each of the five lung lobes is assigned a score ranging from 0 to 4 based on the percentage of opacity as follows: 0 (0%), 1 (1%-25%), 2 (26%-50%), 3 (51%-75%), or 4 (76%-100%). Then a summation of the five lobe scores (range of possible scores, 0-20) are generated in the device outputs. This functionality is commercially available on the Siemens syngo.CT Extended Functionality (K203699).

. Bi-Directional Lesion Diameter
This feature provides an additional measurement derived from the existing segmentation contour of a lung lesion. The existing list of measurements is extended with the maximum orthogonal diameter in 2D (short axis diameter) which is orthogonal to the lesion's maximum 2D diameter (2D diameter, long axis diameter). This functionality is commercially available on the Siemens syngo.CT Extended Functionality (K203699).
. Architecture Enhancement for on premise Edge deployment
- The system supports the existing cloud deployment as well as an on premise "edge" deployment. The system remains hosted in the teamplay digital health platform and remains driven by the AI-Rad Companion Engine. Now the edge deployment implies that the processing of clinical data and the generation of results can be performed onpremises within the customer network. The edge system is fully connected to the cloud for monitoring and maintenance of the system from remote.

AI/ML Overview

The provided document, a 510(k) summary for Siemens Healthcare GmBh's AI-Rad Companion (Pulmonary) SW version VA20, describes the device, its intended use, and the non-clinical tests performed to demonstrate its safety and effectiveness.

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

Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics for all functionalities. However, it does state some performance metrics for one specific feature:

Acceptance Criteria (Implied)	Reported Device Performance
Lesion Follow-up Feature: Adequate identification of lesion pairs	Sensitivity: 94.3%
	Average Positive Predictive Value (PPV): 99.1% (across all subgroups)

Missing Information: The document does not provide acceptance criteria or performance results for other key functionalities of the AI-Rad Companion (Pulmonary), such as:

Segmentation and measurements of complete lung and lung lobes.
Identification of areas with lower Hounsfield values.
Segmentation and measurements of solid lung nodules.
Dedication of found lung nodules to corresponding lung lobe.
Identification of areas with elevated Hounsfield values (Pulmonary Density Assessment).
Bi-directional lesion diameter measurements.

Study Details:

The provided document describes a non-clinical bench test specifically for the lesion follow-up feature. It explicitly states: "No clinical tests were conducted to test the performance and functionality of the modifications introduced within AI-Rad Companion (Pulmonary)." This implies that the reported performance metrics are from an algorithm-only (standalone) performance evaluation, without human-in-the-loop.

Here's what can be extracted about the study:

Sample Size and Data Provenance:
- Test Set Sample Size: 200 cases were used to evaluate the lesion follow-up feature.
- Data Provenance: Not explicitly stated. The document mentions validation for data from Siemens, GE Healthcare, and Philips (reconstruction types specified), but it does not specify the country of origin of the data or whether it was retrospective or prospective.
Number of Experts and Qualifications:
- The document does not provide information on the number of experts used to establish ground truth or their specific qualifications for the test set.
Adjudication Method:
- The document does not specify any adjudication method (e.g., 2+1, 3+1, none) for the test set. Since it's a non-clinical bench test of the algorithm's ability to identify lesion pairs, it's possible that a different form of ground truth establishment (e.g., based on established physical measurements or derived from existing clinical reports) was used rather than direct expert consensus on each case.
Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- No MRMC study was done. The document explicitly states: "No clinical tests were conducted to test the performance and functionality of the modifications introduced within AI-Rad Companion (Pulmonary)." Therefore, there is no effect size reported for human readers improving with AI vs. without AI assistance.
Standalone (Algorithm Only) Performance:
- Yes, a standalone study was done for the lesion follow-up feature. The reported sensitivity and PPV are for the algorithm's performance in identifying lesion pairs.
Type of Ground Truth Used:
- The document does not explicitly state the type of ground truth used for the lesion follow-up test. It mentions "evaluation of 200 cases to identify lesion pairs," which suggests that a definitive ground truth for paired lesions was available for these 200 cases. This could range from expert consensus, to prior established measurements, or structured clinical reports that define lesion pairs.
Training Set Sample Size:
- The document does not specify the sample size used for the training set. It only mentions the use of "machine and deep learning algorithms."
How Ground Truth for Training Set Was Established:
- The document does not describe how the ground truth for the training set was established.

Summary

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August 11, 2022

Image /page/0/Picture/1 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA logo on the right. The FDA logo is in blue and includes the letters "FDA" in a square, followed by the words "U.S. FOOD & DRUG ADMINISTRATION".

Siemens Healthcare GmBh % Kira Kuzmenchuk Regulatory Affairs Specialist 40 Liberty Blvd. Mail Code 65-1A MALVERN PA 19355

Re: K213713

Trade/Device Name: AI-Rad Companion (Pulmonary) Regulation Number: 21 CFR 892.1750 Regulation Name: Computed tomography x-ray system Regulatory Class: Class II Product Code: JAK, QIH Dated: July 15, 2022 Received: July 18, 2022

Dear Kira Kuzmenchuk:

We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for

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devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

Laurel Burk, Ph.D. Assistant Director Diagnostic X-Ray Systems Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known)

K213713

Device Name AI-Rad Companion (Pulmonary)

Indications for Use (Describe)

Al-Rad Companion (Pulmonary) is image processing software that provides quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the evaluation and assessment of disease of the lungs.

It provides the following functionality:

· Segmentation and measurements of complete lung and lung lobes

· Identification of areas with lower Hounsfield values in comparison to a predefined threshold for complete lung and lung lobes
· Providing an interface to external Medical Device syngo.CT Lung CAD
· Segmentation and measurements of solid lung nodules
· Dedication of found lung nodules to corresponding lung lobe
· Correlation of segmented lung nodules of current scan with known priors and quantitative assessment of changes of the correlated data.
· Identification of areas with elevated Hounsfield values, where areas with elevated versus high opacities are distinguished.

Only DICOM images of adult patients are considered to be valid input.

Type of Use (Select one or both, as applicable)

☑ Prescription Use (Part 21 CFR 801 Subpart D)
☐ Over-The-Counter Use (21 CFR 801 Subpart C)

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Image /page/3/Picture/1 description: The image shows the Siemens Healthineers logo. The word "SIEMENS" is in teal, and the word "Healthineers" is in orange. To the right of the words is a graphic of orange dots.

510(k) SUMMARY FOR AI-RAD COMPANION (Pulmonary) SW version VA20

Submitted by: Siemens Medical Solutions USA, Inc. 40 Liberty Boulevard Malvern, PA 19355 Date Prepared: November 23, 2021

This summary of 510(k) safety and effectiveness information is being submitted in accordance with the requirements of Safe Medical Devices Act of 1990 and 21 CFR §807.92.

1. Submitter

Importer/Distributor	Siemens Medical Solutions USA, Inc.40 Liberty BoulevardMalvern, PA 19355Mail Code: 65-1ARegistration Number: 2240869
Manufacturing Site	Siemens Healthcare GmbHHenkestrasse 127Erlangen, Germany 91052Registration Number: 3002808157

2. Contact Person

Kira Kuzmenchuk Regulatory Affairs Manager Siemens Medical Solutions USA, Inc. 40 Liberty Boulevard Mail Code: 65-3 Malvern, PA 19335 Phone: +1 (484) 901 - 9471 Email: kira.kuzmenchuk@siemens-healthineers.com

3. Device Name and Classification

Product Name:

AI-Rad Companion (Pulmonary)

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Trade Name:	AI-Rad Companion (Pulmonary)
Classification Name:	Computed Tomography X-Ray System
Classification Panel:	Radiology
CFR Section:	21 CFR §892.1750
Secondary CFR Section:	21 CFR §892.2050
Device Class:	Class II
Product Code:	JAK
Secondary Product Code:	QIH

4. Predicate Device

Product Name:	AI-Rad Companion (Pulmonary)
Propriety Trade Name:	AI-Rad Companion (Pulmonary)
510(k) Number:	K183271
Clearance Date:	July 26, 2019
Classification Name:	Computed Tomography X-Ray System
Classification Panel:	Radiology
CFR Section:	21 CFR §892.1750
Secondary CFR Section:	21 CFR §892.2050
Device Class:	Class II
Primary Product Code:	JAK
Secondary Product Code:	LLZ
Recall Information:	N/A

5. Indications for Use

It provides the following functionality:

Segmentation and measurements of complete lung and lung lobes ●
Identification of areas with lower Hounsfield values in comparison to a ● predefined threshold for complete lung and lung lobes
Providing an interface to external Medical Device syngo.CT Lung CAD
Segmentation and measurements of solid lung nodules
Dedication of found lung nodules to corresponding lung lobe
Correlation of segmented lung nodules of current scan with known priors and quantitative assessment of changes of the correlated data.
Identification of areas with elevated Hounsfield values, where areas with elevated versus high opacities are distinguished.

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Image /page/5/Picture/0 description: The image contains the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of orange dots arranged in a circular pattern.

The software has been validated for data from Siemens Healthineers (filtered backprojection and iterative reconstruction), GE Healthcare (filtered backprojection reconstruction), and Philips (filtered backprojection reconstruction).

Only DICOM images of adult patients are considered to be valid input.

6. Device Description

As an update to the previously cleared device, the following modifications have been made:

Modified Indications for Use Statement The indications for use statement was updated to include descriptive text for the lung lesion follow feature.
Updated Subject Device Claims List The claims list was updated to include claim pertaining to the lung lesion follow up feature.
Lung Lesion Follow-up Assessment of current and prior lesions This feature provides the possibility to compare currently segmented lung lesions with corresponding priors and changes to the correlated data are assessed quantitatively.
Pulmonary Density Assessment

. Bi-Directional Lesion Diameter
This feature provides an additional measurement derived from the existing segmentation contour of a lung lesion. The existing list of measurements is extended with the maximum orthogonal diameter in 2D (short axis diameter) which is orthogonal to the lesion's maximum 2D diameter (2D diameter, long axis diameter). This functionality is commercially available on the Siemens syngo.CT Extended Functionality (K203699).

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Image /page/6/Picture/0 description: The image shows the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of orange dots arranged in a pattern.

. Architecture Enhancement for on premise Edge deployment
- The system supports the existing cloud deployment as well as an on premise "edge" deployment. The system remains hosted in the teamplay digital health platform and remains driven by the AI-Rad Companion Engine. Now the edge deployment implies that the processing of clinical data and the generation of results can be performed onpremises within the customer network. The edge system is fully connected to the cloud for monitoring and maintenance of the system from remote.

7. Technological Characteristics

The comparison between the above referenced predicate device are listed at a high-level in the following table.

Feature	Subject DeviceAI-Rad Companion (Pulmonary)VA20	Predicate DeviceAI-Rad Companion (Pulmonary)(K183271)
Modality	CT	CT
Segmentationof lungs	Creation of a lung segmentation maskby combining the segmentation masksof 5 lung lobes.	Creation of a lung segmentation maskby combining the segmentation masksof 5 lung lobes.
Segmentationof lung lobes	Computation of segmentation masksof the five lung lobes (right upper(RUL), right middle (RML), rightlower (RLL), left upper (LUL) andleft lower (LLL) lobe) for a given CTdata set of the chest.	Computation of segmentation masksof the five lung lobes (right upper(RUL), right middle (RML), rightlower (RLL), left upper (LUL) andleft lower (LLL) lobe) for a given CTdata set of the chest.
Parenchymaevaluation	The parenchyma evaluation uses thelobe mask, counts all voxels per lobe,counts image voxels below -950 HU,and calculates the percentages ofthese voxels relative to the totalnumber of voxels. Additionally, itsums the individual lobe results andcalculates the percentage for thecomplete lung.	The parenchyma evaluation uses thelobe mask, counts all voxels per lobe,counts image voxels below -950 HU,and calculates the percentages ofthese voxels relative to the totalnumber of voxels. Additionally, itsums the individual lobe results andcalculates the percentage for thecomplete lung.
ParenchymaRanges	The percentages are likewisededicated to the 4 ranges. Name ofranges and their ranges areconfigurable by the user.	The percentages are likewisededicated to the 4 ranges. Name ofranges and their ranges areconfigurable by the user.
PulmonaryDensity	AI-based identification of areas withelevated Hounsfield values.Threshold-based identification ofhighest elevated Hounsfield values	N/A
	inside these elevated regions, by apredefined threshold of -200 HU
Visualizationofsegmentationandparenchymaresults	Color overlay of MPR and VRT withevaluation results	Color overlay of MPR and VRT withevaluation results
Interface toLungCAD	Interface to syngo.CT LungCAD	Interface to syngo.CT LungCAD
Lesionsegmentation	Segmentation of lung lesionsincluding the following data:• Relative change of maximum2D diameter [%]• relative change of maximumorthogonal 2D diameter [%]• relative change of mean 2Ddiameter [%],• relative change of maximum3D diameter [%]• Relative change of volume(volume doubling time [d],negative growth [%])	Segmentation of lung lesions with thefollowing data (not shown to theuser):• Relative change of maximum2D diameter [%]• relative change of maximumorthogonal 2D diameter [%]• relative change of mean 2Ddiameter [%],• relative change of maximum3D diameter [%]• Relative change of volume(volume doubling time [d],negative growth [%])
Visualizationof lesionsegmentationresults	Color overlay of MPR and VRT withevaluation	Color overlay of MPR and VRT withevaluation
Lesionfollow-up	Correlation of segmented lung lesionswith known priors using the data fromthe lesion segmentation.	N/A
Deployment	Cloud and Edge (on-premise)deployments	Cloud deployment

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Image /page/7/Picture/0 description: The image shows the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of orange dots arranged in a circular pattern.

Table 1: Technological Comparisons

8. Nonclinical Tests

Non-clinical tests were conducted to test the functionality of AI-Rad Companion (Pulmonary). Software validation and bench testing have been conducted to assess the performance claims as well as the claim of substantial equivalence to the predicate device.

AI-Rad Companion has been tested to meet the requirements of conformity to multiple industry standards. Non-clinical performance testing demonstrates that AI-Rad Companion (Pulmonary)

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Image /page/8/Picture/0 description: The image contains the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of orange dots.

complies with the FDA guidance document, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" (May 11, 2005) as well as with the following voluntary FDA recognized Consensus Standards listed in Table 1 below.

RecognitionNumber	ProductArea	Title of Standard	ReferenceNumber andDate	StandardsDevelopmentOrganization
5-114	General	Medical Devices – Applicationof usability engineering tomedical devices [includingCorrigendum 1 (2016)]	62366-1:2015-02	IEC
5-125	General	Medical Devices – applicationof risk management to medicaldevices	14971:2019	ISO
13-79	Software/Informatics	Medical device software –software life cycle processes[Including Amendment 1(2016)]	62304:2006/A1:2016	AAMIANSIIEC
12-300	Radiology	Digital Imaging andCommunications in Medicine(DICOM) Set	PS 3.1 – 3.20(2016)	NEMA
12-261	Radiology	Information Technology –Digital Compression and codingof continuous -tone still images:Requirements and Guidelines[including: TechnicalCorrigendum 1(2005)]	10918-11994-02-15	ISOIEC

Table 2: Voluntary Conformance Standards

Verification and Validation

Software documentation for a Moderate Level of Concern software, per FDA's Guidance Document "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" issued on May 11, 2005, is also included as part of this submission. Nonclinical tests were conducted on the subject device during product development.

Non-clinical tests (unit, integration and system) were conducted on AI-Rad Companion (Pulmonary) during product development. Additionally, the lesion follow-up feature was validated with a non-clinical bench test to assess the identification of lesion pairs. In an evaluation of 200 cases to identify lesion pairs, the algorithm had a sensitivity of 94.3% and an average PPV of 99.1% across all subgroups.

Siemens Healthineers adheres to the cybersecurity requirements as defined the FDA Guidance "Content of Premarket Submission for Management of Cybersecurity in Medical Devices:

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Image /page/9/Picture/0 description: The image contains the logo for Siemens Healthineers. The word "SIEMENS" is in teal, and the word "Healthineers" is in orange. To the right of the word "Healthineers" are several orange dots.

Guidance for Industry and Food and Drug Administration Staff" (October 18, 2018) by implementing a process of preventing unauthorized access, modifications, misuse or denial of use, or the unauthorized use of information that is stored, accessed, or transferred from a medical device to an external recipient.

9. Clinical Tests

No clinical tests were conducted to test the performance and functionality of the modifications introduced within AI-Rad Companion (Pulmonary). Verification and validation of the enhancements and improvements have been performed and these modifications have been validated for their intended use. The data from these activities were used to support the subject device and the substantial equivalence argument.

No animal testing has been performed on the subject device.

10. Safety and Effectiveness

The device labeling contains instructions for use and any necessary cautions and warnings to ensure safe and effective use of the device.

Risk management is ensured via ISO 14971:2019 compliance to identify and provide mitigation of potential hazards in a risk analysis early in the design phase and continuously throughout the development of the product. These risks are controlled via measures realized during software development, testing and product labeling.

Furthermore, the device is intended for healthcare professionals familiar with the post processing of magnetic resonance images.

11. Substantial Equivalence and Conclusion

AI-Rad Companion (Pulmonary) is substantially equivalent to the follow predicate device (Table 2):

Predicate Device	FDA ClearanceNumber	FDA ClearanceDate	Main Product Code
AI-Rad Companion(Pulmonary)	K183271	July 26, 2019	JAK

Table 2: Predicate device for AI-Rad Companion (Pulmonary)

AI-Rad Companion (Pulmonary) has the same intended use and technical characteristics compared to the predicate device. AI-Rad Companion (Pulmonary) [K183271], with respect to the software features, functionalities and core algorithms. The enhancements and improvements provided in AI-Rad Companion (Pulmonary) increase the clinical utility and reduce the complexity of the imaging workflow for the clinical user. The conclusions from all verification and validation data suggest that these enhancements are equivalent with respect to safety and effectiveness of the predicate device. These modifications do not change the intended use of the product. Siemens is of the opinion that AI-Rad Companion (Pulmonary) is substantially equivalent to the currently marketed predicate device.

Regulation Number and Section

§ 892.1750 Computed tomography x-ray system.

(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.