(211 days)
Not Found
Yes
The device explicitly states that it "includes locked machine learning algorithms" and uses a "Natural Language Processing (NLP) model," which are both forms of AI.
No.
The device is a treatment planning software that aids in configuring and reviewing radiotherapy plans, but it does not directly administer therapy or physically interact with the patient to provide a therapeutic effect.
No
The device is explicitly stated to be for configuring and reviewing radiotherapy treatment plans, assisting in the treatment planning process, and setting dosimetric goals. The text clearly states, "Diagnosis and treatment decisions occur prior to treatment planning and do not involve Oncospace." This indicates it does not perform a diagnostic function.
Yes
The device, "Oncospace," is clearly described as software designed to assist radiation oncologists and medical dosimetrists in radiotherapy treatment planning. The description explicitly states it is "software" and works "in conjunction with, and does not replace, a treatment planning system (TPS)." It does not mention any associated hardware components that are part of the device itself. While it interacts with external systems (TPS), the device being submitted for 510(k) is purely the software.
No.
This device is for radiotherapy treatment planning, which involves configuring and reviewing treatment plans and predicting dosimetric goals. It does not perform in vitro examination of specimens derived from the human body.
No
The letter does not explicitly state that the FDA has reviewed, approved, or cleared a Predetermined Change Control Plan (PCCP) for this specific device.
Intended Use / Indications for Use
Oncospace is used to configure and review radiotherapy treatment plans for a patient with malignant or benign disease in the head and neck, thoracic, abdominal, and pelvic regions. It allows for set up of radiotherapy treatment protocols, association of a potential treatment plan with the protocol(s), submission of a dose prescription and achievable dosimetric goals to a treatment planning system, and review of the treatment plan. It is intended for use by qualified, trained radiation therapy professionals (such as medical physicists, oncologists, and dosimetrists). This device is for prescription use by order of a physician.
Product codes (comma separated list FDA assigned to the subject device)
MUJ
Device Description
The Oncospace software supports radiation oncologists and medical dosimetrists during radiotherapy treatment planning. The software includes locked machine learning algorithms. During treatment planning, the Oncospace software works in conjunction with, and does not replace, a treatment planning system (TPS).
The Oncospace software is intended to augment the treatment planning process by:
• allowing the radiation oncologist to select and customize a treatment planning protocol that includes dose prescription (number of fractions, dose per fraction, dose normalization), a delivery method (beam type and geometry), and protocol-based dosimetric goals/objectives for treatment targets, and organs at risk (OAR);
• predicting dosimetric goals/objec tives for OARs based on patient-specific anatomical geometry;
• automating the initiation of plan optimization on a TPS by supplying the dose prescription, delivery method, protocol-based target objectives, and predicted OAR objectives;
• providing a user interface for plan evaluation against protocol-based and predicted goals.
Diagnosis and treatment decisions occur prior to treatment planning and do not involve Oncospace. Decisions involving Oncospace are restricted to setting of dosimetric goals for use during plan optimization and plan evaluation. Human judgement continues to be applied in accepting these goals and updating them as necessary during the iterative beam optimization process. Human judgement is also still applied as in standard practice during plan quality assessment; the protocol-based OAR goals are used as the primary means of plan assessment, with the role of the predicted goals being to provide additional information as to whether dose to an OAR may be able to be further lowered.
When Oncospace is used in conjunction with a TPS, the user retains full control of the TPS, including finalization of the treatment plan created for the patient. Oncospace also does not interface with the treatment machines. The risk to patient safety is lower than a TPS since it only informs the treatment plan, does not allow region of interest editing, does not make treatment decisions, and does not interface directly with the treatment machine or any record and verify system.
Oncospace's OAR dose prediction approach, and the use of predictions in end-to-end treatment planning workflow, has been tested for use with a variety of cancer treatment plans. These included a wide range of target and OAR geometries, prescriptions and boost strategies (sequential and simultaneous delivery). Validity has thus been demonstrated for the range of prediction model input features encountered in the test cases. This range is representative of the diversity of the same feature types (describing target-OAR proximity, target and OAR shapes, sizes, etc.) encountered across all cancer sites. Given that the same feature types will be used in OAR dose prediction models trained for all sites, the modeling approach validated here is not cancer site specific, but rather is designed to predict OAR DVHs based on impactful features common to all sites. The software is designed to be used in the context of all forms of intensity-modulated photon beam radiotherapy. The planning objectives themselves are intended to be TPS-independent: these are instead dependent on the degree of organ sparing possible given the beam modality and range of delivery techniques for plans in the database. To facilitate streamlined transmission of DICOM files and plan parameters Oncospace includes scripts using the treatment planning system's scripting language (for example, Pinnacle).
The Oncospace software includes an algorithm for transforming non-standardized OAR names used by treatment planners to standardized names defined by AAPM Task Group 263. This matching process primarily uses a table of synonyms that is updated as matches are made during use of the product, as well as a Natural Language Processing (NLP) model that attempts to match plan names not already in the synonym table. The NLP model selects the most likely match, which may be a correct match to a standard OAR name, an incorrect match, or no match (when the model considers this to be most likely, such as for names resembling a target). The user can also manually match names using a drop-down menu of all TG-263 OAR names. The user is instructed to check each automated match and make corrections using the drop-down menu as needed.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
Not Found
Anatomical Site
head and neck, thoracic, abdominal, and pelvic regions
Indicated Patient Age Range
There are no demographic, regional, or cultural limitations for patients. It is up to the user to determine if the system can be used for a patient.
Intended User / Care Setting
Qualified, trained radiation therapy professionals (such as medical physicists, oncologists, and dosimetrists). This device is for prescription use by order of a physician.
The system can be used in a hospital environment or in a doctor's office.
Description of the training set, sample size, data source, and annotation protocol
Head and Neck: 1145 treatment plans for patients who received radiation therapy for HNC at Johns Hopkins University between 2008-2019. Plans were required to exhibit 90% target coverage. 10% of the plans were single-target and 90% were SIB (19% 2-target, 51% 3-target, 20% 4-target). 96% of plans had a total prescribed dose >= 60 Gy, 4% had a total prescribed dose = 45 Gy, 18% had a total prescribed dose = 60 Gy, 2% had a total prescribed dose = 60 Gy.
Head and Neck Clinical Validation Dataset: 18 patients who received radiation therapy for HNC at JHU between 2021-2022. This included plans with 1-4 target dose levels, 10 to 48 fractions, in a variety of anatomical locations: lip, larynx, base of tongue, parotid, nasopharynx, scalp, neck, etc.
Thoracic Clinical Validation Dataset: 20 patients (14 lung and 6 esophagus) who received radiation therapy at JHU between 2021-2024. This included targets in multiple locations within the lungs and esophagus, including single-target, SIB, and multi-phase courses, treated with conventional- and hypo-fractionation, and SBRT.
Abdominal Clinical Validation Dataset: 17 patients (11 pancreas and 6 liver) who received radiation therapy for at JHU between 2021-2024. This included single-target and SIB courses, treated with conventional- and hypo-fractionation and SBRT.
Pelvis External Performance Test Dataset: 40 patients who received radiation therapy for prostate cancer at Institution_3. Plans were required to exhibit 94% target coverage. All plans had conventional fractionation.
Pelvis Clinical Validation Dataset: 17 patients (12 prostate and 5 gynecological) who received radiation therapy at JHU between 2021-2024. This included single-target and SIB courses, treated with conventional- and hypo-fractionation and SBRT.
NLP Model for OAR naming: Undergone 5-fold cross validation, and external validation, for each anatomic region. The external testing dataset contained a total of 221 structures with 145 unique original names.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Study Type: Verification and validation testing, including clinical performance testing and model performance testing.
Clinical Performance Testing:
- Purpose: To demonstrate that plan quality (mean OAR dose sparing) is non-inferior to plans created without Oncospace, and that target coverage is maintained.
- Sample Sizes: Determined to achieve 80% power at 0.05 significance level with a non-inferiority margin of 10 Gy.
- Head and Neck: 18 patients (JHU, 2021-2022 dataset). Previously validated.
- Abdominal: 17 patients
- Thoracic: 20 patients
- Pelvis (Gynecological): 5 patients. Prostate previously validated.
- Key Results:
- Mean dose was statistically significantly lower for 5 OARs for abdominal and 4 OARs for pelvis (gynecological).
- No statistically significant differences in mean dose for the remaining 11 OARs for thoracic, 3 OARs for abdominal, and 2 OARs for pelvis (gynecological).
- Non-inferiority of mean OAR dose demonstrated: 2.2 Gy for thoracic, 1 Gy for abdominal, and 1.9 Gy for pelvis (gynecological).
- No statistically significant difference in target coverage between clinical plans and plans created with Oncospace.
- No plan required more optimization cycles using Oncospace versus traditional clinical workflow.
Model Performance Testing:
- Purpose: Comparison of predicted dose values to ground truth values using DVH difference metrics with acceptance criteria.
- Key Results (Internal Model Performance): All models met acceptance criteria for internal model performance.
- Key Results (External Model Performance for H&N):
- Institution 2: Mean absolute error in OAR DVH dose values within 5% of prescription dose for 9/12 OARs, and not exceeding 9% for any OARs.
- Institution 3: Mean absolute error in OAR DVH dose values within 5% of prescription dose for 10/12 OARs, and not exceeding 8% for any OARs.
- Key Results (External Model Performance for Prostate):
- Institution 3: Mean absolute error in OAR DVH dose values within 5% of prescription dose for 4/6 OARs, 5.1% for one OAR, and 15.9% for one OAR.
- Small systematic differences between predicted and actual dose values are expected due to inter-institutional differences.
NLP Model Performance (for OAR name transformation):
- Study Type: 5-fold cross validation and external validation.
- Sample Size: External testing dataset: 221 structures with 145 unique original names.
- Key Results:
- During 5-fold cross-validation, all models achieved a validation macro-averaged F1 score above 0.92 and accuracy above 96% for classifying previously unseen terms.
- External testing: Model correctly matched 207/221 (94.1%) of all structure names, or 131/145 (91.0%) unique structure names.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Not Found (Accuracy, F1 score mentioned for NLP model)
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
Not Found
§ 892.5050 Medical charged-particle radiation therapy system.
(a)
Identification. A medical charged-particle radiation therapy system is a device that produces by acceleration high energy charged particles (e.g., electrons and protons) intended for use in radiation therapy. This generic type of device may include signal analysis and display equipment, patient and equipment supports, treatment planning computer programs, component parts, and accessories.(b)
Classification. Class II. When intended for use as a quality control system, the film dosimetry system (film scanning system) included as an accessory to the device described in paragraph (a) of this section, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.
U.S. Food & Drug Administration 510(k) Clearance Letter
Page 1
U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
Doc ID # 04017.07.05
April 11, 2025
Oncospace, Inc.
Sigrid Schoepel
Regulatory Affairs
1812 Ashland Ave., Suite 100K
Baltimore, Maryland 21205
Re: K242748
Trade/Device Name: Oncospace
Regulation Number: 21 CFR 892.5050
Regulation Name: Medical Charged-Particle Radiation Therapy System
Regulatory Class: Class II
Product Code: MUJ
Dated: March 12, 2025
Received: March 12, 2025
Dear Sigrid Schoepel:
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 (the 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 available 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.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device"
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K242748 - Sigrid Schoepel Page 2
(https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
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 (reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-combination-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 Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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-devices/medical-device-safety/medical-device-reporting-mdr-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/medical-devices/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-devices/device-advice-comprehensive-regulatory-
Page 3
K242748 - Sigrid Schoepel Page 3
assistance/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,
Lora D. Weidner, Ph.D.
Assistant Director
Radiation Therapy Team
DHT8C: Division of Radiological
Imaging and Radiation Therapy Devices
OHT8: Office of Radiological Health
Office of Product Evaluation and Quality
Center for Devices and Radiological Health
Enclosure
Page 4
DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration
Form Approved: OMB No. 0910-0120
Expiration Date: 07/31/2026
See PRA Statement below.
Indications for Use
Submission Number (if known)
K242748
Device Name
Oncospace
Indications for Use (Describe)
Oncospace is used to configure and review radiotherapy treatment plans for a patient with malignant or benign disease in the head and neck, thoracic, abdominal, and pelvic regions. It allows for set up of radiotherapy treatment protocols, association of a potential treatment plan with the protocol(s), submission of a dose prescription and achievable dosimetric goals to a treatment planning system, and review of the treatment plan. It is intended for use by qualified, trained radiation therapy professionals (such as medical physicists, oncologists, and dosimetrists). This device is for prescription use by order of a physician.
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)
CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
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"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
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K242748
Page 1 of 10
oncospace.com
info@oncospace.com
1812 Ashland Ave., Suite 100K
Baltimore, MD 21205 USA
510(k) Summary
I. SUBMITTER
Oncospace, Inc.
1812 Ashland Ave., Suite 100K
Baltimore, MD 21205 USA
Phone: 608-335-3176
Email: Sigrid.Schoepel@oncospace.com
Contact Person: Sigrid Schoepel
Date Prepared: 2025 March 7
II. DEVICE
Name of Device: Oncospace
Common or Usual Name: System, Planning, Radiation Therapy Treatment
Classification Name: Medical charged-particle radiation therapy system (21 CFR 892.5050)
Regulatory Class: II
Product Code: MUJ
III. PREDICATE DEVICE
Oncospace, K222803
This predicate device has not been the subject of a recall.
IV. DEVICE DESCRIPTION
The Oncospace software supports radiation oncologists and medical dosimetrists during radiotherapy treatment planning. The software includes locked machine learning algorithms. During treatment planning, the Oncospace software works in conjunction with, and does not replace, a treatment planning system (TPS).
The Oncospace software is intended to augment the treatment planning process by:
• allowing the radiation oncologist to select and customize a treatment planning protocol that includes dose prescription (number of fractions, dose per fraction, dose normalization), a delivery method (beam type and geometry), and protocol-based dosimetric goals/objectives for treatment targets, and organs at risk (OAR);
• predicting dosimetric goals/objectives for OARs based on patient-specific anatomical geometry;
Page 6
K242748
Page 2 of 10
oncospace.com
info@oncospace.com
1812 Ashland Ave., Suite 100K
Baltimore, MD 21205 USA
• automating the initiation of plan optimization on a TPS by supplying the dose prescription, delivery method, protocol-based target objectives, and predicted OAR objectives;
• providing a user interface for plan evaluation against protocol-based and predicted goals.
Diagnosis and treatment decisions occur prior to treatment planning and do not involve Oncospace. Decisions involving Oncospace are restricted to setting of dosimetric goals for use during plan optimization and plan evaluation. Human judgement continues to be applied in accepting these goals and updating them as necessary during the iterative beam optimization process. Human judgement is also still applied as in standard practice during plan quality assessment; the protocol-based OAR goals are used as the primary means of plan assessment, with the role of the predicted goals being to provide additional information as to whether dose to an OAR may be able to be further lowered.
When Oncospace is used in conjunction with a TPS, the user retains full control of the TPS, including finalization of the treatment plan created for the patient. Oncospace also does not interface with the treatment machines. The risk to patient safety is lower than a TPS since it only informs the treatment plan, does not allow region of interest editing, does not make treatment decisions, and does not interface directly with the treatment machine or any record and verify system.
Oncospace's OAR dose prediction approach, and the use of predictions in end-to-end treatment planning workflow, has been tested for use with a variety of cancer treatment plans. These included a wide range of target and OAR geometries, prescriptions and boost strategies (sequential and simultaneous delivery). Validity has thus been demonstrated for the range of prediction model input features encountered in the test cases. This range is representative of the diversity of the same feature types (describing target-OAR proximity, target and OAR shapes, sizes, etc.) encountered across all cancer sites. Given that the same feature types will be used in OAR dose prediction models trained for all sites, the modeling approach validated here is not cancer site specific, but rather is designed to predict OAR DVHs based on impactful features common to all sites. The software is designed to be used in the context of all forms of intensity-modulated photon beam radiotherapy. The planning objectives themselves are intended to be TPS-independent: these are instead dependent on the degree of organ sparing possible given the beam modality and range of delivery techniques for plans in the database. To facilitate streamlined transmission of DICOM files and plan parameters Oncospace includes scripts using the treatment planning system's scripting language (for example, Pinnacle).
The Oncospace software includes an algorithm for transforming non-standardized OAR names used by treatment planners to standardized names defined by AAPM Task Group 263. This matching process primarily uses a table of synonyms that is updated as matches are made during use of the product, as well as a Natural Language Processing (NLP) model that attempts to match plan names not already in the synonym table. The NLP model selects the most likely match, which may be a correct match to a standard OAR name, an incorrect match, or no match (when the model considers this to be most likely, such as for names resembling a target). The user can also manually match names using a drop-down menu of all TG-263 OAR names. The user is instructed to check each automated match and make corrections using the drop-down menu as needed.
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K242748
Page 3 of 10
oncospace.com
info@oncospace.com
1812 Ashland Ave., Suite 100K
Baltimore, MD 21205 USA
• automating the initiation of plan optimization on a TPS by supplying the dose prescription, delivery method, protocol-based target objectives, and predicted OAR objectives;
• providing a user interface for plan evaluation against protocol-based and predicted goals.
Diagnosis and treatment decisions occur prior to treatment planning and do not involve Oncospace. Decisions involving Oncospace are restricted to setting of dosimetric goals for use during plan optimization and plan evaluation. Human judgement continues to be applied in accepting these goals and updating them as necessary during the iterative beam optimization process. Human judgement is also still applied as in standard practice during plan quality assessment; the protocol-based OAR goals are used as the primary means of plan assessment, with the role of the predicted goals being to provide additional information as to whether dose to an OAR may be able to be further lowered.
When Oncospace is used in conjunction with a TPS, the user retains full control of the TPS, including finalization of the treatment plan created for the patient. Oncospace also does not interface with the treatment machines. The risk to patient safety is lower than a TPS since it only informs the treatment plan, does not allow region of interest editing, does not make treatment decisions, and does not interface directly with the treatment machine or any record and verify system.
Oncospace's OAR dose prediction approach, and the use of predictions in end-to-end treatment planning workflow, has been tested for use with a variety of cancer treatment plans. These included a wide range of target and OAR geometries, prescriptions and boost strategies (sequential and simultaneous delivery). Validity has thus been demonstrated for the range of prediction model input features encountered in the test cases. This range is representative of the diversity of the same feature types (describing target-OAR proximity, target and OAR shapes, sizes, etc.) encountered across all cancer sites. Given that the same feature types will be used in OAR dose prediction models trained for all sites, the modeling approach validated here is not cancer site specific, but rather is designed to predict OAR DVHs based on impactful features common to all sites. The software is designed to be used in the context of all forms of intensity-modulated photon beam radiotherapy. The planning objectives themselves are intended to be TPS-independent: these are instead dependent on the degree of organ sparing possible given the beam modality and range of delivery techniques for plans in the database. To facilitate streamlined transmission of DICOM files and plan parameters Oncospace includes scripts using the treatment planning system's scripting language (for example, Pinnacle).
The Oncospace software includes an algorithm for transforming non-standardized OAR names used by treatment planners to standardized names defined by AAPM Task Group 263. This matching process primarily uses a table of synonyms that is updated as matches are made during use of the product, as well as a Natural Language Processing (NLP) model that attempts to match plan names not already in the synonym table. The NLP model selects the most likely match, which may be a correct match to a standard OAR name, an incorrect match, or no match (when the model considers this to be most likely, such as for names resembling a target). The user can also manually match names using a drop-down menu of all TG-263 OAR names. The user is instructed to check each automated match and make corrections using the drop-down menu as needed.
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K242748
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V. INDICATIONS FOR USE
Oncospace is used to configure and review radiotherapy treatment plans for a patient with malignant or benign disease in the head and neck, thoracic, abdominal, and pelvic regions. It allows for set up of radiotherapy treatment protocols, association of a potential treatment plan with the protocol(s), submission of a dose prescription and achievable dosimetric goals to a treatment planning system, and review of the treatment plan. It is intended for use by qualified, trained radiation therapy professionals (such as medical physicists, oncologists, and dosimetrists). This device is for prescription use by order of a physician.
VI. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH THE PREDICATE DEVICE
The Oncospace subject device is a software-only medical device that performs the same functions as the Oncospace predicate device. The following differences exist between the subject and predicate devices:
• The prostate, head, and neck models have been updated to improve performance.
• The thoracic, abdominal, and gynecological regions have been added using the same machine learning methods as in the predicate device.
Note: The subject device algorithms, and any future algorithm updates, are locked prior to clinical use.
| Element | Subject | Predicate | Conclusion |
|---|---|---|---|
| Device Name | Oncospace | Oncospace | Identical |
| 510(k) Owner | Oncospace, Inc. | Oncospace, Inc. | |
| 510(k) Number | -- | K222803 | |
| Product Code | MUJ | MUJ | Identical |
| Product Name | System, Planning, Radiation Therapy Treatment | System, Planning, Radiation Therapy Treatment | Identical |
| Intended Use | Oncospace is used to configure and review radiotherapy treatment plans for a patient with malignant or benign disease in the head and neck, thoracic, abdominal, and pelvic regions. It allows for set up of radiotherapy treatment protocols, association of a potential treatment plan with the protocol(s), submission of a dose prescription and achievable dosimetric goals to a treatment planning system, and review of the treatment plan. It is intended for use by qualified, trained radiation therapy professionals (such as medical physicists, oncologists, and dosimetrists). | Oncospace is used to configure and review radiotherapy treatment plans for a patient with malignant or benign disease in the prostate, head, and neck regions. It allows for set up of radiotherapy treatment protocols, association of a potential treatment plan with the protocol(s), submission of a dose prescription and achievable dosimetric goals to a treatment planning system, and review of the treatment plan. It is intended for use by qualified, trained radiation therapy professionals (such as medical physicists, oncologists, and dosimetrists). This device is for prescription use by order of a physician. | Substantially Equivalent Added thoracic and abdominal regions, added gynecological sites to expand the prostate reference to the pelvic region. |
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| Element | Subject | Predicate | Conclusion |
|---|---|---|---|
| This device is for prescription use by order of a physician. | |||
| Operating System | Windows/Web-browser | Windows/Web-browser | Identical |
| Platform | Client-Server (Clinic-provided client machines, cloud Windows servers controlled by Oncospace) | Client-Server (Clinic-provided client machines, cloud Windows servers controlled by Oncospace) | Identical |
| DICOM-RT Compliant | Yes | Yes | Identical |
| Full Treatment Planning System | No | No | Identical |
| Connected to or Controlling of Radiation Delivery Devices | No | No | Identical |
| Typical Users | Medical professionals, including but not limited to, radiation oncologists, medical physicists or physicians. | Medical professionals, including but not limited to, radiation oncologists, medical physicists or physicians. | Identical |
| Patient Population | There are no demographic, regional, or cultural limitations for patients. It is up to the user to determine if the system can be used for a patient. | There are no demographic, regional, or cultural limitations for patients. It is up to the user to determine if the system can be used for a patient. | Identical |
| Body Regions | Head and neck Thoracic Abdominal Pelvic The thoracic, abdominal, and gynecological regions have been added using the same machine learning methods as in the predicate device. | Head and neck Prostate | New: Gynecologic, thoracic, and abdominal organs Identical: Head and neck, prostate |
| Environment | The system can be used in a hospital environment or in a doctor's office. | The system can be used in a hospital environment or in a doctor's office. | Identical |
| JPEG image support | Yes | Yes | Identical |
| Import Treatment Plans | Yes. Import existing plans from third-party systems to compare dose objectives against templates. | Yes. Import existing plans from third-party systems to compare dose objectives against templates. | Identical |
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| Element | Subject | Predicate | Conclusion |
|---|---|---|---|
| "Template" Treatment Plans | Yes. Factory-default plans with dose goals exist and users can configure a dose template. | Yes. Factory-default plans with dose goals exist and users can configure a dose template. | Identical |
| Automatic Initial Tumor Selection | Yes. Regions of interest are matched as the study is opened in the device. Users can adjust or match to more available regions of interest. | Yes. Regions of interest are matched as the study is opened in the device. Users can adjust or match to more available regions of interest. | Identical |
| Dose Objective Comparison | Yes. Comparisons can be done between more than one selected treatment plan. Dose is based on calculated dose and curated, gold-standard treatment plans. | Yes. Comparisons can be done between more than one selected treatment plan. Dose is based on calculated dose and curated, gold-standard treatment plans. | Identical |
| Image Viewer Capabilities | Yes. Display, pan, zoom, scroll, windowing, viewport layout. | Yes. Display, pan, zoom, scroll, windowing, viewport layout. | Identical |
| Calculate and Display Isodose Lines | Yes | Yes | Identical |
| Calculate and Display Dose Volume Histograms | Yes | Yes | Identical |
| Compare Dose from Multiple Plans | Yes | Yes | Identical |
| Dose Summation/ Treatment-Over-Time Data | Yes | Yes | Identical |
| Plan Review | Yes. Contains features for review of isodose lines, review of DVHs, dose comparison and dose summation. | Yes. Contains features for review of isodose lines, review of DVHs, dose comparison and dose summation. | Identical |
| Export Plan Information | Yes. Can export the selected plan for review and setup by a dosimetrist. Oncospace does not export a final plan, it will not export to a record-and-verify system. | Yes. Can export the selected plan for review and setup by a dosimetrist. Oncospace does not export a final plan, it will not export to a record-and-verify system. | Identical |
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VII. PERFORMANCE DATA
The following verification and validation testing results (performance data) support the substantial equivalence determination. Since this is a software-only medical device that does not control other devices the performance data does not include biocompatibility, electrical safety, electromagnetic compatibility, mechanical, acoustic, or animal testing.
The verification tests met all system requirements and acceptance criteria which address clinical, standard user interface, and cybersecurity requirements for the Oncospace device.
The validation testing for dose prediction was performed using retrospective clinical data. The Oncospace device's purpose is to reduce the effort needed to achieve a clinically viable and deliverable radiation treatment plan by supplying a treatment planning system with patient-specific plan optimization objectives derived from Oncospace dose predictions. Thus a trial of clinical performance was designed to demonstrate that plan quality, as represented by mean organ-at-risk (OAR) dose sparing, is non-inferior to that of plans created without use of Oncospace.. A comparison of target coverage was also made, because a comparison of OAR sparing is only valid if target coverage is maintained. Reduction in effort for the plans created with use of Oncospace was ensured by the planner using only the OAR optimization objective dose values supplied by Oncospace (rather than being allowed to adjust them via the usual trial-and-error process). Sample sizes were determined by estimating variance in mean OAR dose so that the trial would have 80% power at a significance level of 0.05 and a non-inferiority margin of 10 Gy. The head and neck and prostate models have previously undergone clinical performance testing, so for these only model performance testing (comparison of predicted dose values to ground truth values) was repeated here. Please note the distinction here between clinical performance testing (maintaining plan quality when Oncospace-derived objectives are used) and model performance testing (model accuracy).
Table 1 summarizes the characteristics of the datasets used for model development and internal testing, external performance testing, and clinical validation. Some datasets were fully decoupled from the medical record such that technique information could not be linked.
| Anatomical Location | Development (Training/Tuning) and Internal Performance Testing Dataset (randomly split 80/20) | External Performance Test Dataset(s) | Clinical Validation Dataset |
|---|---|---|---|
| Head and Neck | 1145 treatment plans for patients who received radiation therapy for HNC at Johns Hopkins University between 2008-2019. Plans were required to exhibit 90% target coverage. 10% of the plans were single-target and 90% were SIB (19% 2-target, 51% 3-target, 20% 4-target). 96% of plans had a total prescribed dose >= 60 Gy, 4% had a total prescribed dose = 60 Gy, 2% had a total prescribed dose = 60 Gy. | ||
| Thoracic | 1623 treatment plans (1437 lung and 186 esophagus) for patients who received radiation therapy for thoracic cancer at Johns Hopkins University between 2008-2019. Plans were required to exhibit 92% target coverage. 82% of plans had a total prescribed dose >= 45 Gy, 18% had a total prescribed dose |