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Ricoh 3D Anatomic Models are intended as physical replicas of patient anatomy to be used for diagnostic purposes in the fields of craniomaxillofacial, orthopedic, cardiovascular, neurological, gastrointestinal, genitourinary, and breast applications. The Anatomic Models are based on DICOM imaging information from a medical scanner and output files from FDA cleared software intended for the creation and output of digital files suitable for the fabrication of physical replicas. The models should be used in conjunction with other diagnostic tools and expert clinical judgement.

The subject device, each "Ricoh 3D Anatomic Model," is a patient-specific physical replica of an anatomic structure or site, produced via additive manufacturing from a user generated 3D print file. The input 3D print file is created from medical images in DICOM format that have been seqmented to a specific reqion of interest within an FDA cleared application, IBM iConnect Access (K203104). The input 3D print file is then transferred to Ricoh for production and delivery of the physical replica.

The provided text
describes the acceptance criteria and the study that proves the device meets the
acceptance criteria in the context of a 510(k) premarket notification for a 3D Anatomic
Model.

Here's the breakdown of the information requested based on the
provided text:

1. Table of Acceptance Criteria and Reported Device

Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: The document does not explicitly state the specific
  sample size used for the geometric accuracy testing (e.g., number of models
  tested). It refers to "testing" and "assessment" but not quantitative sample
  sizes.
• Data Provenance: The document does not specify the country of origin of the data
  or whether the study was retrospective or prospective. It describes "bench testing"
  and "simulated distribution and handling testing," which are laboratory/controlled
  tests rather than patient-data-driven clinical studies in the typical sense for an
  AI/imaging device.

3. Number of Experts Used to Establish Ground Truth and

Qualifications

Not applicable. For this device (3D Anatomic Model), the "ground
truth" for geometric accuracy is the input digital 3D file (the design spec).
The product is a physical replica, and its accuracy is measured against the
digital file itself, not against a human expert's interpretation of a medical
image or a medical diagnosis. The document mentions "clinical user" approval of
the model, but this is part of the workflow and quality process, not the
ground truth establishment for performance testing.

4. Adjudication Method for the Test Set

Not applicable. As noted above, the primary performance test
(geometric accuracy) compares the physical model directly to the digital input
file. There is no human interpretation or subjective assessment that would
require an adjudication method.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness

Study was Done

No. The document makes no mention of an MRMC study. This type of
study is typically performed for AI-powered diagnostic software to assess its
impact on human reader performance. The device here is a physical replica
generated from an existing cleared software's output, not a diagnostic AI
algorithm.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop

Performance) Study was Done

Yes, in a way. The "Validation Testing" described, particularly the
geometric accuracy assessment, represents a standalone performance test of the
device's manufacturing capability to produce accurate physical models based on
digital input. It assesses the output of the manufacturing process (the
physical model) against its input (the digital file) without human
intervention being a variable in the measurement of geometric accuracy itself.

7. The Type of Ground Truth Used

The ground truth for the device's performance (geometric accuracy)
is the input digital 3D file from which the physical replica is printed.
The physical model is compared directly to this digital file using measurement
techniques to determine deviation.

For the purpose of the device's function (being a physical replica
for diagnostic purposes), the underlying "ground truth" of the patient's
anatomy would stem from the original DICOM imaging information, which is then
segmented by FDA cleared software to create the 3D print file. However, the
performance assessment of this specific device (the physical model itself)
uses the digital file as its reference.

8. The Sample Size for the Training Set

Not applicable. This device is a manufactured physical product (a 3D
print) based on a digital file, not an AI/machine learning algorithm that
requires a training set. The performance data relates to the manufacturing
accuracy and physical integrity of the printed models, not to an algorithm's
ability to learn from data.

9. How the Ground Truth for the Training Set Was Established

Not applicable, as there is no training set for this device.

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Ricoh 3D Anatomic Models are intended as physical replicas of patient anatomy to be used for diagnostic purposes in the fields of craniomaxillofacial and orthopedic applications. The Anatomic Models are based on DICOM imaging information from a medical scanner and output files from FDA cleared software intended for the creation and output of digital files suitable for the fabrication of physical replicas. The models should be used in conjunction with other diagnostic tools and expert clinical judgement.

The subject device, each "Ricoh 3D Anatomic Model," is a patient-specific physical replica of an anatomic structure or site, produced via additive manufacturing from a user generated 3D print file. The input 3D print file is created from medical images in DICOM format that have been seqmented to a specific reqion of interest within an FDA cleared application, IBM iConnect Access (K203104). The input 3D print file is then transferred to Ricoh for production and delivery of the physical replica.

The provided text describes a 510(k) summary for the Ricoh 3D Anatomic Models device. The device is a patient-specific physical replica of an anatomic structure, produced via additive manufacturing from a user-generated 3D print file. It is intended for diagnostic purposes in craniomaxillofacial and orthopedic applications.

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

Acceptance Criteria and Reported Device Performance

The core performance validation for the Ricoh 3D Anatomic Models focuses on the geometric accuracy of the physical replicas compared to the input digital 3D file.

Study Details

The provided text offers limited, high-level details regarding the study methodologies.

1. Sample Size Used for the Test Set and Data Provenance:

• The text states "geometric accuracy of printed orthopedic and craniomaxillofacial physical models was assessed via bench testing." It does not specify the exact sample size (i.e., number of models, number of measurements per model) used for this test set.
• The data provenance is implied to be prospective bench testing performed by Ricoh, rather than based on patient data from specific countries. The input digital 3D files are derived from patient DICOM imaging information, but the "test set" for accuracy assessment refers to the physical models themselves.

2. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

• The text does not specify the number of experts or their qualifications involved in establishing the ground truth measurements for the geometric accuracy testing of the physical models. The "ground truth" here is the original digital 3D file, and the comparison is a technical measurement, not a subjective expert assessment of the model's diagnostic utility directly.
• The indication for use states that "The models should be used in conjunction with other diagnostic tools and expert clinical judgement," implying that clinical experts would ultimately use and evaluate the models in practice, but this is not part of the described technical validation study.

3. Adjudication Method for the Test Set:

• The text does not describe an adjudication method as it relates to human review of the test set, as the primary assessment is a quantitative comparison of the physical model to the digital file. This is a technical measurement validation rather than an image reading study.

4. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done:

• No, an MRMC comparative effectiveness study was not done or described. This type of study typically involves human readers (e.g., radiologists) evaluating medical images or outputs with and without AI assistance to measure diagnostic performance. The Ricoh 3D Anatomic Models are physical replicas, and the validation described focuses on their physical accuracy, not on human diagnostic performance using the models in a comparative MRMC setup.

5. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done:

• Yes, a standalone performance assessment was done in the sense that the geometric accuracy of the fabricated physical models was assessed against the digital input file. This is a direct measurement of the device's output (the physical model) against its intended technical specification (replicating the digital design), without human interpretation of diagnostic value as the primary endpoint of this specific performance test.

6. The Type of Ground Truth Used:

• The ground truth for the geometric accuracy testing was the input digital 3D file. The physical model was compared against this digital representation.

7. The Sample Size for the Training Set:

• The Ricoh 3D Anatomic Models device does not appear to be an AI/ML algorithm that requires a "training set" in the conventional sense. It is a manufacturing process (additive manufacturing) that takes a digital file and produces a physical object. Therefore, a training set size is not applicable to the description of this device's validation. The device's performance relies on the precision of the manufacturing process and materials.

8. How the Ground Truth for the Training Set was Established:

• As noted above, this question is not applicable as the device description does not involve an AI/ML training set. The "ground truth" for the overall process originates from patient DICOM images that are segmented using FDA-cleared software (e.g., IBM iConnect Access), which then generates the 3D print file. The validation described here is of the physical printing process itself, not the image segmentation or diagnosis preceding the 3D print file generation.

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