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510(k) Data Aggregation
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(174 days)
MIM software is used by trained medical professionals as a tool to aid in evaluation and information management of digital medical images. The medical image modalities include, but are not limited to, CT, MR, CR, DX, MG, US, SPECT, PET, and XA as supported by ACR/NEMA DICOM 3.0. MIM assists in the following indications:
- Receive, transmit, store, retrieve, display, print, and process medical images and DICOM objects.
- Create, display, and print reports from medical images.
- Registration, fusion display, and review of medical images for diagnosis, staging, treatment planning, monitoring treatment response, and treatment evaluation.
- Evaluation of cardiac left ventricular function and perfusion, including left ventricular end-diastolic volume, end-systolic volume, and ejection fraction.
- Localization and definition of objects such as tumors and normal tissues in medical images.
- Creation, transformation, and modification of contours for applications including, but not limited to, quantitative analysis, aiding adaptive therapy, transferring contours to radiation therapy treatment planning systems, and archiving contours for patient follow-up and management.
- Quantitative and statistical analysis of PET/SPECT brain scans by comparing to other registered PET/SPECT brain scans.
- Planning and evaluation of permanent implant brachytherapy procedures (not including radioactive microspheres).
- Calculating absorbed radiation dose as a result of administering a radionuclide.
- Assist with the planning and evaluation of ablation procedures by providing visualization and analysis, including energy zone visualization through the placement of virtual ablation devices validated for inclusion in MIM-Ablation. The software is not intended to predict specific ablation zone volumes or predict ablation success.
When using the device clinically, within the United States, the user should only use FDA approved radiopharmaceuticals. If used with unapproved ones, this device should only be used for research purposes.
Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Images that are printed to film must be printed using an FDA-approved printer for the diagnosis of digital mammography images. Mammographic images must be viewed on a display system that has been cleared by the FDA for the diagnosis of digital mammography images. The software is not to be used for mammography CAD.
When used for diagnostic purposes, the mobile thin client is not intended to replace a full workstation and should only be used when there is no access to a workstation.
The subject MIM – LesionID Pro device is a standalone software application that extends the functionality of the MIM software device. It is a modification to the predicate MIM software application (K243012) for incorporating updates to the LesionID Pro option that is commercially available in the currently distributed version of MIM software.
LesionID Pro assists users with the evaluation of PSMA PET/CT and SPECT/CT studies by automating hotspot segmentation and physiological uptake removal, to help reduce manual processing and streamline generation of Total Tumor Burden (TTB) statistics. It is provided via MIM Workflows that allow automation using scripts constructed of MIM software modular functions and commands.
LesionID Pro does not determine final hotspots segmentation for TTB generation, and requires users to review, edit, and confirm the segmentation before generating TTB statistics. The modifications made to LesionID Pro optimize the identification and removal of physiological uptake, automates the processing for a more streamlines workflow, and introduced enhancements related to user interface and experience.
Here's a summary of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) clearance letter for MIM - LesionID Pro:
The clearance letter primarily focuses on the device's substantial equivalence to predicate devices and does not detail specific quantitative acceptance criteria or a comprehensive study plan with statistical results in the provided sections. Instead, it describes general performance testing and qualitative clinical reader evaluation.
Acceptance Criteria and Reported Device Performance
The document describes the acceptance criteria as ensuring that the "initial TTB segmentation generated by LesionID Pro was of acceptable quality for clinical use in the context of PSMA PET and SPECT TTB segmentation and evaluation" and that it "reduce[s] user need for manual editing."
The reported device performance indicates that LesionID Pro "successfully completed performance testing on a clinically representative dataset to verify that the generated segmentations are adequate for use as an initial segmentation, helping to reduce user need for manual editing."
Given the information, a table of specific quantitative acceptance criteria and corresponding reported device performance values is not available in the provided text. The evaluation appears to be qualitative and aimed at verifying adequacy and reduction in manual editing.
| Acceptance Criteria (Inferred from study description) | Reported Device Performance |
|---|---|
| Initial TTB segmentation adequate for clinical use in PSMA PET and SPECT | Successfully completed performance testing verifying adequacy |
| Initial TTB segmentation reduces user need for manual editing | Successfully completed performance testing verifying reduced manual editing needs |
| Segmentations adequate for use as an initial segmentation | Segmentations verified as adequate for initial use |
| Generated segmentations aligning with physician-approved segmentation Agreement Standard | Test evaluated initial TTB segmentation against a pre-defined segmentation Agreement Standard based on physician-approved segmentation (Result: "successfully completed") |
Study Details
Based on the provided text, the study focuses on performance testing and clinical reader evaluation of LesionID Pro.
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1. Sample sized used for the test set and the data provenance:
- Sample Size: Not explicitly stated as a number. The text mentions "a clinically representative dataset" and "clinically representative PSMA PET/CT and SPECT/CT patient clinical studies."
- Data Provenance: Not explicitly stated (e.g., country of origin). The studies spanned "factors various relevant to the evaluation of LesionID Pro's segmentation performance (e.g., radiotracers, disease burden, imaging systems)." The readers were "United States board certified NM physicians," suggesting the clinical context is within the US. The information does not specify if the data was retrospective or prospective.
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2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Number of Experts: Not explicitly stated as a number. The "pre-defined segmentation Agreement Standard based on physician approved segmentation" implies expert consensus or approval was used to define the ground truth for comparison.
- Qualifications of Experts (for ground truth): The "physician approved segmentation" implies qualified medical professionals, but their specific qualifications (e.g., years of experience) are not detailed here.
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3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- The "pre-defined segmentation Agreement Standard based on physician approved segmentation" suggests a form of consensus or expert-defined standard, but the specific adjudication method (e.g., "2+1") is not described.
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4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
- MRMC Study: A "qualitative clinical reader evaluation" was performed where readers assessed the "initial segmentation generated by LesionID Pro." This indicates a reader study, but it's not explicitly framed as an MRMC comparative effectiveness study measuring reader improvement with AI vs. without AI assistance. It seems to be an evaluation of the AI's output itself for clinical acceptability rather than a comparison of human performance with and without the AI.
- Effect Size: No effect size or quantitative measure of human reader improvement with AI assistance is reported.
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5. If a standalone (i.e., algorithm only without human-in-the loop performance) was done:
- Yes, the "performance testing on a clinically representative dataset" compared the initial TTB segmentation generated by LesionID Pro (presumably standalone algorithm output) against a "pre-defined segmentation Agreement Standard." The qualitative clinical reader evaluation was of the initial segmentation generated by LesionID Pro, further supporting standalone evaluation. The device also "requires users to review, edit, and confirm the segmentation before generating TTB statistics," indicating the AI provides an initial segmentation, which is a standalone function.
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6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- The ground truth for comparison was a "pre-defined segmentation Agreement Standard based on physician approved segmentation." This points towards expert-defined or expert-approved segmentation.
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7. The sample size for the training set:
- Not specified. The document only mentions testing and verification.
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8. How the ground truth for the training set was established:
- Not specified. The document only discusses the ground truth for the test set.
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(156 days)
Archy Dental Imaging is an internet-based, image management software (PACS) that enables dental offices to keep records of hard and soft tissue charts in the form of digital images. The system uses a Web-based interface and includes acquisition, editing, and storage of digital images. Images and data can be stored, communicated, processed, and displayed within the system or across computer networks at distributed locations. Images can be acquired from standard dental imaging devices or can be uploaded directly from the user's computer. Images can be edited (e.g., zoomed, contrast adjusted, rotated, etc.), as well as exported. The system is designed to provide images for diagnostic use.
Archy Dental Imaging is a cloud-based dental imaging software that allows access to diagnostic radiological and photo images on any PC with an active internet connection via modern web browser. Archy Dental Imaging contains all key features present in traditional client-server based dental imaging software.
Archy Dental Imaging is a Class II dental imaging software that includes the ability to acquire, view, annotate, and organize dental radiographs and color images. Images stored using Archy Dental Imaging are saved using lossless compression and can be exported as DICOM or PNG files. The original images are treated as immutable by the rest of the system.
Archy Dental Imaging is a software-only dental image device which allows the user to acquire images using standard dental imaging devices, such as intraoral X-ray sensors, intraoral cameras, and scanners. Archy Dental Imaging is imaging software designed for use in dentistry. The main Archy Dental Imaging software functionality includes image acquisition, organization, and annotation. Archy Dental Imaging is used by dental professionals for the visualization of patient images retrieved from a dental imaging device or scanner, for assisting in case diagnosis, review, and treatment planning. Dentists and other qualified individuals can display and review images, apply annotations, and manipulate images. Archy Dental Imaging is the imaging component of Archy, a full-featured dental practice management system that handles scheduling, charting, and other practice business concerns. The software operates within a web browser upon standard consumer PC hardware and displays images on the PC's connected display/monitor. The subject device is the Archy Dental Imaging software; the computer or the monitor are not part of the submission.
Archy Dental Imaging neither contacts the patient nor controls any life sustaining devices. Diagnosis is not performed by this software but by doctors and other qualified individuals. A physician, providing ample opportunity for competent human intervention, interpreting images and information being displayed and printed.
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(23 days)
syngo.MR Applications is a syngo based post-acquisition image processing software for viewing, manipulating, evaluating, and analyzing MR, MR-PET, CT, PET, CT-PET images and MR spectra.
syngo.MR Applications is a software only Medical Device consisting post-processing applications/workflows used for viewing and evaluating the designated images provided by a MR diagnostic device. The post-processing applications/workflows are integrated with the hosting application syngo.via, that enables structured evaluation of the corresponding images
The provided FDA 510(k) clearance letter and summary for syngo.MR Applications (VB80) indicate that no clinical studies or bench testing were performed to establish new performance criteria or demonstrate meeting previously established acceptance criteria. The submission focuses on software changes and enhancements from a predicate device (syngo.MR Applications VB40).
Therefore, based solely on the provided document, I cannot create the requested tables and information because the document explicitly states:
- "No clinical studies were carried out for the product, all performance testing was conducted in a non-clinical fashion as part of verification and validation activities of the medical device."
- "No bench testing was required to be carried out for the product."
The document details the following regarding performance and acceptance:
- Non-clinical Performance Testing: "Non-clinical tests were conducted for the subject device during product development. The modifications described in this Premarket Notification were supported with verification and validation testing."
- Software Verification and Validation: "The performance data demonstrates continued conformance with special controls for medical devices containing software. Non-clinical tests were conducted on the device Syngo.MR Applications during product development... The testing results support that all the software specifications have met the acceptance criteria. Testing for verification and validation for the device was found acceptable to support the claims of substantial equivalence."
- Conclusion: "The predicate device was cleared based on non-clinical supportive information. The comparison of technological characteristics, device hazards, non-clinical performance data, and software validation data demonstrates that the subject device performs comparably to and is as safe and effective as the predicate device that is currently marketed for the same intended use."
This implies that the acceptance criteria are related to the functional specifications and performance of the software, as demonstrated by internal verification and validation activities, rather than a clinical performance study with specific quantitative metrics. The new component, "MR Prostate AI," is noted to be integrated without modification and had its own prior 510(k) clearance (K241770), suggesting its performance was established in that separate submission.
Without access to the actual verification and validation reports mentioned in the document, it's impossible to list precise acceptance criteria or detailed study results. The provided text only states that "all the software specifications have met the acceptance criteria."
Therefore, I can only provide an explanation of why the requested details cannot be extracted from this document:
Explanation Regarding Acceptance Criteria and Study Data:
The provided FDA 510(k) clearance letter and summary for syngo.MR Applications (VB80) explicitly state that no clinical studies or bench testing were performed for this submission. The device (syngo.MR Applications VB80) is presented as a new version of a predicate device (syngo.MR Applications VB40) with added features and enhancements, notably the integration of an existing AI algorithm, "Prostate MR AI VA10A (K241770)," which was cleared under a separate 510(k).
The basis for clearance is "non-clinical performance data" and "software validation data" demonstrating that the subject device performs comparably to and is as safe and effective as the predicate device. The document mentions that "all the software specifications have met the acceptance criteria" as part of the verification and validation (V&V) activities. However, the specific quantitative acceptance criteria, detailed performance metrics, sample sizes, ground truth establishment, or expert involvement for these V&V activities are not included in this public summary.
Therefore, the requested information cannot be precisely extracted from the provided text.
Summary of Information Available (and Not Available) from the Document:
| Information Requested | Status (Based on provided document) |
|---|---|
| 1. Table of acceptance criteria and reported performance | Not provided in the document. The document states: "The testing results support that all the software specifications have met the acceptance criteria." However, it does not specify what those acceptance criteria are or report detailed performance metrics against them. These would typically be found in the detailed V&V reports, which are not part of this summary. |
| 2. Sample size and data provenance for test set | Not provided. The document indicates "non-clinical tests were conducted as part of verification and validation activities." The sample sizes for these internal tests, the nature of the data, and its provenance (e.g., country, retrospective/prospective) are not detailed. It is implied that the data is not patient-specific clinical test data. |
| 3. Number of experts and qualifications for ground truth | Not applicable/Not provided. Since no clinical studies or specific performance evaluations against an external ground truth are described in this document, there's no mention of experts establishing ground truth for a test set. The validation appears to be against software specifications. If the "MR Prostate AI" component had such a study, those details would be in its individual 510(k) (K241770), not this submission. |
| 4. Adjudication method for test set | Not applicable/Not provided. As with the ground truth establishment, no adjudication method is mentioned because no external test set requiring such expert consensus is described within this 510(k) summary. |
| 5. MRMC comparative effectiveness study and effect size | Not performed for this submission. The document explicitly states "No clinical studies were carried out for the product." Therefore, no MRMC study or AI-assisted improvement effect size is reported here. |
| 6. Standalone (algorithm only) performance study | Partially addressed for a component. While this submission doesn't detail such a study, it notes that the "MR Prostate AI" algorithm is integrated without modification and "is classified under a different regulation in its 510(K) and this is out-of-scope from the current submission." This implies that a standalone performance study was done for the Prostate MR AI algorithm under its own 510(k) (K241770), but those details are not within this document. For the overall syngo.MR Applications (VB80) product, no standalone study is described. |
| 7. Type of ground truth used | Not provided for the overall device's V&V. The V&V activities are stated to have met "software specifications," which suggests an internal, design-based ground truth rather than clinical ground truth like pathology or outcomes data. For the integrated "MR Prostate AI" algorithm, clinical ground truth would have been established for its separate 510(k) submission. |
| 8. Sample size for the training set | Not applicable/Not provided for this submission. The document describes internal non-clinical V&V for the syngo.MR Applications software. It does not refer to a machine learning model's training set within this context. The "Prostate MR AI" algorithm, being independently cleared, would have its training set details in its specific 510(k) dossier (K241770), not here. |
| 9. How the ground truth for the training set was established | Not applicable/Not provided for this submission. As above, this document does not discuss a training set or its ground truth establishment for syngo.MR Applications. This information would pertain to the Prostate MR AI algorithm and be found in its own 510(k). |
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(181 days)
VXvue is intended to acquire Digital images from X-ray Detectors, process the images to facilitate diagnosis and to display, and transfer the resulting images to other devices for diagnostic purpose.
VXvue is indicated for use in general radiographic images of human anatomy. And it is not for fluoroscopic, angiographic, and mammographic applications.
VXvue gets images from a detector, processes, and transfers the images and manages patient's information and the images for radiologists. VXvue enables images such as x-ray images to be stored electronically and viewed on screens.
VXvue offers full compliance with DICOM (Digital Imaging and Communications in Medicine) standards to allow the sharing of medical information with other PACS (Picture Archiving and Communication System Server). Besides, VXvue is a device that provides one or more capabilities relating to the acceptance, transfer, display, storage, and digital processing of medical images. The software components provide functions for performing operations related to image manipulation and enhancement.
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(168 days)
Acorn 3D Software is a modular image processing software intended for use as an interface for visualization of medical images, segmentation, treatment planning, and production of an output file.
The Acorn 3D Segmentation module is intended for use as a software interface and image segmentation system for the transfer of CT or CTA medical images to an output file. Acorn 3D Segmentation is also intended for measuring and treatment planning. The Acorn 3D Segmentation output can also be used for the fabrication of physical replicas of the output file using additive manufacturing methods, Acorn 3DP Models. The physical replica can be used for diagnostic purposes in the field of musculoskeletal and craniomaxillofacial applications.
The Acorn 3D Trajectory Automation module may be used to plan pedicle screw placement in the thoracic and lumbar regions of the spine in pediatric and adult patients.
Acorn 3D Software and 3DP Models should be used in conjunction with expert clinical judgment.
Acorn 3D Software is an image processing software that allows the user to import, visualize and segment medical images, check and correct the segmentations, and create digital 3D models. The models can be used in Acorn 3D Software for measuring, treatment planning and producing an output file to be used for additive manufacturing (3D printing). Acorn 3D Software is structured as a modular package.
This includes the following functionality:
- Importing medical images in DICOM format
- Viewing images and DICOM data
- Selecting a region of interest using generic segmentation tools
- Segmenting specific anatomy using dedicated semi-automatic tools or fully automatic algorithms
- Verifying and editing a region of interest
- Calculating a digital 3D model and editing the model
- Measuring on images and 3D models
- Exporting 3D models to third-party packages
- Planning pedicle screw placement
The Acorn 3D Segmentation module contains both machine learning based auto segmentation as well as semi-automatic and manual segmentation tools. The auto-segmentation tool is only intended to be used for thoracic and lumbar regions of the spine (T1-T12 and L1-L5) and the pelvis (sacrum). Semi-automatic and manual segmentation tools are intended to be used for all musculoskeletal anatomy.
| Automatic | Semi-Automatic | Manual | |
|---|---|---|---|
| Definition | Algorithmic with little or no direct human control | A combination of algorithmic and direct human control | Directly controlled by a human |
| Tool Type | Machine Learning algorithm used to automatically segment individual vertebrae and the pelvis | Algorithmic based tools that do not incorporate machine learning. | Manual tools requiring user input. |
| Anatomical Location(s) | Spinal anatomy:• Thoracic (T1-T12)• Lumbar (L1-L5)• Sacrum | Musculoskeletal & craniomaxillofacial bone:• Short• Long• Flat• Sesamoid• Irregular | Musculoskeletal & craniomaxillofacial bone:• Short• Long• Flat• Sesamoid• Irregular |
Acorn 3DP Model is an additively manufactured physical replica of the virtual 3D model generated in Acorn 3D Segmentation. The output file from Acorn 3D Segmentation is used to additively manufacture the Acorn 3DP Model.
The Acorn 3D Trajectory Automation module contains dedicated fully automatic algorithms for planning pedicle screw trajectories. The algorithms are only intended to be used for the thoracic and lumbar regions of the spine (T1-T12 and L1-L5). The output file from Acorn 3D Trajectory Automation contains information relevant to pedicle screw placement surgery, including entry points, end points, and screw sizes of planned screws.
The provided FDA 510(k) clearance letter describes the Acorn 3D Software, specifically focusing on the new Acorn 3D Trajectory Automation module. However, the document is quite sparse on detailed descriptions of the acceptance criteria and the specifics of the study proving the device meets these criteria. The information below is extracted from the provided text, and where details are missing, it's explicitly stated.
1. Table of Acceptance Criteria and Reported Device Performance
The document mentions "deviations were within the acceptance criteria" without specifying the numerical acceptance criteria themselves. It also doesn't provide specific numerical results of the device's performance, only a qualitative statement of accuracy.
| Acceptance Criteria (Not explicitly stated in numerical terms) | Reported Device Performance |
|---|---|
| Accuracy of pedicle screw geometry: Deviations within acceptance criteria | Deviations were within the acceptance criteria. |
| Accuracy of pedicle screw trajectories: Deviations within acceptance criteria | Deviations were within the acceptance criteria. |
| Substantial equivalence to predicate device for planning pedicle screws and trajectories | Performance testing demonstrated substantial equivalence to the predicate device. |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: Not specified. The document only mentions "clinical data" was used.
- Data Provenance: Not specified. It's unclear if the clinical data was retrospective or prospective, or the country of origin.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
- The document does not specify the number of experts used or their qualifications for establishing ground truth for the test set.
4. Adjudication Method for the Test Set
- The document does not specify any adjudication method (e.g., 2+1, 3+1, none) used for the test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- The document does not mention that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done. Therefore, no effect size of human readers improving with AI vs. without AI assistance is provided.
6. Standalone Performance Study
- Yes, a standalone performance study was done for the Acorn 3D Trajectory Automation module. The document states:
- "The accuracy of pedicle screw geometry as well as pedicle screw trajectories created in the subject device, Acorn 3D Trajectory Automation, was assessed via bench testing."
- This implies the algorithm's performance was evaluated independently without human intervention during the trajectory planning process itself, as it's a "fully automatic algorithm."
7. Type of Ground Truth Used
- The ground truth for the "accuracy of pedicle screw geometry" and "pedicle screw trajectories" was established by comparing the device's output to "clinical data." While the nature of this "clinical data" is not explicitly defined (e.g., expert consensus on images, surgical outcomes, or pathology reports), it serves as the reference standard.
8. Sample Size for the Training Set
- The document does not specify the sample size used for the training set of the machine learning algorithms. It mentions "Using a collection of images and masks as a training dataset for machine-learning segmentation algorithm" but no numbers.
9. How the Ground Truth for the Training Set Was Established
- The document states that the machine learning segmentation algorithm uses "a collection of images and masks as a training dataset." It doesn't explicitly describe how these "masks" (which represent the ground truth segmentations) were created. It can be inferred that these masks would have been generated by human experts, likely through manual or semi-automatic segmentation, but this is not confirmed in the text.
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(77 days)
The TheraSphere 360™ Y-90 Management Platform includes Treatment Planning and Activity Calculation functionalities as optional interactive tools intended for calculating the activity of TheraSphere Microspheres required at treatment time based upon the desired dose, lung shunt fraction, anticipated residual waste, and liver mass.
The Treatment Planning and Activity Calculation functionalities include features to aid in TheraSphere Microspheres dose vial selection.
Additionally, the TheraSphere 360 Platform includes optional post-treatment analysis functionalities to be used following treatment with TheraSphere Microspheres. For post-TheraSphere Microspheres treatment, the TheraSphere 360 Platform should only be used for the retrospective determination of dose and should not be used to prospectively calculate dose or for pre-treatment planning when there is a need for retreatment using TheraSphere Microspheres.
The TheraSphere 360 Y-90 Management Platform is an end-to-end, browser-based platform that will host a wide range of resources (e.g. radioembolization activity calculations, ordering, tracking, and education) that support Authorized Users of TheraSphere Microspheres.
The TheraSphere 360 Platform includes treatment planning functionality, activity calculation functionality, vial selection and ordering, and post-treatment analysis functionality. The treatment planning functionality and the activity calculation functionality include an interactive tool intended for calculating the activity of TheraSphere Microspheres required at the treatment time based upon the desired dose, lung shunt fraction, anticipated residual waste, and liver mass.
The Vial Selector function allows users to select and order TheraSphere Microspheres dose vials from inventory that match desired results.
The post-treatment analysis functionality is intended as an optional tool for post-treatment evaluation following TheraSphere Microspheres treatment.
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(202 days)
Sirona Advanced Imaging Suite is a Medical Image Management and Processing System and consists of four PET (Positron Emission Tomography) viewing features which is used for the viewing, registration, fusion, and/or display for diagnosis of medical images from the following modalities: PET and CT.
These features are as follows:
- a. PET-CT overlay/fusion
- b. Measurement of Standardized Uptake Value on PET image series and generated PET-CT overlay/fusion
- c. Maximum Intensity Reconstruction of PET image series
- d. Multiplanar Reconstruction of PET image series and PET-CT overlay/fusion
Sirona Advanced Imaging Suite is intended to be used with the Sirona PACS (or MIMPS) Viewer.
The intended users of the PET Module are trained radiologists, medical professionals, or other healthcare providers within a healthcare organization.
Sirona Advanced Imaging Suite is a software-based imaging solution designed to facilitate the review, analysis, and interpretation of positron emission tomography (PET) and computed tomography (CT) imaging studies. Intended to be used with the Sirona PACS (or MIMPS) Viewer, this module enables healthcare professionals, including radiologists and nuclear medicine physicians, to visualize, manipulate, and analyze multi-modality medical images for diagnostic and clinical decision-making. Sirona Advanced Imaging Suite provides image fusion and co-registration capabilities, allowing users to overlay PET and CT images for combined anatomical and functional assessment. It supports multi-planar reconstructions (MPRs), maximum intensity projections (MIP), and standardized uptake value (SUV) calculations for metabolic activity assessment. The software is fully compatible with DICOM standards, ensuring seamless integration with imaging modalities and healthcare IT infrastructure.
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