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syngo.via molecular imaging (MI) workflows comprise medical diagnostic applications for viewing, manipulation, quantification, analysis and comparison of medical images from single or multiple imaging modalities with one or more time-points. These workflows support functional data, such as positron emission tomography (PET) or nuclear medicine (NM), as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR). syngo.via MI workflows can perform harmonization of SUV (PET) across different PET systems or different PET reconstruction methods.

syngo.via MI workflows are intended to be utilized by appropriately trained health care professionals to aid in the management of diseases, including those associated with oncology, cardiology, neurology, and organ function. The images and results produced by the syngo.via MI workflows can also be used by the physician to aid in radiotherapy treatment planning.

syngo.via MI Workflows (including Scenium and syngo MBF applications) is a multi-modality post-processing software only medical device intended to aid in the management of diseases, including those associated with oncology, cardiology, neurology, and organ function. The syngo.via MI Workflows applications are part of a larger syngo.via client/server system which is intended to be installed on common IT hardware. The hardware itself is not seen as part of the syngo.via MI Workflows medical device.

The syngo.via MI Workflows software addresses the needs of the following typical users of the product:

• Reading Physician / Radiologist – Reading physicians are doctors who are trained in interpreting patient scans from PET, SPECT and other modality scanners. They are highly detail oriented and analyze the acquired images for abnormalities, enabling ordering physicians to accurately diagnose and treat scanned patients. Reading physicians serve as a liaison between the ordering physician and the technologists, working closely with both.
• Technologist – Nuclear medicine technologists operate nuclear medicine scanners such as PET and SPECT to produce images of specific areas and states of a patient's anatomy by administering radiopharmaceuticals to patients orally or via injection. In addition to administering the scan, the technologist must properly select the scan protocol, keep the patient calm and relaxed, monitor the patient's physical health during the protocol and evaluate the quality of the images. Technologists work very closely with physicians, providing them with quality-checked scan images.

The software has been designed to integrate the clinical workflow for the above users into a server-based system that is consistent in design and look with the base syngo.via platform and other syngo.via software applications. This ensures a similar look and feel for radiologists that may review multiple types of studies from imaging modalities other than Molecular Imaging, such as MR.

The syngo.via MI workflows software supports integration through DICOM transfers of positron emission tomography (PET) or nuclear medicine (NM) data, as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR).

Although data is automatically imported into the server based on predefined configurations through the hospital IT system, data can also be manually imported from external media, including CD, external mass storage devices, etc.

The Siemens syngo.via platform and the applications that reside on it, including syngo.via MI Workflows, are distributed via electronic medium. The Instructions for Use is also delivered via electronic medium.

syngo.via MI Workflows includes 2 workflows (syngo.MM Oncology and syngo.MI General) as well as the Scenium neurology software application and the syngo MBF cardiology software application which are launched from the OpenApps framework within the MI General workflow.

Here's a breakdown of the acceptance criteria and study details for the syngo.via MI Workflows, Scenium, and syngo MBF devices:

Acceptance Criteria and Reported Device Performance

For Lung and Lung Lobe Segmentation:

For PERCIST Liver Reference Region Placement (Binary Liver Mask, input to the algorithm):

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syngo.via molecular imaging (MI) workflows comprise medical diagnostic applications for viewing, manipulation, quantification, analysis and comparison of medical images from single or multiple imaging modalities with one or more time-points. These workflows support functional data, such as positron emission tomography (PET) or nuclear medicine (NM), as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR), syngo.via MI workflows can perform harmonization of SUV (PET) across different PET systems or different PET reconstruction methods.

syngo.via MI workflows are intended to be utilized by appropriately trained health care professionals to aid in the management of diseases, including those associated with oncology, cardiology, neurology, and organ function. The images and results produced by the syngo.via MI workflows can also be used by the physician to aid in radiotherapy treatment planning.

syngo.via MI Workflows (including Scenium and syngo MBF applications) is a multi-modality postprocessing software only medical device intended to aid in the management of diseases, including those associated with oncology, cardiology, neurology, and organ function. The syngo.via MI Workflows applications are part of a larger syngo.via client/server system which is intended to be installed on common IT hardware. The hardware itself is not seen as part of the syngo.via MI Workflows medical device.

The syngo.via MI Workflows software addresses the needs of the following typical users of the product:

• Reading Physician / Radiologist – Reading physicians are doctors who are trained in interpreting patient scans from PET, SPECT and other modality scanners. They are highly detail oriented and analyze the acquired images for abnormalities, enabling ordering physicians to accurately diagnose and treat scanned patients. Reading physicians serve as a liaison between the ordering physician and the technologists, working closely with both.
• Technologist – Nuclear medicine technologists operate nuclear medicine scanners such as PET and SPECT to produce images of specific areas and states of a patient's anatomy by administering radiopharmaceuticals to patients orally or via injection. In addition to administering the scan, the technologist must properly select the scan protocol, keep the patient calm and relaxed, monitor the patient's physical health during the protocol and evaluate the quality of the images. Technologists work very closely with physicians, providing them with quality-checked scan images.

The software has been designed to integrate the clinical workflow for the above users into a serverbased system that is consistent in design and look with the base syngo.via platform and other syngo.via software applications. This ensures a similar look and feel for radiologists that may review multiple types of studies from imaging modalities other than Molecular Imaging, such as MR.

The syngo.via MI workflows software supports integration through DICOM transfers of positron emission tomography (PET) or nuclear medicine (NM) data, as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR).

Although data is automatically imported into the server based on predefined configurations through the hospital IT system, data can also be manually imported from external media, including CD, external mass storage devices, etc.

The Siemens syngo.via platform and the applications that reside on it, including syngo.via MI Workflows, are distributed via electronic medium. The Instructions for Use is also delivered via electronic medium.

syngo.via MI Workflows includes 2 workflows (syngo.MM Oncology and syngo.MI General) as the Scenium neurology software application and the syngo MBF cardiology software application which are launched from the OpenApps framework within the MI General workflow.

Here's a breakdown of the acceptance criteria and study information for the Siemens syngo.via MI Workflows, including Scenium, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance for Test Set

• Calibration Data:
  • Sample Size: Not explicitly stated, but "calibration of PET images and their corresponding SUVr and CL reference data were obtained from the GAAIN website." This implies a sufficiently large dataset for method calibration.
  • Provenance: GAAIN website (Global Alzheimer's Association Interactive Network) – likely a multinational, retrospective dataset of clinical trial data.
• Validation Data (ADNI):
  • Sample Size: Not explicitly stated, but "two independent datasets" were used for validation against ADNI CL values for florbetaben. ADNI (Alzheimer's Disease Neuroimaging Initiative) is a large, multi-center, prospective observational study primarily conducted in North America.
  • Provenance: ADNI (Alzheimer's Disease Neuroimaging Initiative), likely primarily from the USA and Canada. Prospective given the nature of ADNI.
• Validation Data (Visual Reading Agreement):
  • Sample Size: 162 patients (69 females, 93 males)
  • Provenance: Retrospective review of patients with Mild Cognitive Impairment (MCI) who underwent A-PET. The specific country of origin is not mentioned.

3. Number of Experts and Qualifications for Ground Truth (Test Set)

• Calibration Data (GAAIN): The "standard method" for Centiloid scale calculation (Klunk et al.²) implies a consensus-derived or established expert-validated process. The number and specific qualifications of experts involved in the original GAAIN data curation are not detailed but are assumed to be highly qualified specialists in PET imaging and Alzheimer's research.
• Validation Data (ADNI): The ADNI Centiloid values are established through rigorous, expert-driven protocols. The text states "ADNI CL values," implying the ground truth was derived from the ADNI project's established methods, which involve numerous qualified experts in neurology, radiology, and nuclear medicine.
• Validation Data (Visual Reading Agreement): Patients were classified as "negative" by consensus. The number and specific qualifications of experts involved in this consensus are not explicitly stated, but it would typically involve experienced nuclear medicine physicians or radiologists specializing in neuroimaging.

4. Adjudication Method for the Test Set

• Calibration Data (GAAIN): Not explicitly stated, but the "standard method" for Centiloid score calculation suggests an established, perhaps algorithmic, adjudication or consensus process applied to the raw data.
• Validation Data (ADNI): Not explicitly stated, but the ADNI's established protocols for data analysis and Centiloid score determination would inherently involve robust, multi-expert consensus or adjudicated methods.
• Validation Data (Visual Reading Agreement): Patients were "classified as 'negative' by consensus." This indicates that multiple experts reviewed the images and reached an agreement on the classification. The specific method (e.g., 2+1, 3+1) is not provided.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No MRMC comparative effectiveness study was done comparing human readers with AI assistance vs. without AI assistance. The study primarily focuses on validating the device's output (Centiloid scores) against established standards and visual interpretations, not on human workflow improvement with AI.

6. Standalone (Algorithm Only) Performance

• Yes, standalone performance was done for the Scenium Centiloid scoring feature. The studies directly compare Scenium's calculated Centiloid scores (algorithm output) against "standard method" values (from GAAIN) and ADNI CL values. The agreement with visual reading also assesses the algorithm's standalone diagnostic accuracy in classifying patients.

7. Type of Ground Truth Used

• Expert Consensus / Established Methodology:
  • For the calibration, the ground truth was the "standard method" of Centiloid estimation as prescribed in Klunk et al.², using reference data from GAAIN, which is an established, expert-driven consortium.
  • For validation, it involved "ADNI CL values," which are considered an established ground truth in Alzheimer's research.
  • For the visual reading agreement, the ground truth was "visual-based classification" determined by expert consensus.

8. Sample Size for the Training Set

• The text does not explicitly mention a "training set" for the Scenium Centiloid scoring algorithm. The process described is a "calibration" using data from GAAIN to derive transformation equations, and then "validation" on independent datasets. It's possible the calibration data acts as a form of training/development set.
  • Calibration Data (GAAIN): Sample size not explicitly stated for the "calibration analysis" dataset.

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

• As a "training set" isn't explicitly defined, we refer to the calibration process. The ground truth for the calibration (or equations derivation) was established using "calibration of PET images and their corresponding SUVr and CL reference data obtained from the GAAIN website." This reference data itself would have been established through rigorous scientific methods and likely expert consensus within the GAAIN consortium, adhering to the "level-2 calibration analysis prescribed in Klunk et al.²" to ensure a standardized and reliable ground truth.

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syngo.via molecular imaging (MI) workflows comprise medical diagnostic applications for viewing, manipulation, quantification, analysis and comparison of medical images from single or multiple imaging modalities with one or more time-points. These workflows support functional data, such as positron emission tomography (PET) or nuclear medicine (NM), as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR). syngo.via MI workflows can perform harmonization of SUV (PET) across different PET systems or different PET reconstruction methods.

syngo via MI workflows are intended to be utilized by appropriately trained health care professionals to aid in the management of diseases, including those associated with oncology, cardiology, neurology, and organ function. The images and results produced by the syngo.via MI workflows can also be used by the physician to aid in radiotherapy treatment planning.

syngo.via MI Workflows (including Scenium and syngo MBF applications) is a multi-modality postprocessing software only medical device intended to aid in the management of diseases, including those associated with oncology, cardiology, neurology, and organ function. The syngo.via MI Workflows applications are part of a larger syngo.via client/server system which is intended to be installed on common IT hardware. The hardware itself is not seen as part of the syngo.via MI Workflows medical device.

The syngo.via MI Workflows software addresses the needs of the following typical users of the product:

• . Reading Physician / Radiologist – Reading physicians are doctors who are trained in interpreting patient scans from PET, SPECT and other modality scanners. They are highly detail oriented and analyze the acquired images for abnormalities, enabling ordering physicians to accurately diagnose and treat scanned patients. Reading physicians serve as a liaison between the ordering physician and the technologists, working closely with both.
• . Technologist – Nuclear medicine technologists operate nuclear medicine scanners such as PET and SPECT to produce images of specific areas and states of a patient's anatomy by administering radiopharmaceuticals to patients orally or via injection. In addition to administering the scan, the technologist must properly select the scan protocol, keep the patient calm and relaxed, monitor the patient's physical health during the protocol and evaluate the quality of the images. Technologists work very closely with physicians, providing them with quality-checked scan images.

The software has been designed to integrate the clinical workflow for the above users into a serverbased system that is consistent in design and look with the base syngo.via platform and other syngo.via software applications. This ensures a similar look and feel for radiologists that may review multiple types of studies from imaging modalities other than Molecular Imaging, such as MR.

syngo.via MI workflows software supports integration through DIC emission tomography (PET) or nuclear medicine (NM) data, as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR).

Although data is automatically imported into the server based on predefined configurations through the hospital IT system, data can also be manually imported from external media, including CD, external mass storage devices, etc.

The Siemens syngo.via platform and the applications that reside on it, including syngo.via MI Workflows, are distributed via electronic medium. The Instructions for Use is also delivered via electronic medium.

syngo.via MI Workflows includes 2 workflows (syngo.MM Oncology and syngo.MI General) as the Scenium neurology software application and the syngo MBF cardiology software application which are launched from the OpenApps framework within the MI General workflow.

Here's a breakdown of the acceptance criteria and the study information for the Syngo.via MI Workflows, Scenium, and Syngo MBF device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document primarily focuses on two areas of performance evaluation: Organ Segmentation and Tau Workflow Support. The acceptance criteria for Organ Segmentation are explicitly stated, while for Tau Workflow, the criteria are implied through correlation and agreement with existing methods.

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

• Organ Segmentation: Not explicitly stated. The algorithm used was "originally cleared within syngo.via RT Image Suite (K201444) and carried into the reference predicate device (syngo.via RT Image Suite, K220783)." This suggests the data provenance for this algorithm was tied to those previous clearances. The document implies the segmentation quality was assessed, but the specific test set size for this current submission is not provided.
• Tau Workflow Support: "more than 700 flortaucipir images from ADNI".
• Data Provenance (Tau Workflow): "ADNI" (Alzheimer's Disease Neuroimaging Initiative). This is a prospective, multi-center, North American study. The exact countries of origin of the individual images are not specified but ADNI is a U.S. led initiative with international participation.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• Organ Segmentation: For manual ground truth annotation, the number of experts and their qualifications are not specified.
• Tau Workflow Support: The ground truth for the "MR-based method and MR-based segmentations" used for comparison is from existing methods mentioned in the references. The number and qualifications of experts involved in establishing this historical ground truth are not specified in this document.

4. Adjudication Method for the Test Set

• Organ Segmentation: An adjudication method is not explicitly stated. The process involved "comparing a manually annotated ground truth with the algorithm result." It's common for a single expert or a consensus of experts to establish manual ground truth, but the method for resolving discrepancies or reaching consensus is not detailed here.
• Tau Workflow Support: An adjudication method is not explicitly stated. The comparison was made between the device's calculated SUVRs and those from an "MR-based method and MR-based segmentations." This implies a comparison against a pre-established or validated method rather than a multi-reader adjudication specifically for this study.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No MRMC comparative effectiveness study was done for this submission. The document explicitly states: "Clinical testing was not conducted for this submission." The evaluations focused on standalone performance and agreement with existing methods.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Performance

• Yes, standalone performance was done.
  • Organ Segmentation: The segmentation algorithm's performance (DICE coefficient and ASSD) was assessed by comparing its output directly against manually annotated ground truth. This is a standalone evaluation.
  • Tau Workflow Support: The "SUVRs calculated on individual and composite Braak VOIs using our pipeline and our masks" were compared to an "MR-based method." This directly assesses the algorithm's standalone quantification capabilities.

7. Type of Ground Truth Used

• Organ Segmentation: Expert consensus (manual annotation) is implied ("manually annotated ground truth").
• Tau Workflow Support: Reference method (MR-based method and MR-based segmentations) and potentially expert consensus that established those reference methods. The references provided suggest established research pipelines for flortaucipir processing and ADNI publications, which would typically involve expert interpretation and validation.

8. Sample Size for the Training Set

• Organ Segmentation: The document states the algorithm is the "same algorithm originally cleared within syngo.via RT Image Suite (K201444) and carried into the reference predicate device (syngo.via RT Image Suite, K220783)." The training set size for this re-used algorithm is not specified in this document, but would have been part of the original clearance.
• Tau Workflow Support: The training set size for the tau quantification workflow is not specified.

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

• Organ Segmentation: The method for establishing ground truth for the training set of the deep-learning algorithm is not specified in this document. Given it's a deep-learning algorithm, it would typically involve expert-labeled data, but the details are not provided.
• Tau Workflow Support: The method for establishing ground truth for the training set (if applicable) for the tau quantification workflow is not specified. It mentions using the AAL atlas as a basis for defining Braak regions, which is a pre-existing anatomical atlas.

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syngo.via molecular imaging (MI) workflows comprise medical diagnostic applications for viewing, manipulation, quantification, analysis and comparison of medical images from single or multiple imaging modalities with one or more time-points. These workflows support functional data, such as position emission tomography (PET) or nuclear medicine (NM), as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR), syngo.via MI workflows can perform harmonization of SUV (PET) across different PET systems or different PET reconstruction methods.

syngo.via MI workflows are intended to be utilized by appropriately trained health care professionals to aid in the management of diseases, including those associated with oncology, neurology, and organ function. The images and results produced by the syngo.via MI workflows can also be used by the physician to aid in radiotherapy treatment planning.

syngo.via MI Workflows is a multi-modality post-processing software only medical device, which is intended to be installed on common IT hardware. This hardware must fulfill the defined requirements. The hardware itself is not seen as part of the medical device.

The Siemens syngo.via platform (K191040) and the applications that reside on it are distributed via electronic medium. The Instructions for Use also delivered via electronic medium.

synqo.via molecular imaging (MI) workflows comprise medical diagnostic applications for viewing, manipulation, quantification, analysis and comparison of medical images from single or multiple imaging modalities with one or more time-points. These workflows support functional data, such as positron emission tomography (PET) or nuclear medicine (NM), as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR).

syngo.via MI Workflows enable visualization of information that would otherwise have to be visually compared disjointedly. syngo.via MI workflows are intended to be utilized by appropriately trained health care professionals to aid in the management of diseases, including those associated with oncology, cardiology, neurology, and organ function. The images and results produced by the syngo.via MI workflows can also be used by the physician to aid in radiotherapy treatment planning.

Scenium assists in the display and analysis of images within the MI Neurology workflow of syngo.via MI Workflows. This software enables visualization and appropriate rendering of multimodality data, providing a number of features which enable the user to process acquired image data.

Scenium consists of four workflows:

• Database Comparison
• -Striatal Analvsis
• -Cortical Analysis
• -Subtraction

The Scenium workflows are used to assist the clinician with the visual evaluation, assessment and quantification of pathologies, such as dementia (i.e., Alzheimer's), movement disorders (i.e., Parkinson's) and seizure analysis (i.e., Epilepsy),

syngo MBF is a software only product intended for visualization, assessment and quantification of medical images: specifically providing quantitative blood flow measurements of PET images. The software is launched from the OpenApps Framework within the MI Cardiology workflow within syngo.Via MI Workflows. The application supports dynamic Rubidium – PET and dynamic Ammonia – PET images. The application provides visualization and measurement tools, for qualitative and quantitative visualization and assessment of the input data. It provides automatic and manual tools to orient and segment the myocardium. The software calculates measurements of myocardial blood flow, and provides tools, such as a database comparison workflow, for the Clinician to assess these results.

The provided text describes modifications to the syngo.via MI Workflows software (specifically VB60A, Scenium VE40A, and syngo MBF VB30A versions) and asserts their substantial equivalence to a predicate device (syngo.via MI Workflows VB50A, Scenium VE30A, and syngo MBF VB20A, K201195). However, it does not contain a detailed description of acceptance criteria or a specific study proving the device meets those criteria in the typical sense of a clinical or performance validation study with quantitative metrics, expert adjudication, or MRMC data.

Instead, the document focuses on:

• Regulatory Compliance: Adherence to FDA regulations (21 CFR 892.2050, 21 CFR Part 807.87(h)), recognized standards (ISO 14971, EN ISO 13485, IEC 62304, NEMA PS 3.1-3.20, IEC 62366-1, ISO 15223-1), and cybersecurity guidelines.
• Functional Equivalence: Stating that the new features do not alter the existent technological characteristics or raise new issues of safety and effectiveness compared to the predicate device.
• Verification and Validation (V&V): A general statement that "Verification and Validation activities have been successfully performed on the software package, including assurance that functions work as designed, performance requirements and specifications have been met, and that all hazard mitigations have been fully implemented. All testing has met the predetermined acceptance values."

Without specific performance metrics and a detailed study design provided in the given text, it is not possible to fully populate all components of your request. I will extract what information is present and indicate where information is Not Provided (NP).

Acceptance Criteria and Device Performance (as inferred from the document)

The document broadly states that "All testing has met the predetermined acceptance values." However, it does not explicitly define these "predetermined acceptance values" in a quantitative table. The primary acceptance criteria appear to be substantial equivalence, functional correctness, and adherence to safety and quality standards.

Study Details:

1. Sample sizes used for the test set and the data provenance:

   • Test Set Sample Size: NP (Not provided in the document. The document refers to "Verification and Validation activities" and "All testing" but does not specify the number of cases or datasets used for these tests.)
   • Data Provenance: NP (Not provided. It is not stated where the data for testing originated from, e.g., country of origin, or if it was retrospective or prospective data.)

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Number of Experts: NP (Given the nature of the modifications described – mainly functional additions and improvements to existing workflows – it's unlikely a traditional "ground truth" for disease diagnosis was established for this specific submission beyond ensuring the software performs its intended technical functions. If expert review was part of the V&V, it is not detailed.)
   • Qualifications of Experts: NP

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Adjudication Method: NP (This type of adjudication is typically for establishing diagnostic ground truth, which is not the focus of the described V&V for these software updates.)

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: No. The document describes software workflow updates for viewing, manipulation, quantification, and analysis of medical images. It does not introduce an "AI" component intended to directly assist or change clinical decision-making in a way that would necessitate an MRMC study demonstrating improved human reader performance. The software is a tool for professionals, not an AI diagnostic assistant.

5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:

   • Standalone Performance: The V&V activities would have included testing of the software's algorithms and functions in a standalone manner to ensure they work as designed and meet specifications. However, specific metrics (e.g., accuracy, sensitivity, specificity for automated tasks) are NP for any specific algorithm. The "syngo MBF" module, for instance, calculates quantitative blood flow measurements, and its accuracy would have been part of the V&V, but no specific performance statistics are provided.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • Type of Ground Truth: For the nature of these software updates, the "ground truth" would likely be technical correctness and adherence to algorithmic specifications rather than clinical outcomes or pathology. For example, ensuring that a 4D visualization works as intended, or that quantitative measurements (e.g., SUV harmonization, blood flow measurements) are mathematically correct and consistent with reference values or established methodologies. Detailed information about exactly how this "ground truth" was established (e.g., through phantom studies, simulations, or comparison with established clinical software/manual calculations) is NP.

7. The sample size for the training set:

   • Training Set Sample Size: NP. The document does not mention training sets, which implies that the updates are not based on a machine learning model that would require a distinct training phase. These are described as functional additions and improvements to existing software, not new AI/ML algorithms.

8. How the ground truth for the training set was established:

   • Training Set Ground Truth: NP, as no specific training set for (ML/AI) models is implied.

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