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LOGIQ Totus is intended for use by a qualified physician for ultrasound evaluation of Fetal/Obstetrics; Abdominal(including Renal, Gynecology/Pelvic), Pediatric; Small organ(Breast, Testes, Thyroid); Neonatal Cephalic; Adult Cephalic; Cardiac(Adult and Pediatric), Peripheral Vascular, Musculo-skeletal Conventional and Superficial; Urology(including Prostate); Transrectal; Transvaginal; Transesophageal and Intraoperative(Abdominal and Vascular).

Modes of operation includes: B, M, PW Doppler, CW Doppler, Color Doppler, Color M Doppler, Power Doppler, Harmonic Imaging, Coded Pulse, 3D/4D Imaging mode, Elastography, Shear Wave Elastography, Attenuation Imaging and Combined modes: B/M, B/Color, B/PWD, B/Color/PWD, B/Power/PWD.

The LOGIQ Totus is intended to be used in a hospital or medical clinic.

The LOGIQ Totus is full featured, Track 3 device, primarily intended for general purpose diagnostic ultrasound system which consists of a mobile console approximately 490mm wide (monitor width: 545mm), 835mm deep and 1415~1815mm high that provides digital acquisition, processing and display capability. The user interface includes a computer keyboard, specialized controls, 14-inch LCD touch screen and color 23.8-inch LCD & HDU image display.

The provided FDA 510(k) clearance letter and summary for the LOGIQ Totus Ultrasound System (K253370) describes the acceptance criteria and the study for the Ultrasound Guided Fat Fraction for adult imaging (UGFF) software feature. This feature is being added to the LOGIQ Totus and is similar to a previously cleared Siemens UDFF feature.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document describes the performance of the UGFF feature by comparing it to MRI Proton Density Fat Fraction (MRI-PDFF) and, in a separate confirmatory study, to a predicate UDFF device. The "acceptance criteria" are implied by the reported strong correlations and limits of agreement with these reference standards.

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

• Primary Study (UGFF vs. MRI-PDFF):

  • Sample Size: 582 participants
  • Data Provenance: External clinical study in Japan (Population: Asian). The study was retrospective or prospective is not specified, but the phrase "obtained from the liver of five hundred and eighty-two (582) participants" suggests a data collection event rather than a purely retrospective analysis of existing medical records. The study is described as an "external clinical study," further suggesting a dedicated data collection.

• First Confirmatory Study (UGFF vs. MRI-PDFF):

  • Sample Size: 15 US patients and 5 EU patients (total 20 patients)
  • Data Provenance: US and EU patients. Demographic information on the 5 EU patients was unavailable. This was conducted as a "confirmatory study."

• Second Confirmatory Study (UGFF vs. UDFF):

  • Sample Size: 24 EU patients
  • Data Provenance: EU patients. This was conducted as a "confirmatory study."

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

The document does not specify the number of experts or their qualifications for establishing the ground truth.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method. For the UGFF feature, the "ground truth" was objective measurements (MRI-PDFF or a predicate device's UDFF), which typically do not require adjudication by human experts in the same way an image diagnosis might.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done for the UGFF feature as described. The studies focused on comparing the device's output (UGFF index) to an objective reference standard (MRI-PDFF or another device's UDFF), not on how human readers' performance improved with or without AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, a standalone performance evaluation was done. The UGFF index, based on acoustic property measurements, is compared directly to MRI-PDFF and UDFF. This indicates the algorithm's performance independent of human interpretation or intervention in the final measurement calculation. While a technologist operates the ultrasound system, the UGFF index calculation itself is an algorithmic output.

7. The Type of Ground Truth Used

The type of ground truth used is MRI Proton Density Fat Fraction (MRI-PDFF) measurements, which are quantitative and objective reference standards for liver fat quantification. Additionally, for one confirmatory study, the ground truth was the Ultrasound-Derived Fat Fraction (UDFF) from a Siemens Acuson S3000/S2000, functioning as a predicate device's output. These are akin to "outcomes data" or "established reference standard measurements."

8. The Sample Size for the Training Set

The document states: "During the migration of the AI software feature from LOGIQ E10s (K231989), the algorithm was not retrained and there were no changes to the algorithmic flow or the AI components performing the inferencing." This implies the training set was associated with the original clearance of the Auto Renal Measure Assistant on the LOGIQ E10s (K231989) but the sample size for the training set is not provided in this document.

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

Similarly, since the algorithm was not retrained and the document pertains to the migration of an existing AI feature, the method for establishing the ground truth for the original training set is not provided in this document.

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The LOGIQ Totus is a general-purpose diagnostic ultrasound system intended for use by qualified and trained healthcare professionals for ultrasound imaging, measurement, display and analysis of the human body and fluid. LOGIQ Totus clinical applications include: Fetal / Obstetrics; Abdominal (including Renal, Gynecology/Pelvic); Pediatric; Small Organ (Breast, Testes, Thyroid); Neonatal Cephalic; Adult Cephalic; Cardiac(Adult and Pediatric); Peripheral Vascular; Musculo-skeletal Conventional and Superficial; Urology (including Prostate); Transrectal; Transvaginal.

Modes of operation include: B, M, PW Doppler, CW Doppler, Color Doppler, Color M Doppler, Power Doppler, Harmonic Imaging, Coded Pulse, 3D/4D Imaging mode, Elastography, Shear Wave Elastography, Attenuation Imaging, Contrast Enhanced Imaging and Combined modes: B/M, B/Color, B/PWD, B/Color/PWD, B/Power/PWD.

The system is intended to be used in Hospital or Clinical environments such as Intensive Care Unit(ICU, CVICU, CCU), Neonatal Intensive Care Unit(NICU), Pediatric Intensive Care Unit(PICU), Emergency Room, Operating Room, Outpatient Surgery Clinic, Radiology, Medical Office (Nurse Practitioner), Observational Units, Cath Lab, Clinic, Physician's Office, Labor/Deliver Unit and Oncology.

The LOGIQ Totus is full featured, Track 3 device, primarily intended for general purpose diagnostic ultrasound system which consists of a mobile console approximately 490mm wide(monitor width: 545mm), 835mm deep and 1415~1815mm high that provides digital acquisition, processing and display capability. The user interface includes a computer keyboard, specialized controls. 14-inch LCD touch screen and color 23.8-inch LCD & HDU image display.

The provided document contains information on two AI features: "Auto preset selection" and "Auto Abdominal Color Assistant". The acceptance criteria and study details for each are presented below.

Auto Preset Selection

1. A table of acceptance criteria and the reported device performance:

2. Sample size used for the test set and the data provenance:

• Test Set Sample Size:
  • Number of individual patients' images collected from: 50+ patients
  • Number of samples (images): 330+ images
• Data Provenance:
  • Country of Origin: USA (57%) and Australia (43%)
  • Retrospective/Prospective: Not explicitly stated, but the mention of "data collection protocol was standardized" suggests it might be retrospective collection of pre-existing data, or a controlled prospective study.

3. 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 how many individual sonographers/clinicians were involved.
• Qualifications of Experts: "Certified sonographer/clinician." No years of experience or specific board certifications are mentioned.

4. Adjudication method for the test set:

• Adjudication Method: "For the testing process, the results are generated by the AI software and the same are verified as Pass or Fail by a certified sonographer/clinician." This implies a single expert verification without explicit multi-reader adjudication (e.g., 2+1 or 3+1).

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• No MRMC comparative effectiveness study was explicitly mentioned for this AI feature. The testing method described focuses on the AI's success rate verified by experts, not on comparing human performance with and without AI assistance.

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

• Yes, the "overall model success rate" refers to the algorithm's performance in suggesting views. The "verified as Pass or Fail by a certified sonographer/clinician" is likely a post-hoc verification of the algorithm's output, rather than an interactive human-in-the-loop study.

7. The type of ground truth used:

• Type of Ground Truth: Expert verification by certified sonographer/clinician, determining if the AI's view suggestion was a "Pass or Fail". This can be considered a form of "expert consensus" or "expert truth" (albeit with a single expert verification as mentioned in point 4).

8. The sample size for the training set:

• Not explicitly stated. The document only mentions that "The exams used for test/training validation purpose are separated from the ones used during training process and there is no overlap between the two." The sample size (330+ images from 50+ patients) is specified for the test set.

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

• Not explicitly stated. The document mentions that the test data was independent of the training data but doesn't detail the ground truth establishment for the training set. It's generally assumed that ground truth for training data in such AI applications would also be established by experts.

Auto Abdominal Color Assistant

1. A table of acceptance criteria and the reported device performance:

2. Sample size used for the test set and the data provenance:

• Test Set Sample Size:
  • Number of individual patients' images collected from: 40 patients
  • Number of samples (images): 280+ images
• Data Provenance:
  • Country of Origin: USA (35%) and Australia (65%)
  • Retrospective/Prospective: Similar to "Auto preset selection", not explicitly stated, but a "standardized data collection protocol" is mentioned.

3. 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 how many individual sonographers/clinicians were involved.
• Qualifications of Experts: "Certified sonographer / clinician." No years of experience or specific board certifications are mentioned.

4. Adjudication method for the test set:

• Adjudication Method: "For the testing process, the results are generated by the AI software and the same are verified a Pass or Fail by a certified sonographer / clinician." This implies a single expert verification without explicit multi-reader adjudication.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• No MRMC comparative effectiveness study was explicitly mentioned for this AI feature.

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

• Yes, the "overall model success rate" refers to the algorithm's performance. The "verified as Pass or Fail by a certified sonographer / clinician" is likely a post-hoc verification of the algorithm's output.

7. The type of ground truth used:

• Type of Ground Truth: Expert verification by certified sonographer/clinician, determining if the AI's view suggestion was a "Pass or Fail".

8. The sample size for the training set:

• Not explicitly stated. The document only mentions that "The exams used for test/training validation purpose are separated from the ones used during training process and there is no overlap between the two." The sample size (280+ images from 40 patients) is specified for the test set.

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

• Not explicitly stated. Similar to the "Auto preset selection" feature, it's assumed expert input would have been used for training data ground truth, but no details are provided.

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