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in a patients with liver cancer, use of artificial intelligence before the surgery to predict and determine the loss of muscule mass and predict patients recovery after patient underwent liver surgery

Validation of Sarcopenia assessment using machine learning in the real-world scenario and its prediction of outcomes following liver resection. - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2026/03/106885
Enrollment
683
Registered
2026-03-25
Start date
Unknown
Completion date
Unknown
Last updated
2026-03-30

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: M629- Disorder of muscle, unspecified Health Condition 2: C220- Liver cell carcinoma

Interventions

Intervention1: Nil: Nil Control Intervention1: Nil: Nil

Sponsors

Tata Memorial Hospital
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: 1. Adults (equal or above 18 years) undergoing contrast or non-contrast abdominal CT for surgical evaluation. 2. Scans with complete L2 L4 vertebral levels visible. 3. Adequate image quality for segmentation.

Exclusion criteria

Exclusion criteria: 1. Metallic implants or instrumentation in the lumbar spine causing artefacts. 2. Severe scoliosis or deformities distorting psoas anatomy. 3. Incomplete CT series or missing DICOM data. 4. Severe motion artefacts or poor breath-hold affecting image clarity.

Design outcomes

Primary

MeasureTime frame
1. To identify patients with sarcopenia using CT-derived Hounsfield Unit Average Calculation (HUAC) scores using a deep learning model.Timepoint: 6 months—

Secondary

MeasureTime frame
To evaluate the association of sarcopenia and postoperative outcomes in patients undergoing abdominal surgeries.Timepoint: 6 months—

Countries

India

Contacts

Public ContactDr MIZELLE DSILVA

Tata Memorial Hospital

drmaheshgoel@gmail.com9820504492

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Apr 4, 2026