Thermal imaging in total knee replacement and its relation with inflammation markers
| Autor: | Karan Jindal, Jaspreet Singh, Aman Hooda, Dhillon, Viney Lohchab, Vikas Bachhal, Prasant Kumar Mahapatra |
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| Rok vydání: | 2021 |
| Předmět: |
Knee Joint
medicine.medical_treatment Total knee replacement Knee replacement Inflammation Osteoarthritis Knee region Blood Sedimentation image analysis medicine thermal imaging QA1-939 Humans Arthroplasty Replacement Knee skin temperature medicine.diagnostic_test business.industry Applied Mathematics Skin temperature non-invasive assessment General Medicine medicine.disease inflammatory markers Computational Mathematics Modeling and Simulation Erythrocyte sedimentation rate Quality of Life Raised temperature medicine.symptom General Agricultural and Biological Sciences business Nuclear medicine TP248.13-248.65 Mathematics Biotechnology |
| Zdroj: | Mathematical Biosciences and Engineering, Vol 18, Iss 6, Pp 7759-7773 (2021) |
| ISSN: | 1551-0018 |
| Popis: | Total knee replacement is an end-stage surgical treatment of osteoarthritis patients to improve their quality of life. The study presents a thermal imaging-based approach to assess the recovery of operated-knees. The study focuses on the potential of thermal imaging for total knee replacement and its relation with clinical inflammatory markers. A total of 20 patients with bilateral knee replacement were included for thermal imaging and serology, where data was acquired on pre-operative day and five post-operative days. To quantify the inflammation, the temperature-based parameters (like mean differential temperature, relative percentage of raised temperature) were evaluated from thermal images, while the clinically proven inflammation markers were obtained from blood samples for clinical validation. Initially, the knee region was segmented by applying the automatic method, subsequently, the mean skin temperature was calculated and investigated for a statistical relevant relationship with inflammatory markers. After surgery, the mean skin temperature was first increased (>2.15 ℃ for different views) then settled to pre-operative level by 90th day. Consequently, the mean differential temperature showed a strong correlation with erythrocyte sedimentation rate (r > 0.893) and C-reactive protein (r > 0.955). Also, the visual profile and relative percentage of raised temperature showed promising results in quantifying the temperature changes both qualitatively and quantitatively. This study provides an automatic and non-invasive way of screening the patients for raised levels of skin temperature, which can be a sign of inflammation. Hence, the proposed temperature-based technique can help the clinicians for visual assessment of post-operative recovery of patients. |
| Databáze: | OpenAIRE |
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