Adipose Tissue Impacts Radiofrequency Ablation Lesion Size: Results of an Ex Vivo Poultry Model.

BACKGROUND: Radiofrequency ablation (RFA) is a common treatment in which radiofrequency (RF) is used to heat neural tissue and reduce pain. The impact of adipose content in tissue on the lesion size may impact efficacy, and to date, there is little, if any, data comparing its influence on RFA. OBJECTIVES: We evaluated the influence of adipose tissue on RF lesion size. STUDY DESIGN: Controlled, ex vivo study. SETTING: Academic institution in a procedural setting. METHODS: RF lesions were created using 20-G 10-mm protruding electrode (PE) needles inserted into unbrined chicken breasts and thighs at 21°C. RF current was applied for 90 seconds at 80°C. Chicken breasts were used as the control group and chicken thighs were used as the high adipose variant. Four different groups were examined: 1- Standard 20 g RFA needle, 2- 20 g RFA PE needle, 3- Standard RFA needle with lidocaine 2% injectate, and 4- Standard RFA needle with iohexol 240 mg injectate. There were 12 lesions performed in each group; length, width, and depth were measured. RESULTS: The control group had significantly deeper lesions in all 4 cohorts. Lesions' lengths were smaller in the fat-rich group. The control and PE cohorts showed a significant difference in width between the 2 fat-rich and nonfatty groups. LIMITATIONS: Radiofrequency ablation was performed at room temperature and not heated to physiological temperature. This was an ex vivo study, thus factors of human anatomy and physiology could not be evaluated. CONCLUSIONS: Adipose tissue content was inversely related to lesion size in all samples. This factor should be considered when assessing methods of enhancing lesion size in human models.

Estimation of Hemi-Abdominal-Based Free Flap Weight Using Two Computed Tomography-Derived Measurements.

BACKGROUND: Accurate flap weight estimation is crucial for preoperative planning in microsurgical breast reconstruction; however, current flap weight estimation methods are time consuming. It was our objective to develop a parsimonious and accurate formula for the estimation of abdominal-based free flap weight. METHODS: Patients who underwent hemi-abdominal-based free tissue transfer for breast reconstruction at a single institution were retrospectively reviewed. Subcutaneous tissue thicknesses were measured on axial computed tomography angiograms at several predetermined points. Multivariable linear regression was used to generate the parsimonious flap weight estimation model. Split-sample validation was used to for internal validation. RESULTS: A total of 132 patients (196 flaps) were analyzed, with a mean body mass index of 31.2 ± 4.0 kg/m2 (range: 22.6-40.7). The mean intraoperative flap weight was 990 ± 344 g (range: 368-2,808). The full predictive model (R 2 = 0.68) estimated flap weight using the Eq. 91.3x + 36.4y + 6.2z - 1030.0, where x is subcutaneous tissue thickness (cm) 5 cm lateral to midline at the level of the anterior superior iliac spine (ASIS), y is distance (cm) between the skin overlying each ASIS, and z is patient weight (kg). Two-thirds split-sample validation was performed using 131 flaps to build a model and the remaining 65 flaps for validation. Upon validation, we observed a median percent error of 10.2% (interquartile range [IQR]: 4.5-18.5) and a median absolute error of 108.6 g (IQR: 45.9-170.7). CONCLUSION: We developed and internally validated a simple and accurate formula for the preoperative estimation of hemi-abdominal-based free flap weight for breast reconstruction.