Familial health behavioral change in the context of adult treatment with obesity medications.

Chronic osteomyelitis is a persistent infectious bone disorder that presents substantial challenges in clinical management. Moreover, surgical debridement remains the most effective treatment strategy for controlling this condition (). However, surgical success requires careful balance; notably, insufficient debridement may leave residual infection and lead to recurrence, whereas overly aggressive debridement may result in unnecessary loss to healthy bone tissue (; ; ; ). Traditionally, surgeons determine the extent of debridement based on clinical experience and visual interpretation of imaging findings. This approach is inherently subjective and influenced by individual variability, making it difficult to accurately distinguish infected tissue from healthy bone. Radiomics, as emerging quantitative imaging analysis approach, has demonstrated transformative potential in this field (; ; ). By extracting high-dimensional quantitative features from medical images, radiomics provides objective quantitative standards for disease characterisation and has shown empirical value in improving diagnostic accuracy (; ; ). In our previous study, we applied the support vector machine (SVM) algorithm and demonstrated that a radiomics-based model incorporating a 5-mm expanded region of interest (ROI) outperformed the conventional ROI model in diagnosing chronic osteomyelitis (). However, excessive expansion may adversely affect model performance and compromise diagnostic accuracy. Moreover, although prior studies have primarily focused on diagnostic performance, the effect of ROI selection on defining the pathological extent of disease has not been thoroughly investigated. Importantly, precise alignment between the diagnostic ROI and the actual surgical field remains a significant clinical challenge. An ROI that is too small may overlook critical lesion areas, resulting in incomplete diagnostic information and reduced accuracy. Conversely, an excessively large ROI may include substantial amounts of normal tissue, thus increasing feature heterogeneity and analytical complexity. Similar considerations apply to the theoretical relationship between diagnostic ROI boundaries and surgical margins. Appropriate expansion is necessary to capture occult pathological changes, whereas excessive expansion may lead to unnecessary tissue damage. Therefore, accurately determining the optimal expansion range is essential for enhancing diagnostic precision and guiding surgical decision-making.