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Multiscale image analysis for the quantitative evaluation of periapical lesion healings

机译:多尺度图像分析用于定量评估根尖周病变愈合情况

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Intraoral radiographs are used routinely for the diagnosis of periapical lesions and the evaluation of subsequent lesion treatments. However, a reliable and reproductive evaluation is often difficult due to the subjectiveness of visual interpretation and various imaging factors in routine dental radiography. To aid radiographic evaluation of periapical lesion healing, we have developed a multiscale image analysis method based on the change of bone features. Fifty pairs of pre- and post-treatment intraoral radiographs were retrospectively obtained and classified into successful (25 cases) or failed (25 cases) treatments based on the presence of periapical radiolucency. To accurately segment the bone images, an optimal scale was determined at which measured bone thickness reached 95% of the maximum values. Trabecular bone images were segmented in multiple scales to calculate intensity and skeleton features. Texture features were calculated within the user-traced lesion area. Based on relative differences of these features between pre- and post-treatment, several treatment efficacy models were derived and tested by leave one out cross validation. Intensity, skeleton, and texture features were significantly changed after successful treatment (Wilcoxon's paired test, p<0.05). Treatment efficacy of periapical lesions was classified at the sensitivity of 96% and the specificity of 92% (logistic regression analysis). We found that healing lesions show not only brighter but also larger, thicker, more branched trabecular bones, while cases of persistent disease have bones with more uniform density. Our model may aid the early intervention for re-treatment of failed lesion healings.
机译:常规使用口内X光片来诊断根尖周病变和评估随后的病变治疗。然而,由于视觉解释的主观性和常规牙科X线照相中的各种成像因素,通常难以进行可靠且生殖力的评估。为了辅助根尖周病变愈合的放射学评估,我们基于骨骼特征的变化开发了一种多尺度图像分析方法。回顾性地获得五十对治疗前和治疗后口腔内X光片,并根据根尖周放射线透亮度将治疗分为成功(25例)或失败(25例)治疗。为了准确地分割骨骼图像,确定了最佳比例,在该比例下测得的骨骼厚度达到最大值的95%。将小梁骨图像分割成多个比例,以计算强度和骨骼特征。在用户追踪的病变区域内计算纹理特征。根据治疗前后这些特征的相对差异,通过留出一个交叉验证,得出并测试了几种治疗功效模型。成功治疗后,强度,骨骼和质地特征发生了显着变化(Wilcoxon配对测试,p <0.05)。根尖周病变的治疗效率分为敏感性96%和特异性92%(逻辑回归分析)。我们发现,愈合损伤不仅显示出更明亮,而且显示出更大,更粗,更分支的小梁骨,而持续性疾病病例的骨密度更均匀。我们的模型可能有助于早期干预,以重新治疗失败的伤口愈合。

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