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Improved Detection of Benign and Malignant Rib Lesions in the Routine Computed Tomography Workup of Oncological Patients Using Automated Unfolded Rib Image Postprocessing

机译:在肿瘤患者的常规计算断层扫描过程中改善了良性和恶性肋病变的检测使用自动展开肋骨图像后处理

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Objective The aim of this study was to evaluate the performance of the automated computed tomography (CT) postprocessing software unfolded rib images for improved detection of both benign and malignant rib lesions during routine diagnostic workup of oncological patients. Materials and Methods One thousand eight in-patients and out-patients (63.66 +/- 14.25 years; range, 18.67-95.67 years; 405 females and 603 males), undergoing chest CT between July 2018 to January 2019 at our institution, were retrospectively evaluated. Patients underwent chest CT alone or as part of a whole-body CT staging/restaging. The CT protocol consisted of the following: 120 kV; 100 mAs; matrix, 512 x 512; collimation, 0.6 mm; reconstructed section thickness of 3 mm and 1 mm using a soft tissue spatial resolution kernel (I30f) and a sharp kernel (B70f). Both transversal image data sets were used for "conventional" diagnosis including coronal reformates with 3-mm slice thickness. One-millimeter slice thickness image data sets of all patients were additionally directed from the scanner to a computational server where they were automatically postprocessed to 3-dimensional unfolded ribs. The "unfolding" of the rib using the centerline as an axis allows a synchronous display and rotation of all ribs by mouse scrolling. These postprocessed image data sets were evaluated in a separate reading session (approximately 4 weeks later). The readers had no information about the underlying medical history or clinical presentation. They were asked to record the lesion number, site of involvement along the rib (proximal, body, distal), number of the involved ribs, and the character of the lesion in terms of lytic versus sclerotic versus mixed lytic/sclerotic. The standard of reference was F-18-FDG PET, Ga-68-DOMITATE PET/CT, bone scan, or imaging follow-up (>6 months). Results From a total of 1008 evaluated patients, 763 (73.02%) were hemato-oncologic patients. A total of 104 rib lesions were found by transversal CT image reading, whereas the unfolded rib image reading detected 305 lesions. Eighty-nine were classified malignant, and 202 were classified benign. Detection of malignant rib lesions proved significant both for less than 1 cm (P < 0.02) and more than 1 cm in diameter (P < 0.007). The sensitivity, specificity, positive predictive value, and negative predictive value for detection of malignant rib lesions were 97.7%, 98.5%, 96.6%, and 99% for unfolding ribs, and 76.4%, 100%, 92.7%, and 90.5% for conventional (transversal) image reading, respectively. Detection of sclerotic rib lesions and lesions greater than 1 cm in diameter were significantly better (P < 0.01) for the unfolding rib algorithm. Conclusions The "unfolded rib" reformates are significantly superior for rib lesion detection compared with conventional transversal CT scan reading and should therefore be used in all patients, particularly those with an oncologic background.
机译:目的本研究的目的是评估自动计算断层扫描(CT)后处理软件展开肋图像的性能,以改善肿瘤学患者常规诊断疗效期间良性和恶性肋病变的检测。材料和方法一千八名患者和外患者(63.66 +/- 14.25年;范围,18.67-95.67岁; 405岁的女性和603名男性),在2018年7月至2019年1月在我们的机构进行了回顾性评估。患者单独接受胸部CT或作为全身CT分期/重启的一部分。 CT协议包括:120 kV; 100 mas;矩阵,512 x 512;准直,0.6毫米;使用软组织空间分辨率内核(I30F)和尖锐的内核(B70F)重建截面厚度为3mm和1mm。两个横向图像数据集都用于“常规”诊断,包括具有3mm切片厚度的冠状重整。所有患者的一毫米切片厚度图像数据组另外从扫描仪到计算服务器,在那里它们被自动被破坏到三维展开肋。使用中心线作为轴的肋骨“展开”允许通过鼠标滚动同步显示和旋转所有肋骨。这些后处理的图像数据集在单独的读取会话中(大约4周稍后)进行评估。读者没有有关潜在的病史或临床表现的信息。他们被要求记录病变号,沿肋骨(近端,身体,远端),所涉及的肋骨数量,以及在裂解与硬化leytic / sclerotic方面的病变的特征。参考标准是F-18-FDG PET,GA-68 - 占PET / CT,骨扫描或成像后续(> 6个月)。结果来自1008名评估患者,763名(73.02%)是半肿瘤患者。通过横向CT图像读数发现总共104个肋病变,而展开的肋图像读数检测到305个病变。八十九分为恶性的恶性,202人被分类为良性。恶性肋病变的检测证明,直径小于1cm(P <0.02),直径大于1厘米(P <0.007)。检测恶性肋病变的敏感性,特异性,阳性预测值和阴性预测值为展开肋的97.7%,98.5%,96.6%和99%,76.4%,100%,92.7%和90.5%常规(横向)图像读数。用于展开肋算法的直径大于1cm的硬化肋病变和大于1cm的病变的检测显着更好(P <0.01)。结论与常规横向CT扫描读数相比,“展开肋骨”重构显着优于肋骨病变检测,因此应在所有患者中使用,特别是患有肿瘤背景的患者。

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