Diagnostic Accuracy of Contrast-Enhanced Thoracic Photon-Counting Computed Tomography for Opportunistic Locoregional Staging of Breast Cancer Compared With Digital Mammography: A Prospective Trial.
IF 7 1区 医学Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Jakob Neubauer, Caroline Wilpert, Oliver Gebler, Florin-Andrei Taran, Martin Pichotka, Thomas Stein, Moisés Felipe Molina-Fuentes, Jakob Weiss, Ingolf Juhasz-Böss, Fabian Bamberg, Marisa Windfuhr-Blum, Claudia Neubauer
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引用次数: 0
Abstract
Objective: Accurate locoregional staging is crucial for effective breast cancer treatment. Photon-counting computed tomography (PC-CT) is an emerging technology with high spatial resolution and the ability to depict uptake of contrast agents in tissues, making it a promising tool for breast cancer imaging. The aim of this study was to establish the feasibility of locoregional staging of breast cancer through contrast-enhanced thoracic PC-CT, assess its diagnostic performance, and compare it with that of digital mammography (DM).
Materials and methods: Patients with newly diagnosed breast cancer, DM, and indication of thoracic CT staging were prospectively enrolled in this clinical cohort study over a period of 6 months. Participants underwent contrast-enhanced thoracic PC-CT and breast magnetic resonance imaging in prone position. After blinding to patient data, 2 radiologists independently rated PC-CT and DM regarding the following 6 characteristics: (1) diameter of the largest mass lesion, (2) infiltration of cutis/pectoral muscle/thoracic wall, (3) number of mass lesions, (4) presence/absence of adjacent ductal carcinoma in situ (DCIS), (5) tumor conspicuity, and (6) diagnostic confidence. Reference standard was generated from consensus reading of magnetic resonance imaging combined with all histopathological/clinical data by an independent adjudication committee applying TNM eighth edition.
Results: Among 32 enrolled female subjects (mean ± SD age, 59 ± 13.0 years), diagnostic accuracy for T-classification was higher for PC-CT compared with DM (0.94 vs 0.50, P < 0.01). Moreover, the correlation of the number of detected tumor masses with the reference standard was stronger for PC-CT than for DM (0.72 vs 0.50, P < 0.01). We observed that PC-CT significantly ( P < 0.04) outperformed DM regarding not only sensitivity (0.83 and 0.25, respectively) but also specificity (0.99 and 0.80, respectively) for adjacent DCIS. The κ values for interreader reliability were higher for PC-CT compared with DM (mean 0.88 vs 0.54, respectively; P = 0.01).
Conclusions: Photon-counting computed tomography outperformed DM in T-classification and provided higher diagnostic accuracy for the detection of adjacent DCIS. Therefore, opportunistic locoregional staging of breast cancer in contrast-enhanced thoracic PC-CT is feasible and could overcome limitations of DM with the potential to improve patient management.
目的:准确的局部分期对乳腺癌的有效治疗至关重要。光子计数计算机断层扫描(PC-CT)是一项新兴技术，具有高空间分辨率和描述组织中造影剂摄取的能力，使其成为乳腺癌成像的一个有前途的工具。本研究旨在通过增强胸部PC-CT确定乳腺癌局部区域分期的可行性，评估其诊断性能，并与数字乳房x线摄影(DM)进行比较。材料与方法:前瞻性纳入新诊断乳腺癌、糖尿病、胸部CT分期指征患者，为期6个月。参与者在俯卧位接受了增强胸部PC-CT和乳房磁共振成像。在对患者数据进行盲化后，2名放射科医生独立对PC-CT和DM的以下6个特征进行了评分:(1)最大肿块病变的直径，(2)皮肤/胸肌/胸壁的浸润情况，(3)肿块病变的数量，(4)有无邻近导管原位癌(DCIS)，(5)肿瘤的显著性，(6)诊断的可信度。参考标准是由一个独立的评审委员会应用TNM第八版，根据磁共振成像和所有组织病理学/临床数据的一致阅读产生的。结果:32名女性受试者(平均±SD年龄，59±13.0岁)中，PC-CT对t分类的诊断准确率高于DM (0.94 vs 0.50, P < 0.01)。PC-CT的肿瘤肿块数与参考标准的相关性高于DM (0.72 vs 0.50, P < 0.01)。我们观察到PC-CT对相邻DCIS的敏感性(分别为0.83和0.25)和特异性(分别为0.99和0.80)均显著优于DM (P < 0.04)。PC-CT的解读器可靠性κ值高于DM(平均值分别为0.88 vs 0.54;P = 0.01)。结论:光子计数ct在t分型上优于DM，对相邻DCIS的诊断准确率更高。因此，通过增强胸廓PC-CT对乳腺癌进行局部分期是可行的，可以克服DM的局限性，并有可能改善患者管理。
期刊介绍：
Investigative Radiology publishes original, peer-reviewed reports on clinical and laboratory investigations in diagnostic imaging, the diagnostic use of radioactive isotopes, computed tomography, positron emission tomography, magnetic resonance imaging, ultrasound, digital subtraction angiography, and related modalities. Emphasis is on early and timely publication. Primarily research-oriented, the journal also includes a wide variety of features of interest to clinical radiologists.
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