Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong.
Department of Radiology, Pamela Youde Nethersole Eastern Hospital, 3 Lok Man Road, Chai Wan, Hong Kong.
Cancer Imaging. 2020 Apr 6;20(1):27. doi: 10.1186/s40644-020-00303-4.
Magnetic resonance imaging (MRI) has limited accuracy in detecting pelvic lymph node (PLN) metastasis. This study aimed to examine the use of intravoxel incoherent motion (IVIM) in classifying pelvic lymph node (PLN) involvement in cervical cancer patients.
Fifty cervical cancer patients with pre-treatment magnetic resonance imaging (MRI) were examined for PLN involvement by one subspecialist and one non-subspecialist radiologist. PLN status was confirmed by positron emission tomography or histology. The tumours were then segmented by both radiologists. Kruskal-Wallis tests were used to test for differences between diffusion tumour volume (DTV), apparent diffusion coefficient (ADC), pure diffusion coefficient (D), and perfusion fraction (f) in patients with no malignant PLN involvement, those with sub-centimetre and size-significant PLN metastases. These parameters were then considered as classifiers for PLN involvement, and were compared with the accuracies of radiologists.
Twenty-one patients had PLN involvement of which 10 had sub-centimetre metastatic PLNs. DTV increased (p = 0.013) while ADC (p = 0.015), and f (p = 0.006) decreased as the nodal status progressed from no malignant involvement to sub-centimetre and then size-significant PLN metastases. In determining PLN involvement, a classification model (DTV + f) had similar accuracies (80%) as the non-subspecialist (76%; p = 0.73) and subspecialist (90%; p = 0.31). However, in identifying patients with sub-centimetre PLN metastasis, the model had higher accuracy (90%) than the non-subspecialist (30%; p = 0.01) but had similar accuracy with the subspecialist (90%, p = 1.00). Interobserver variability in tumour delineation did not significantly affect the performance of the classification model.
IVIM is useful in determining PLN involvement but the added value decreases with reader experience.
磁共振成像(MRI)在检测盆腔淋巴结(PLN)转移方面的准确性有限。本研究旨在探讨体素内不相干运动(IVIM)在分类宫颈癌患者盆腔淋巴结(PLN)受累中的应用。
对 50 例接受治疗前 MRI 检查的宫颈癌患者进行了 PLN 受累检查,由一名专科医生和一名非专科医生进行。PLN 状态通过正电子发射断层扫描或组织学证实。然后,两名放射科医生对肿瘤进行了分割。采用 Kruskal-Wallis 检验比较无恶性 PLN 受累、亚厘米和大小显著 PLN 转移患者的弥散肿瘤体积(DTV)、表观弥散系数(ADC)、纯弥散系数(D)和灌注分数(f)之间的差异。这些参数被认为是 PLN 受累的分类器,并与放射科医生的准确性进行了比较。
21 例患者有 PLN 受累,其中 10 例有亚厘米转移性 PLN。随着淋巴结状态从无恶性受累进展到亚厘米和大小显著的 PLN 转移,DTV 增加(p = 0.013),而 ADC(p = 0.015)和 f(p = 0.006)降低。在确定 PLN 受累时,分类模型(DTV + f)的准确性与非专科医生(76%;p = 0.73)和专科医生(90%;p = 0.31)相似。然而,在识别亚厘米 PLN 转移患者时,该模型的准确性高于非专科医生(90%对 30%;p = 0.01),但与专科医生的准确性相似(90%,p = 1.00)。肿瘤勾画的观察者间变异性并不显著影响分类模型的性能。
IVIM 有助于确定 PLN 受累,但随着读者经验的增加,其附加值会降低。