目的:肿瘤大小测量对于胰腺导管腺癌(PDA)患者的分期和分层至关重要。然而,由于对肿瘤边缘的描述不足,计算机断层扫描(CT)经常低估肿瘤的大小。CT衍生的分形维数(FD)图可能有助于可视化灌注混沌,从而允许更真实的尺寸测量。
方法:在46例经组织学证实的PDA患者中,我们比较了常规多相CT扫描中的肿瘤大小测量值,CT衍生的FD图,多参数磁共振成像(MPMRI),and,如果可用,切除标本的大体病理。在10名患者的发现队列中,大体病理学可作为直径测量的参考。其余36例患者组成一个单独的验证队列,以mpMRI作为直径和体积的参考。
结果:所有纳入肿瘤的RECIST直径中位数为40mm(范围:18-82mm)。在发现队列中,我们发现,与大体病理(Δdiameter3D=-5.7mm)相比,CT上的肿瘤直径明显低估(p=0.03),而实际的直径测量是从FD图(Δdiameter3D=0.6mm)和mpMRI(Δdiameter3D=-0.9mm)获得的,两者之间有很好的相关性(R2=0.88)。在验证队列中,与mpMRI相比,CT还系统地低估了肿瘤大小(Δdiameter3D=-10.6mm,Δ体积=-10.2mL),尤其是在较大的肿瘤中。相比之下,FD图测量与mpMRI(Δdiameter3D=+1.5mm,Δ体积=-0.6mL)。与核心(FDcore=4.37)和远端胰腺(FDpanc=4.28)相比,肿瘤边缘(FDrim=4.43)的定量灌注混沌显着(p=0.001)更高。
结论:在PDA中,与大体病理学和MPMRI相比,分形分析可以可视化肿瘤边缘的灌注混沌,并改善CT上的尺寸测量,从而补偿常规CT的尺寸低估。
结论:•基于CT的胰腺癌肿瘤大小测量系统地低估了肿瘤直径(Δ直径=-10.6mm)和体积(Δ体积=-10.2mL),尤其是在较大的肿瘤中。•分形分析提供了分形维数(FD)的地图,这使得使用大体病理学或多参数MRI作为参考标准进行更可靠和尺寸无关的测量。•FD量化灌注混沌-潜在的病理生理学原理-并且可以将更混乱的肿瘤边缘与肿瘤核心和邻近的非肿瘤胰腺组织分开。
OBJECTIVE: Tumour size measurement is pivotal for staging and stratifying patients with pancreatic ductal adenocarcinoma (PDA). However, computed tomography (CT) frequently underestimates tumour size due to insufficient depiction of the tumour rim. CT-derived fractal dimension (FD) maps might help to visualise perfusion chaos, thus allowing more realistic size measurement.
METHODS: In 46 patients with histology-proven PDA, we compared tumour size measurements in routine multiphasic CT scans, CT-derived FD maps, multi-parametric magnetic resonance imaging (mpMRI), and, where available, gross pathology of resected specimens. Gross pathology was available as reference for diameter measurement in a discovery cohort of 10 patients. The remaining 36 patients constituted a separate validation cohort with mpMRI as reference for diameter and volume.
RESULTS: Median RECIST diameter of all included tumours was 40 mm (range: 18-82 mm). In the discovery cohort, we found significant (p = 0.03) underestimation of tumour diameter on CT compared with gross pathology (Δdiameter3D = -5.7 mm), while realistic diameter measurements were obtained from FD maps (Δdiameter3D = 0.6 mm) and mpMRI (Δdiameter3D = -0.9 mm), with excellent correlation between the two (R2 = 0.88). In the validation cohort, CT also systematically underestimated tumour size in comparison to mpMRI (Δdiameter3D = -10.6 mm, Δvolume = -10.2 mL), especially in larger tumours. In contrast, FD map measurements agreed excellently with mpMRI (Δdiameter3D = +1.5 mm, Δvolume = -0.6 mL). Quantitative perfusion chaos was significantly (p = 0.001) higher in the tumour rim (FDrim = 4.43) compared to the core (FDcore = 4.37) and remote pancreas (FDpancreas = 4.28).
CONCLUSIONS: In PDA, fractal analysis visualises perfusion chaos in the tumour rim and improves size measurement on CT in comparison to gross pathology and mpMRI, thus compensating for size underestimation from routine CT.
CONCLUSIONS: • CT-based measurement of tumour size in pancreatic adenocarcinoma systematically underestimates both tumour diameter (Δdiameter = -10.6 mm) and volume (Δvolume = -10.2 mL), especially in larger tumours. • Fractal analysis provides maps of the fractal dimension (FD), which enable a more reliable and size-independent measurement using gross pathology or multi-parametric MRI as reference standards. • FD quantifies perfusion chaos-the underlying pathophysiological principle-and can separate the more chaotic tumour rim from the tumour core and adjacent non-tumourous pancreas tissue.