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分形分析提高胰腺导管腺癌 CT 肿瘤大小测量的准确性:与大体病理和多参数 MRI 的比较。

Fractal analysis improves tumour size measurement on computed tomography in pancreatic ductal adenocarcinoma: comparison with gross pathology and multi-parametric MRI.

机构信息

Department of Radiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany.

Groupe Hospitalier Paris Saint-Joseph, 185 rue Raymond Losserand, 75014, Paris, France.

出版信息

Eur Radiol. 2022 Aug;32(8):5053-5063. doi: 10.1007/s00330-022-08631-8. Epub 2022 Feb 24.

Abstract

OBJECTIVES

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 (Δdiameter = -5.7 mm), while realistic diameter measurements were obtained from FD maps (Δdiameter = 0.6 mm) and mpMRI (Δdiameter = -0.9 mm), with excellent correlation between the two (R = 0.88). In the validation cohort, CT also systematically underestimated tumour size in comparison to mpMRI (Δdiameter = -10.6 mm, Δvolume = -10.2 mL), especially in larger tumours. In contrast, FD map measurements agreed excellently with mpMRI (Δdiameter = +1.5 mm, Δvolume = -0.6 mL). Quantitative perfusion chaos was significantly (p = 0.001) higher in the tumour rim (FD = 4.43) compared to the core (FD = 4.37) and remote pancreas (FD = 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.

KEY POINTS

• 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.

摘要

目的

肿瘤大小的测量对于胰腺导管腺癌(PDA)的分期和分层至关重要。然而,由于肿瘤边缘显示不足,计算机断层扫描(CT)经常低估肿瘤大小。CT 衍生的分形维数(FD)图可能有助于可视化灌注混沌,从而实现更真实的大小测量。

方法

在 46 名经组织学证实的 PDA 患者中,我们比较了常规多期 CT 扫描、CT 衍生 FD 图、多参数磁共振成像(mpMRI)以及在有条件的情况下切除标本的大体病理学中的肿瘤大小测量值。在一个由 10 名患者组成的发现队列中,大体病理学可作为直径测量的参考。其余 36 名患者组成了一个单独的验证队列,以 mpMRI 作为直径和体积的参考。

结果

所有纳入肿瘤的中位 RECIST 直径为 40mm(范围:18-82mm)。在发现队列中,我们发现 CT 与大体病理学相比,肿瘤直径存在显著(p=0.03)低估(Δ直径=-5.7mm),而 FD 图(Δ直径=0.6mm)和 mpMRI(Δ直径=-0.9mm)可以获得更真实的直径测量值,两者之间具有良好的相关性(R=0.88)。在验证队列中,与 mpMRI 相比,CT 也系统地低估了肿瘤大小(Δ直径=-10.6mm,Δ体积=-10.2mL),尤其是在较大的肿瘤中。相比之下,FD 图测量值与 mpMRI 非常吻合(Δ直径=+1.5mm,Δ体积=-0.6mL)。肿瘤边缘的定量灌注混沌明显(p=0.001)高于肿瘤核心(FD=4.37)和远侧胰腺(FD=4.28)。

结论

在 PDA 中,分形分析可视化肿瘤边缘的灌注混沌,并与大体病理学和 mpMRI 相比,改善 CT 上的肿瘤大小测量,从而弥补常规 CT 引起的大小低估。

关键要点

  • 在胰腺腺癌中,基于 CT 的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)图,可以使用大体病理学或多参数 MRI 作为参考标准进行更可靠和与大小无关的测量。

  • FD 量化了灌注混沌——潜在的病理生理原理——并可以将更混乱的肿瘤边缘与肿瘤核心和相邻的非肿瘤胰腺组织区分开来。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a0b/9279218/978e1a999700/330_2022_8631_Fig1_HTML.jpg

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