光子计数CT胰腺低剂量动态容积灌注扫描中单期图像对胰腺癌图像的评估价值

doi:10.16150/j.1671-2870.2025.02.006

摘要/Abstract

摘要：

目的： 评估基于光子计数CT（photon-counting computed tomography， PCCT）的胰腺低剂量动态容积灌注CT（volume perfusion computed tomography， VPCT）扫描中单期图像的图像质量及其对胰腺导管腺癌（pancreatic ductal adenocarcinoma， PDAC）进行形态学评估的可行性。 方法： 2024年4月至8月，前瞻性收集疑似PDAC的患者，术前行胰腺VPCT扫描，纳入经组织病理学确诊为PDAC的55例患者，记录并计算检查辐射剂量。分析灌注时间衰减曲线，分别基于T3D、55 keV和70 keV虚拟单能量图像（virtual monoenergetic image， VMI），提取最佳胰腺实质期和门静脉期单期图像，用于临床诊断和PDAC的形态学评估。对图像进行主观评分，并测量图像中病灶、正常胰腺实质、胰周血管及腹壁脂肪CT值，以腹壁脂肪CT值标准差为图像噪声值，计算病灶、正常胰腺实质、胰周血管信噪比以及病灶、胰周血管对比噪声比（contrast-to-noise ratio， CNR）。采用Cohen’s kappa系数评估观察者主观评价一致性，采用单因素重复测量方差分析和Friedman H检验对各组图像定量评价指标及主观评分进行比较。 结果： VPCT扫描平均有效辐射剂量为（18.0 ± 4.9） mSv。基于重建图像提取的胰腺实质期和门静脉期单期图像均符合临床诊断质量标准，图像主观质量评分均≥3分。55 keV VMI重建图像提取的胰腺实质期单期图像中，PDAC病灶CNR为11.1±4.4，T3D为9.1±3.7，70 keV VMI为8.0±3.2；门静脉期55 keV VMI中，PDAC病灶CNR为6.3±3.0，T3D为5.7±3.0，而70 keV VMI为4.9±2.7。55 keV VMI重建提取单期图像表现出最高PDAC病灶CNR（P<0.001），表现出最高正常胰腺实质和胰周血管信噪比、胰周血管CNR，以及最佳PDAC病灶对比度主观评分。55 keV VMI和T3D重建单期图像的图像噪声［胰腺实质期（8.3±2.1）比（8.2±2.1），门静脉期（8.4±2.1）比（8.3±2.2）］差异无统计学意义（P=0.599、0.683），两者的图像噪声均高于70 keV VMI（胰腺实质期7.1±1.9，门静脉期7.3±1.8）（P<0.001）。 结论： 基于PCCT低剂量胰腺动态VPCT成像方案所获得的灌注扫描单期图像，可用于PDAC成像及形态学评估，55 keV VMI重建能够进一步优化PDAC的图像质量。

关键词: X线计算机体层扫描, 光子计数CT, CT灌注成像, 图像质量, 辐射剂量

Abstract:

Objective This study aims to evaluate the image quality of single-phase images in low-dose pancreatic dynamic volume perfusion computed tomography (VPCT) scans based on photon-counting computed tomography (PCCT) and assess their feasibility for morphological evaluation of pancreatic ductal adenocarcinoma (PDAC). Methods From April to August 2024, participants suspected of PDAC were prospectively enrolled and underwent preoperative pancreatic VPCT scans. A total of 55 patients with pathologically confirmed PDAC were included, and radiation doses were recorded and calculated. Perfusion time-attenuation curves were analyzed, and optimal single-phase images of pancreatic parenchymal phase and portal venous phase were extracted from T3D, 55 keV, and 70 keV virtual monoenergetic images (VMIs) for clinical diagnosis and morphological evaluation of PDAC. Subjective scoring of images was performed, and CT values of lesions, normal pancreatic parenchyma, peripancreatic vessels, and abdominal wall fat were measured. The standard deviation of the CT value of abdominal wall fat was used as the image noise value. Signal-to-noise ratios (SNRs) of lesions, normal pancreatic parenchyma, and peripancreatic vessels, as well as contrast-to-noise ratios (CNRs) of lesions and peripancreatic vessels were calculated. Inter-observer agreement of subjective evaluations was evaluated using Cohen's kappa coefficient. One-way repeated measures ANOVA and Friedman H tests were used to compare the quantitative evaluation indicators and subjective scores among groups. Results The VPCT scanning achieved an average effective radiation dose of (18.0±4.9) mSv. The single-phase images of pancreatic parenchymal phase and portal venous phase extracted from reconstructed images met clinical diagnostic quality standards, with all subjective image quality scores above 3 points. In the single-phase images of pancreatic parenchymal phase reconstructed at 55 keV VMI, the CNR of PDAC lesions was 11.1±4.4, while for T3D it was 9.1±3.7 and for 70 keV VMI it was 8.0±3.2. In images of portal venous phase reconstructed at 55 keV VMI, the CNR of PDAC lesions was 6.3±3.0, while for T3D it was 5.7±3.0 and for 70 keV VMI, it was 4.9±2.7. Single-phase images reconstructed from 55 keV VMI showed the highest CNR of PDAC lesions (P<0.001), along with the highest SNR of normal pancreatic parenchyma and peripancreatic vessels, the highest CNR of peripancreatic vessels, and optimal subjective contrast scores of PDAC lesions. There was no significant difference in image noise between 55 keV VMI and T3D reconstructed single-phase images [parenchymal phase: (8.3±2.1) vs. (8.2±2.1), portal venous phase: (8.4±2.1) vs. (8.3±2.2)] (P=0.599, 0.683). Both had higher image noise than that of 70 keV VMI (parenchymal phase: 7.1±1.9, portal venous phase: 7.3±1.8) (P<0.001). Conclusion Single-phase images obtained from perfusion scanning PCCT-based low-dose pancreatic dynamic VPCT imaging protocols can be used for PDAC imaging and morphological evaluation. The 55 keV VMI reconstruction can further optimize the image quality of PDAC.

Key words: X-ray computed tomography, Photon-counting CT, CT perfusion imaging, Image quality, Radiation dosage

中图分类号:

R814.42

常蕊, 李纪强, 杨琰昭, 柴维敏, 严福华, 董海鹏. 光子计数CT胰腺低剂量动态容积灌注扫描中单期图像对胰腺癌图像的评估价值[J]. 诊断学理论与实践, 2025, 24(02): 155-162.

CHANG Rui, LI Jiqiang, YANG Yanzhao, CHAI Weimin, YAN Fuhua, DONG Haipeng.. Evaluation value of single-phase images from photon-counting CT-based low-dose pancreatic dynamic volume perfusion scanning for pancreatic cancer imaging[J]. Journal of Diagnostics Concepts & Practice, 2025, 24(02): 155-162.

图/表 5

表1

图1

表2

图2

表3

参考文献 18

[1]	LI H O, SUN C, XU Z D, et al. B. Low-dose whole organ CT perfusion of the pancreas: preliminary study[J]. Abdom Imaging,2014,39(1):40-7.
[2]	O'MALLEY R B, SOLOFF E V, COVELER A L, et al. Feasibility of wide detector CT perfusion imaging performed during routine staging and restaging of pancreatic ductal adenocarcinoma[J]. Abdom Radiol (NY),2021,46(5):1992-2002. doi: 10.1007/s00261-020-02786-y pmid: 33079256
[3]	O'MALLEY R B, COX D, SOLOFF E V, et al. CT perfusion as a potential biomarker for pancreatic ductal adenocarcinoma during routine staging and restaging[J]. Abdom Radiol (NY),2022,47(11):3770-3781. doi: 10.1007/s00261-022-03638-7 pmid: 35972550
[4]	PERIK T H, VAN GENUGTEN E A J, AARNTZEN E H J G, et al. Quantitative CT perfusion imaging in patients with pancreatic cancer: a systematic review[J]. Abdom Radiol (NY),2022,47(9):3101-3117.
[5]	SKORNITZKE S, VATS N, MAYER P, et al. Pancreatic CT perfusion: quantitative meta-analysis of disease discrimination, protocol development, and effect of CT parameters[J]. Insights Imaging,2023,14(1):132.
[6]	HAMDY A, ICHIKAWA Y, TOYOMASU Y, et al. Perfusion CT to assess response to neoadjuvant chemotherapy and radiation therapy in pancreatic ductal adenocarcinoma: initial experience[J]. Radiology,2019,292(3):628-635. doi: 10.1148/radiol.2019182561 pmid: 31287389
[7]	WANG X, HENZLER T, GAWLITZA J, et al. Image qua-lity of mean temporal arterial and mean temporal portal venous phase images calculated from low dose dynamic volume perfusion CT datasets in patients with hepatocellular carcinoma and pancreatic cancer[J]. Eur J Radiol,2016,85(11):2104-2110.
[8]	WILLEMINK M J, PERSSON M, POURMORTEZA A, et al. Photon-counting CT: technical principles and clinical prospects[J]. Radiology,2018,289:293-312 doi: 10.1148/radiol.2018172656 pmid: 30179101
[9]	FLOHR T, SCHMIDT B. Technical basics and clinical benefits of photon-counting CT[J]. Invest Radiol,2023,58:441-450 doi: 10.1097/RLI.0000000000000980 pmid: 37185302
[10]	LI J, CHEN X Y, XU K, et al. Detection of insulinoma: one-stop pancreatic perfusion CT with calculated mean temporal images can replace the combination of bi-phasic plus perfusion scan[J]. Eur Radiol,2020,30(8):4164-4174. doi: 10.1007/s00330-020-06657-4 pmid: 32189051
[11]	MICHALSKI C W, ERKAN M, HUSER N, et al. Resection of primary pancreatic cancer and liver metastasis: a systematic review[J]. Dig Surg,2008,25(6):473–480
[12]	KLEIN F, PUHL G, GUCKELBERGER O, et al. The impact of simultaneous liver resection for occult liver metastases of pancreatic adenocarcinoma[J]. Gastroenterol Res Pract,2012(6):939-950
[13]	LENG S, BRUESEWITZ M, TAO S, et al. Photon-coun-ting detector CT: system design and clinical applications of an emerging technology[J]. Radiographics,2019,39(3):729-743.
[14]	KIM J, MABUD T, HUANG C, et al. Inter-reader agreement of pancreatic adenocarcinoma resectability assessment with photon counting versus energy integrating detector CT[J]. Abdom Radiol (NY),2024,49(9):3149-3157. doi: 10.1007/s00261-024-04298-5 pmid: 38630314
[15]	谢环环, 林晓珠, 王晴柔, 等. CT能谱成像在胰腺癌病灶显示中的应用价值[J].实用放射学杂志,2017,33(5):750-753.
	XIE H H, LIN X Z, WANG Q R, et al. Value of CT spectral imaging in demonstration of pancreatic ductal adenocarcinoma[J]. J Pract Radiol, 2017, 33(5):750-753.
[16]	BEER L, TOEPKER M, BA-SALAMAH A, et al. Objective and subjective comparison of virtual monoenergetic vs. polychromatic images in patients with pancreatic ductal adenocarcinoma[J]. Eur Radiol,2019,29(7):3617-3625.
[17]	杨琰昭, 常蕊, 王晴柔, 等. 双层探测器光谱CT虚拟单能量图像在胰腺导管腺癌术前评估中的优化研究[J]. 上海交通大学学报:医学版, 2022, 42(9):1323-1328.
	YANG Y Z, CHANG R, WANG Q R, et al. Optimized study of virtual monoenergetic images derived from a dual-layer spectral detector CT in the preoperative evalua-tion of pancreatic ductal adenocarcinoma[J]. J Shanghai Jiaotong Univ(Med Sci),2022,(9):1323-1328
[18]	DECKER J A, BECKER J, HARTING M, et al. Optimal conspicuity of pancreatic ductal adenocarcinoma in virtual monochromatic imaging reconstructions on a photon-counting detector CT: comparison to conventional MDCT[J]. Abdom Radiol (NY),2024,49(1):103-116.

Acquisition parameters Parameter
Scan mode	PCCT（NAEOTOM Alpha）
Tube voltage (kVp)	90
Image quality (IQ) level	80
Tube current	Care Dose 4D
Spiral pitch	1.0
Rotation time（s）	0.25
Collimation（mm）	144 × 0.4
Total acquisition time（s）	47（began at 7）
Z-axis coverage ^*（cm）	16 - 25
Number of scan cycles ^†	17 - 23
Contrast Volume（mL）	40
Iodine concentration（mg/mL）	400
Flow rate（mL/s）	4
Reconstruction Parameters
Quantum iterative reconstruction	QIR 4
Reconstruction filter kernel	Br 40
Slice thickness and increment (mm)	1 / 1
Image reconstruction	55 keV / 70 keV / T3D

Parameter	Value
Sex	Male 34，Female 21
Age（y）	66.4 ± 6.6 (49-78)
Weight（kg）	62.5 ± 10.2 (40-83)
Height（m）	1.66 ± 0.90 (1.45-1.86)
BMI（kg/m²）	22.7 ± 3.2 (17.6-32.9)
Z-axis range（cm）	18.7 ± 2.2 (16-25)
No. of scan cycles	20 ± 2.0 (17-23)
CTDIvol（mGy）	58.7 ± 14.6 (28.3-95.4)
DLP（mGy · cm）	1199.4 ± 328.8 (472.5-1 943.1)
ED（mSv）	18.0 ± 4.9 (7.1-29.2)

Item	T3D	70 keV	55 keV	P^*	P^†	P^‡	P^§
Pancreatic parenchymal phase
Image noise (HU)	8.2 ± 2.1	7.1 ± 1.9	8.3 ± 2.1	< 0.001	< 0.001	0.599	< 0.001
SNR parenchyma	16.3 ± 5.9	16.7 ± 5.0	18.8 ± 6.4	< 0.001	0.002	< 0.001	< 0.001
SNR vessel	35.9 ± 15.9	36.1 ± 12.5	46.8 ± 19.8	< 0.001	< 0.001	< 0.001	< 0.001
SNR lesion	7.2 ± 1.8	7.5 ± 2.1	7.6 ± 2.0	0.036	0.062	0.003	0.505
CNR vessel	27.0 ± 17.7	25.7 ± 16.2	36.9 ± 23.0	< 0.001	< 0.001	< 0.001	< 0.001
CNR lesion	9.1 ± 3.7	8.0 ± 3.2	11.1 ± 4.4	< 0.001	< 0.001	< 0.001	< 0.001
Portal venous phase
Image noise (HU)	8.3 ± 2.2	7.3 ± 1.8	8.4 ± 2.1	< 0.001	< 0.001	0.683	< 0.001
SNR parenchyma	12.4 ± 3.2	11.8 ± 3.2	13.3 ± 3.6	< 0.001	0.033	< 0.001	< 0.001
SNR vessel	20.9 ± 6.3	18.5 ± 5.0	23.3 ± 7.5	< 0.001	< 0.001	< 0.001	< 0.001
SNR lesion	6.5 ± 2.0	6.7 ± 1.9	6.9 ± 2.2	0.003	0.009	< 0.001	0.231
CNR vessel	10.6 ± 4.4	9.0 ± 3.7	13.5 ± 5.7	< 0.001	< 0.001	< 0.001	< 0.001
CNR lesion	5.7 ± 3.0	4.9 ± 2.7	6.3 ± 3.0	< 0.001	< 0.001	< 0.001	< 0.001