Research progress of dual<b>-</b>layer spectral detector CT in imaging diagnosis of gastric cancer_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

LIAO Tianyi ^1,2 , LIU Shuo ^1,2 , ZHANG Xiang ^1,2 ,  CAI Hui ^1,2,3

1. The First Clinical Medical College, Lanzhou University, Lanzhou 730000, P. R. China;
2. Key Laboratory of Tumor Molecular Diagnosis and Precision Medicine in Surgery of Gansu Province, Gansu Provincial People’s Hospital, Lanzhou 730000, P. R. China;
3. Department of General Surgery, Gansu Provincial People’s Hospital, Lanzhou 730000, P. R. China;

Corresponding author：

CAI Hui, Email: caialonteam@163.com

Keywords：

dual-layer spectral detector CT; gastric cancer; imaging diagnosis

DOI：

10.7507/1007-9424.202305023

Video：

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Objective To summarize the advantages of double-layer detector spectral CT (DLCT) as compared with conventional CT in disease diagnosis and its research status in the diagnosis of gastric cancer. Method The literature relevant research was summarized, including the clinical application of DLCT and its clinical research in the diagnosis of gastric cancer. Results The image quality of DLCT was better than that of conventional CT examination. Its virtual non-contrast could display gastric cancer lesions and evaluate lymph node metastasis. The number of CT scans of patient was reduced by DLCT, correspondingly the radiation dose received by patients was reduced, and the examination time of patient was shortened. The iodine uptake in the tissues could visually be observed by the iodine concentration map in the DLCT and be quantitatively analyzed, which could provide a new option for noninvasive evaluation of angiogenesis in the gastric cancer. The DLCT scanning provided a material decomposition image, the different iodine absorption of normal gastric mucosa and gastric cancer could be reflected by the material decomposition image. The enhancement degree and blood supply of lesions could be effectively reflected by quantitative measurement of iodine concentration and thus the benign and malignant changes of the gastric diseases were effectively identified. The DLCT could distinguish the structure of the gastric wall, which could show the depth of invasion of malignant gastric lesions to the gastric wall and whether the adjacent tissues and organs were involved or not. Through the homology analysis of abnormal lymph nodes and suspicious metastases in the abdominal cavity through the related parameters of the DLCT could more accurately determine the clinical TNM stage of the gastric cancer before surgery. Conclusions In recent years, DLCT has shown a better morphological diagnostic efficiency than conventional CT in clinical application. Its virtual non-contrast, iodine concentration, effective atomic number, and other parameters characteristics make it show obvious advantages in gastric cancer, such as evaluation of angiogenesis of gastric cancer, differentiation of benign and malignant gastric diseases, clinical staging of gastric cancer, and other applications. In future, with more usable parameters research and continuous accumulation of clinical application about DLCT in clinic, which can better serve clinical work.

Citation： LIAO Tianyi, LIU Shuo, ZHANG Xiang, CAI Hui. Research progress of dual-layer spectral detector CT in imaging diagnosis of gastric cancer. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2023, 30(9): 1124-1129. doi: 10.7507/1007-9424.202305023 Copy

1.	Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2021, 71(3): 209-249.
2.	Machlowska J, Baj J, Sitarz M, et al. Gastric cancer: epidemiology, risk factors, classification, genomic characteristics and treatment strategies. Int J Mol Sci, 2020, 21(11): 4012. doi: 10.3390/ijms21114012.
3.	中国抗癌协会胃癌专业委员会影像协作组, 中华放射学会腹部学组. 胃癌影像学检查与诊断规范化流程专家共识(2022版). 中华胃肠外科杂志, 2022, 25(10): 859-868.
4.	Große Hokamp N, Maintz D, Shapira N, et al. Technical background of a novel detector-based approach to dual-energy computed tomography. Diagn Interv Radiol, 2020, 26(1): 68-71.
5.	Rassouli N, Etesami M, Dhanantwari A, et al. Detector-based spectral CT with a novel dual-layer technology: principles and applications. Insights Imaging, 2017, 8(6): 589-598.
6.	Fulton N, Rajiah P. Abdominal applications of a novel detector-based spectral CT. Curr Probl Diagn Radiol, 2018, 47(2): 110-118.
7.	Kalisz K, Rassouli N, Dhanantwari A, et al. Noise characteristics of virtual monoenergetic images from a novel detector-based spectral CT scanner. Eur J Radiol, 2018, 98: 118-125.
8.	Lennartz S, Große Hokamp N, Abdullayev N, et al. Diagnostic value of spectral reconstructions in detecting incidental skeletal muscle metastases in CT staging examinations. Cancer Imaging, 2019, 19(1): 50. doi: 10.1186/s40644-019-0235-3.
9.	Laukamp KR, Große Hokamp N, Alabar O, et al. Metal artifacts from sternal wires: evaluation of virtual monoenergetic images from spectral-detector CT for artifact reduction. Clin Imaging, 2020, 60(2): 249-256.
10.	Popnoe DO, Ng CS, Zhou S, et al. Comparison of virtual to true unenhanced abdominal computed tomography images acquired using rapid kV-switching dual energy imaging. PLoS One, 2020, 15(9): e0238582. doi: 10.1371/journal.pone.0238582.
11.	Luo N, Li W, Xie J, et al. Preoperative normalized iodine concentration derived from spectral CT is correlated with early recurrence of hepatocellular carcinoma after curative resection. Eur Radiol, 2021, 31(4): 1872-1882.
12.	袁源, 郎宁, 袁慧书. CT能谱曲线在脊柱转移瘤和感染性病变中的鉴别诊断价值. 北京大学学报(医学版), 2021, 53(1): 183-187.
13.	Li K, Li Y, Qi Z, et al. Quantitative lung perfusion blood volume using dual energy CT-based effective atomic number (Z_eff ) imaging. Med Phys, 2021, 48(11): 6658-6672.
14.	Greffier J, Viry A, Barbotteau Y, et al. Phantom task-based image quality assessment of three generations of rapid kV-switching dual-energy CT systems on virtual monoenergetic images. Med Phys, 2022, 49(4): 2233-2244.
15.	Lartaud PJ, Hallé D, Schleef A, et al. Spectral augmentation for heart chambers segmentation on conventional contrasted and unenhanced CT scans: an in-depth study. Int J Comput Assist Radiol Surg, 2021, 16(10): 1699-1709.
16.	Lennartz S, Pisuchpen N, Parakh A, et al. Virtual unenhanced images: qualitative and quantitative comparison between different dual-energy CT scanners in a patient and phantom study. Invest Radiol, 2022, 57(1): 52-61.
17.	Zhang PP, Choi HH, Ohliger MA. Detection of fatty liver using virtual non-contrast dual-energy CT. Abdom Radiol (NY), 2022, 47(6): 2046-2056.
18.	Riederer I, Fingerle AA, Zimmer C, et al. Potential of dual-layer spectral CT for the differentiation between hemorrhage and iodinated contrast medium in the brain after endovascular treatment of ischemic stroke patients. Clin Imaging, 2021, 79: 158-164.
19.	Du Y, Zhang JY, Gong LP, et al. Hypoxia-induced EBV-circLMP2A promotes angiogenesis in EBV-associated gastric carcinoma through the KHSRP/VHL/HIF1α/VEGFA pathway. Cancer Lett, 2022, 526: 259-272.
20.	Li Q, Cui D, Feng Y, et al. Correlation between microvessel density (MVD) and multi-spiral CT (MSCT) perfusion parameters of esophageal cancer lesions and the diagnostic value of combined CtBP2 and P16INK4A. J Gastrointest Oncol, 2021, 12(3): 981-990.
21.	姚晋, 陈卉娇, 黄娟. 胃窦癌64层螺旋CT灌注成像特点及其与肿瘤血管生成的关系. 中国普外基础与临床杂志, 2010, 17(7): 755-759.
22.	Chen XH, Ren K, Liang P, et al. Spectral computed tomography in advanced gastric cancer: can iodine concentration non-invasively assess angiogenesis?. World J Gastroenterol, 2017, 23(9): 1666-1675.
23.	Wang N, Chang LL. Maspin suppresses cell invasion and migration in gastric cancer through inhibiting EMT and angiogenesis via ITGB1/FAK pathway. Hum Cell, 2020, 33(3): 663-675.
24.	Banks M, Graham D, Jansen M, et al. British Society of Gastroenterology guidelines on the diagnosis and management of patients at risk of gastric adenocarcinoma. Gut, 2019, 68(9): 1545-1575.
25.	Meng X, Ni C, Shen Y, et al. Differentiating malignant from benign gastric mucosal lesions with quantitative analysis in dual energy spectral computed tomography: initial experience. Medicine (Baltimore), 2017, 96(2): e5878. doi: 10.1097/MD.0000000000005878.
26.	Wang Y, Liu W, Yu Y, et al. Potential value of CT radiomics in the distinction of intestinal-type gastric adenocarcinomas. Eur Radiol, 2020, 30(5): 2934-2944.
27.	Song Z, Li Q, Zhang D, et al. Nomogram based on spectral CT quantitative parameters and typical radiological features for distinguishing benign from malignant thyroid micro-nodules. Cancer Imaging, 2023, 23(1): 13. doi: 10.1186/s40644-023-00525-2.
28.	Li Q, Song Z, Zhang D, et al. Diagnostic accuracy of dual-energy computed tomography-based nomogram for differentiating papillary thyroid microcarcinomas from micronodular goiters. Quant Imaging Med Surg, 2023, 13(6): 3428-3440.
29.	Ajani JA, D'Amico TA, Bentrem DJ, et al. Gastric cancer, version 2. 2022, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw, 2022, 20(2): 167-192.
30.	Liu JJ, Liu W, Jin ZY, et al. Improved visualization of gastric cancer and increased diagnostic performance in lesion depiction and depth identification using monoenergetic reconstructions from a novel dual-layer spectral detector CT. Acad Radiol, 2020, 27(6): e140-e147. doi :10.1016/j.acra.2019.09.004.
31.	孙东东, 赵致平, 侯宗贤. 宝石CT前处置流程的优化对胃癌术前T分期的应用效果分析. 甘肃科技, 2023, 39(3): 104-106, 111.
32.	邢静静, 柴亚如, 高剑波, 等. 能谱CT在鉴别T3及T4a期胃癌中的应用价值. 中华胃肠外科杂志, 2016, 19(5): 580-584.
33.	Pan Z, Pang L, Ding B, et al. Gastric cancer staging with dual energy spectral CT imaging. PLoS One, 2013, 8(2): e53651. doi: 10.1371/journal.pone.0053651.
34.	胡国权, 郝建成, 范元军, 等. 多层螺旋CT对可切除性胃癌转移性淋巴结及N分期的诊断价值研究. 中国普外基础与临床杂志, 2022, 29(4): 527-531.
35.	Wang Y, Liu W, Yu Y, et al. CT radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer. Eur Radiol, 2020, 30(2): 976-986.
36.	张维汉, 胡建昆. 胃癌腹膜转移诊治现状. 中华胃肠外科杂志, 2021, 24(3): 204-207.
37.	刘静, 黄宝生, 张丽萍等. 能谱CT定量参数对进展期胃癌cM分期准确性的应用研究. 河西学院学报, 2023, 39(2): 38-45.
38.	Zhai Z, Zhu ZY, Zhang Y, et al. Prognostic significance of Borrmann type combined with vessel invasion status in advanced gastric cancer. World J Gastrointest Oncol, 2020, 12(9): 992-1004.
39.	Ren T, Zhang W, Li S, et al. Combination of clinical and spectral-CT parameters for predicting lymphovascular and perineural invasion in gastric cancer. Diagn Interv Imaging, 2022, 103(12): 584-593.

1. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2021, 71(3): 209-249.
2. Machlowska J, Baj J, Sitarz M, et al. Gastric cancer: epidemiology, risk factors, classification, genomic characteristics and treatment strategies. Int J Mol Sci, 2020, 21(11): 4012. doi: 10.3390/ijms21114012.
3. 中国抗癌协会胃癌专业委员会影像协作组, 中华放射学会腹部学组. 胃癌影像学检查与诊断规范化流程专家共识(2022版). 中华胃肠外科杂志, 2022, 25(10): 859-868.
4. Große Hokamp N, Maintz D, Shapira N, et al. Technical background of a novel detector-based approach to dual-energy computed tomography. Diagn Interv Radiol, 2020, 26(1): 68-71.
5. Rassouli N, Etesami M, Dhanantwari A, et al. Detector-based spectral CT with a novel dual-layer technology: principles and applications. Insights Imaging, 2017, 8(6): 589-598.
6. Fulton N, Rajiah P. Abdominal applications of a novel detector-based spectral CT. Curr Probl Diagn Radiol, 2018, 47(2): 110-118.
7. Kalisz K, Rassouli N, Dhanantwari A, et al. Noise characteristics of virtual monoenergetic images from a novel detector-based spectral CT scanner. Eur J Radiol, 2018, 98: 118-125.
8. Lennartz S, Große Hokamp N, Abdullayev N, et al. Diagnostic value of spectral reconstructions in detecting incidental skeletal muscle metastases in CT staging examinations. Cancer Imaging, 2019, 19(1): 50. doi: 10.1186/s40644-019-0235-3.
9. Laukamp KR, Große Hokamp N, Alabar O, et al. Metal artifacts from sternal wires: evaluation of virtual monoenergetic images from spectral-detector CT for artifact reduction. Clin Imaging, 2020, 60(2): 249-256.
10. Popnoe DO, Ng CS, Zhou S, et al. Comparison of virtual to true unenhanced abdominal computed tomography images acquired using rapid kV-switching dual energy imaging. PLoS One, 2020, 15(9): e0238582. doi: 10.1371/journal.pone.0238582.
11. Luo N, Li W, Xie J, et al. Preoperative normalized iodine concentration derived from spectral CT is correlated with early recurrence of hepatocellular carcinoma after curative resection. Eur Radiol, 2021, 31(4): 1872-1882.
12. 袁源, 郎宁, 袁慧书. CT能谱曲线在脊柱转移瘤和感染性病变中的鉴别诊断价值. 北京大学学报(医学版), 2021, 53(1): 183-187.
13. Li K, Li Y, Qi Z, et al. Quantitative lung perfusion blood volume using dual energy CT-based effective atomic number (Z_eff ) imaging. Med Phys, 2021, 48(11): 6658-6672.
14. Greffier J, Viry A, Barbotteau Y, et al. Phantom task-based image quality assessment of three generations of rapid kV-switching dual-energy CT systems on virtual monoenergetic images. Med Phys, 2022, 49(4): 2233-2244.
15. Lartaud PJ, Hallé D, Schleef A, et al. Spectral augmentation for heart chambers segmentation on conventional contrasted and unenhanced CT scans: an in-depth study. Int J Comput Assist Radiol Surg, 2021, 16(10): 1699-1709.
16. Lennartz S, Pisuchpen N, Parakh A, et al. Virtual unenhanced images: qualitative and quantitative comparison between different dual-energy CT scanners in a patient and phantom study. Invest Radiol, 2022, 57(1): 52-61.
17. Zhang PP, Choi HH, Ohliger MA. Detection of fatty liver using virtual non-contrast dual-energy CT. Abdom Radiol (NY), 2022, 47(6): 2046-2056.
18. Riederer I, Fingerle AA, Zimmer C, et al. Potential of dual-layer spectral CT for the differentiation between hemorrhage and iodinated contrast medium in the brain after endovascular treatment of ischemic stroke patients. Clin Imaging, 2021, 79: 158-164.
19. Du Y, Zhang JY, Gong LP, et al. Hypoxia-induced EBV-circLMP2A promotes angiogenesis in EBV-associated gastric carcinoma through the KHSRP/VHL/HIF1α/VEGFA pathway. Cancer Lett, 2022, 526: 259-272.
20. Li Q, Cui D, Feng Y, et al. Correlation between microvessel density (MVD) and multi-spiral CT (MSCT) perfusion parameters of esophageal cancer lesions and the diagnostic value of combined CtBP2 and P16INK4A. J Gastrointest Oncol, 2021, 12(3): 981-990.
21. 姚晋, 陈卉娇, 黄娟. 胃窦癌64层螺旋CT灌注成像特点及其与肿瘤血管生成的关系. 中国普外基础与临床杂志, 2010, 17(7): 755-759.
22. Chen XH, Ren K, Liang P, et al. Spectral computed tomography in advanced gastric cancer: can iodine concentration non-invasively assess angiogenesis?. World J Gastroenterol, 2017, 23(9): 1666-1675.
23. Wang N, Chang LL. Maspin suppresses cell invasion and migration in gastric cancer through inhibiting EMT and angiogenesis via ITGB1/FAK pathway. Hum Cell, 2020, 33(3): 663-675.
24. Banks M, Graham D, Jansen M, et al. British Society of Gastroenterology guidelines on the diagnosis and management of patients at risk of gastric adenocarcinoma. Gut, 2019, 68(9): 1545-1575.
25. Meng X, Ni C, Shen Y, et al. Differentiating malignant from benign gastric mucosal lesions with quantitative analysis in dual energy spectral computed tomography: initial experience. Medicine (Baltimore), 2017, 96(2): e5878. doi: 10.1097/MD.0000000000005878.
26. Wang Y, Liu W, Yu Y, et al. Potential value of CT radiomics in the distinction of intestinal-type gastric adenocarcinomas. Eur Radiol, 2020, 30(5): 2934-2944.
27. Song Z, Li Q, Zhang D, et al. Nomogram based on spectral CT quantitative parameters and typical radiological features for distinguishing benign from malignant thyroid micro-nodules. Cancer Imaging, 2023, 23(1): 13. doi: 10.1186/s40644-023-00525-2.
28. Li Q, Song Z, Zhang D, et al. Diagnostic accuracy of dual-energy computed tomography-based nomogram for differentiating papillary thyroid microcarcinomas from micronodular goiters. Quant Imaging Med Surg, 2023, 13(6): 3428-3440.
29. Ajani JA, D'Amico TA, Bentrem DJ, et al. Gastric cancer, version 2. 2022, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw, 2022, 20(2): 167-192.
30. Liu JJ, Liu W, Jin ZY, et al. Improved visualization of gastric cancer and increased diagnostic performance in lesion depiction and depth identification using monoenergetic reconstructions from a novel dual-layer spectral detector CT. Acad Radiol, 2020, 27(6): e140-e147. doi :10.1016/j.acra.2019.09.004.
31. 孙东东, 赵致平, 侯宗贤. 宝石CT前处置流程的优化对胃癌术前T分期的应用效果分析. 甘肃科技, 2023, 39(3): 104-106, 111.
32. 邢静静, 柴亚如, 高剑波, 等. 能谱CT在鉴别T3及T4a期胃癌中的应用价值. 中华胃肠外科杂志, 2016, 19(5): 580-584.
33. Pan Z, Pang L, Ding B, et al. Gastric cancer staging with dual energy spectral CT imaging. PLoS One, 2013, 8(2): e53651. doi: 10.1371/journal.pone.0053651.
34. 胡国权, 郝建成, 范元军, 等. 多层螺旋CT对可切除性胃癌转移性淋巴结及N分期的诊断价值研究. 中国普外基础与临床杂志, 2022, 29(4): 527-531.
35. Wang Y, Liu W, Yu Y, et al. CT radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer. Eur Radiol, 2020, 30(2): 976-986.
36. 张维汉, 胡建昆. 胃癌腹膜转移诊治现状. 中华胃肠外科杂志, 2021, 24(3): 204-207.
37. 刘静, 黄宝生, 张丽萍等. 能谱CT定量参数对进展期胃癌cM分期准确性的应用研究. 河西学院学报, 2023, 39(2): 38-45.
38. Zhai Z, Zhu ZY, Zhang Y, et al. Prognostic significance of Borrmann type combined with vessel invasion status in advanced gastric cancer. World J Gastrointest Oncol, 2020, 12(9): 992-1004.
39. Ren T, Zhang W, Li S, et al. Combination of clinical and spectral-CT parameters for predicting lymphovascular and perineural invasion in gastric cancer. Diagn Interv Imaging, 2022, 103(12): 584-593.

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Research progress of dual-layer spectral detector CT in imaging diagnosis of gastric cancer

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