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

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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.	中國抗癌協會胃癌專業委員會影像協作組, 中華放射學會腹部學組. 胃癌影像學檢查與診斷規范化流程專家共識(2022版). 中華胃腸外科雜志, 2022, 25(10): 859-868.
4.	Gro?e 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, Gro?e 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, Gro?e 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, 郎寧, 袁慧書. CT能譜曲線在脊柱轉移瘤和感染性病變中的鑒別診斷價值. 北京大學學報(醫學版), 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.	姚晉, 陳卉嬌, 黃娟. 胃竇癌64層螺旋CT灌注成像特點及其與腫瘤血管生成的關系. 中國普外基礎與臨床雜志, 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.	孫東東, 趙致平, 侯宗賢. 寶石CT前處置流程的優化對胃癌術前T分期的應用效果分析. 甘肅科技, 2023, 39(3): 104-106, 111.
32.	邢靜靜, 柴亞如, 高劍波, 等. 能譜CT在鑒別T3及T4a期胃癌中的應用價值. 中華胃腸外科雜志, 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.	胡國權, 郝建成, 范元軍, 等. 多層螺旋CT對可切除性胃癌轉移性淋巴結及N分期的診斷價值研究. 中國普外基礎與臨床雜志, 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.	張維漢, 胡建昆. 胃癌腹膜轉移診治現狀. 中華胃腸外科雜志, 2021, 24(3): 204-207.
37.	劉靜, 黃寶生, 張麗萍等. 能譜CT定量參數對進展期胃癌cM分期準確性的應用研究. 河西學院學報, 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. 中國抗癌協會胃癌專業委員會影像協作組, 中華放射學會腹部學組. 胃癌影像學檢查與診斷規范化流程專家共識(2022版). 中華胃腸外科雜志, 2022, 25(10): 859-868.
4. Gro?e 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, Gro?e 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, Gro?e 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, 郎寧, 袁慧書. CT能譜曲線在脊柱轉移瘤和感染性病變中的鑒別診斷價值. 北京大學學報(醫學版), 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. 姚晉, 陳卉嬌, 黃娟. 胃竇癌64層螺旋CT灌注成像特點及其與腫瘤血管生成的關系. 中國普外基礎與臨床雜志, 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. 孫東東, 趙致平, 侯宗賢. 寶石CT前處置流程的優化對胃癌術前T分期的應用效果分析. 甘肅科技, 2023, 39(3): 104-106, 111.
32. 邢靜靜, 柴亞如, 高劍波, 等. 能譜CT在鑒別T3及T4a期胃癌中的應用價值. 中華胃腸外科雜志, 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. 胡國權, 郝建成, 范元軍, 等. 多層螺旋CT對可切除性胃癌轉移性淋巴結及N分期的診斷價值研究. 中國普外基礎與臨床雜志, 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. 張維漢, 胡建昆. 胃癌腹膜轉移診治現狀. 中華胃腸外科雜志, 2021, 24(3): 204-207.
37. 劉靜, 黃寶生, 張麗萍等. 能譜CT定量參數對進展期胃癌cM分期準確性的應用研究. 河西學院學報, 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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