Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
European Radiology
Published in: European Radiology 1/2020

Open Access 01-01-2020 | Magnetic Resonance Imaging | Gastrointestinal

Gastric cancer and image-derived quantitative parameters: Part 2—a critical review of DCE-MRI and 18F-FDG PET/CT findings

Authors: Lei Tang, Xue-Juan Wang, Hideo Baba, Francesco Giganti

Published in: European Radiology | Issue 1/2020

Login to get access

Abstract

There is yet no consensus on the application of functional imaging and qualitative image interpretation in the management of gastric cancer. In this second part, we will discuss the role of image-derived quantitative parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in gastric cancer, as both techniques have been shown to be promising and useful tools in the clinical decision making of this disease. We will focus on different aspects including aggressiveness assessment, staging and Lauren type discrimination, prognosis prediction and response evaluation. Although both the number of articles and the patients enrolled in the studies were rather small, there is evidence that quantitative parameters from DCE-MRI such as Ktrans, Ve, Kep and AUC could be promising image-derived surrogate parameters for the management of gastric cancer. Data from 18F-FDG PET/CT studies showed that standardised uptake value (SUV) is significantly associated with the aggressiveness, treatment response and prognosis of this disease. Along with the results from diffusion-weighted MRI and contrast-enhanced multidetector computed tomography presented in Part 1 of this critical review, there are additional image-derived quantitative parameters from DCE-MRI and 18F-FDG PET/CT that hold promise as effective tools in the diagnostic pathway of gastric cancer.

Key Points

• Quantitative analysis from DCE-MRI and18F-FDG PET/CT allows the extrapolation of multiple image-derived parameters.
• Data from DCE-MRI (Ktrans, Ve, Kep and AUC) and 18F-FDG PET/CT (SUV) are non-invasive, quantitative image-derived parameters that hold promise in the evaluation of the aggressiveness, treatment response and prognosis of gastric cancer.
Literature
1.
Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D (2011) Global cancer statistics. CA Cancer J Clin 61(2):69–90CrossRef
2.
3.
Giganti F, Orsenigo E, Arcidiacono PG et al (2016) Preoperative locoregional staging of gastric cancer: is there a place for magnetic resonance imaging? Prospective comparison with EUS and multidetector computed tomography. Gastric Cancer 19(1):216–225CrossRef
4.
Richman DM, Tirumani SH, Hornick JL et al (2017) Beyond gastric adenocarcinoma: multimodality assessment of common and uncommon gastric neoplasms. Abdom Radiol (NY) 42(1):124–140
5.
Brenkman HJF, Gertsen EC, Vegt E et al (2018) Evaluation of PET and laparoscopy in STagIng advanced gastric cancer: a multicenter prospective study (PLASTIC-study). BMC Cancer 18(1):450CrossRef
6.
European Society of Radiology (ESR) (2010) White paper on imaging biomarkers. Insights Imaging 1(2):42–45CrossRef
7.
Buckler AJ, Bresolin L, Dunnick NR, Sullivan DC (2011) A collaborative enterprise for multi-stakeholder participation in the advancement of quantitative imaging. Radiology 258(3):906–914CrossRef
8.
Tofts PS (1997) Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J Magn Reson Imaging 7(1):91–101CrossRef
9.
O’Connor JP, Tofts PS, Miles KA, Parkes LM, Thompson G, Jackson A (2011) Dynamic contrast-enhanced imaging techniques: CT and MRI. Br J Radiol 84(special_issue_2):S112–S120
10.
Kershaw LE, Cheng HLM (2010) Temporal resolution and SNR requirements for accurate DCE-MRI data analysis using the AATH model. Magn Reson Med 64(6):1772–1780CrossRef
11.
Nishida N, Yano H, Nishida T, Kamura T, Kojiro M (2006) Angiogenesis in cancer. Vasc Health Risk Manag 2(3):213–219CrossRef
12.
Tonini T, Rossi F, Claudio PP (2003) Molecular basis of angiogenesis and cancer. Oncogene 22(42):6549–6556CrossRef
13.
Cuenod CA, Balvay D (2013) Perfusion and vascular permeability: basic concepts and measurement in DCE-CT and DCE-MRI. Diagn Interv Imaging 94(12):1187–1204CrossRef
14.
Tofts PS, Brix G, Buckley DL et al (1999) Estimating kinetic parameters from dynamic contrast-enhanced T1-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging 10:223–232CrossRef
15.
Kang BC, Kim JH, Kim KW et al (2000) Abdominal imaging value of the dynamic and delayed MR sequence with Gd-DTPA in the T-staging of stomach cancer: correlation with the histopathology. Abdom Imaging 25:14–24CrossRef
16.
Joo I, Lee JM, Han JK, Yang HK, Lee HJ, Choi BI (2015) Dynamic contrast-enhanced MRI of gastric cancer: correlation of the perfusion parameters with pathological prognostic factors. J Magn Reson Imaging 41(6):1608–1614CrossRef
17.
Ma L, Xu X, Zhang M et al (2017) Dynamic contrast-enhanced MRI of gastric cancer: correlations of the pharmacokinetic parameters with histological type, Lauren classification, and angiogenesis. Magn Reson Imaging 37:27–32CrossRef
18.
Li HH, Zhu H, Yue L et al (2018) Feasibility of free-breathing dynamic contrast-enhanced MRI of gastric cancer using a golden-angle radial stack-of-stars VIBE sequence: comparison with the conventional contrast-enhanced breath-hold 3D VIBE sequence. Eur Radiol 28(5):1891–1899CrossRef
19.
Thie JA (2004) Understanding the standardized uptake value, its methods, and implications for usage. J Nucl Med 45(9):1431–1434PubMed
20.
Stahl A, Ott K, Weber WA et al (2003) FDG PET imaging of locally advanced gastric carcinomas: correlation with endoscopic and histopathological findings. Eur J Nucl Med Mol Imaging 30(2):288–295CrossRef
21.
Mochiki E, Kuwano H, Katoh H, Asao T, Oriuchi N, Endo K (2004) Evaluation of 18F-2-deoxy-2-fluoro-D-glucose positron emission tomography for gastric cancer. World J Surg 28(3):247–253CrossRef
22.
Chen J, Cheong JH, Yun MJ et al (2005) Improvement in preoperative staging of gastric adenocarcinoma with positron emission tomography. Cancer 103(11):2383–2390
23.
Oh HH, Lee SE, Choi IS et al (2011) The peak-standardized uptake value (P-SUV) by preoperative positron emission tomography-computed tomography (PET-CT) is a useful indicator of lymph node metastasis in gastric cancer. J Surg Oncol 104(5):530–533CrossRef
24.
Oh SY, Cheon GJ, Kim YC, Jeong E, Kim S, Choe JG (2012) Detectability of T-measurable diseases in advanced gastric cancer on FDG PET-CT. Nucl Med Mol Imaging 46(4):261–268CrossRef
25.
Namikawa T, Okabayshi T, Nogami M, Ogawa Y, Kobayashi M, Hanazaki K (2014) Assessment of 18F-fluorodeoxyglucose positron emission tomography combined with computed tomography in the preoperative management of patients with gastric cancer. Int J Clin Oncol 19(4):649–655CrossRef
26.
Stahl A, Ott K, Schwaiger M, Weber WA (2004) Comparison of different SUV-based methods for monitoring cytotoxic therapy with FDG PET. Eur J Nucl Med Mol Imaging 31(11):1471–1479CrossRef
27.
Vallböhmer D, Hölscher AH, Schneider PM et al (2010) [18F]-Fluorodeoxyglucose-positron emission tomography for the assessment of histopathologic response and prognosis after completion of neoadjuvant chemotherapy in gastric cancer. J Surg Oncol 102(2):135–140
28.
Giganti F, De Cobelli F, Canevari C et al (2014) Response to chemotherapy in gastric adenocarcinoma with diffusion-weighted MRI and 18 F-FDG-PET/CT: correlation of apparent diffusion coefficient and partial volume corrected standardized uptake value with histological tumor regression grade. J Magn Reson Imaging 40(5):1147–1157CrossRef
29.
Wang C, Guo W, Zhou M et al (2016) The predictive and prognostic value of early metabolic response assessed by positron emission tomography in advanced gastric cancer treated with chemotherapy. Clin Cancer Res 22(7):1603–1610CrossRef
30.
Park S, Ha S, Kwon HW et al (2017) Prospective evaluation of changes in tumor size and tumor metabolism in patients with advanced gastric cancer undergoing chemotherapy: association and clinical implication. J Nucl Med 58(6):899–904CrossRef
31.
Schneider PM, Eshmuminov D, Rordorf T et al (2018) 18FDG-PET-CT identifies histopathological non-responders after neoadjuvant chemotherapy in locally advanced gastric and cardia cancer: cohort study. BMC Cancer 18:548CrossRef
32.
Mandard AM, Dalibard F, Mandard JC et al (1994) Pathologic assessment of tumor regression after preoperative chemoradiotherapy of esophageal carcinoma: clinicopathologic correlations. Cancer 73(11):2680–2686CrossRef
33.
Borggreve AS, Mook S, Verheij M et al (2018) Preoperative image-guided identification of response to neoadjuvant chemoradiotherapy in esophageal cancer (PRIDE): a multicenter observational study. BMC Cancer 18(1):1006CrossRef
34.
Kwee RM, Kwee TC (2014) Role of imaging in predicting response to neoadjuvant chemotherapy in gastric cancer. World J Gastroenterol 20(7):1650–1656CrossRef
35.
Pak KH, Yun M, Cheong JH, Hyung WJ, Choi SH, Noh SH (2011) Clinical implication of FDG-PET in advanced gastric cancer with signet ring cell histology. J Surg Oncol 104(6):566–570
36.
Park JC, Lee J-H, Cheoi K et al (2012) Predictive value of pretreatment metabolic activity measured by fluorodeoxyglucose positron emission tomography in patients with metastatic advanced gastric cancer: the maximal SUV of the stomach is a prognostic factor. Eur J Nucl Med Mol Imaging 39(7):1107–1116CrossRef
37.
Lee JW, Lee SM, Lee M-S, Shin HC (2012) Role of 18F-FDG PET/CT in the prediction of gastric cancer recurrence after curative surgical resection. Eur J Nucl Med Mol Imaging 39(9):1425–1434CrossRef
38.
Kim J, Lim ST, Na CJ et al (2014) Pretreatment F-18 FDG PET/CT parameters to evaluate progression-free survival in gastric cancer. Nucl Med Mol Imaging 48(1):33–40CrossRef
39.
Grabinska K, Pelak M, Wydmanski J, Tukiendorf A, d’Amico A (2015) Prognostic value and clinical correlations of 18-fluorodeoxyglucose metabolism quantifiers in gastric cancer. World J Gastroenterol 21(19):5901–5909
40.
Na SJ, o JH, Park JM et al (2016) Prognostic value of metabolic parameters on preoperative 18F-fluorodeoxyglucose positron emission tomography/computed tomography in patients with stage III gastric cancer. Oncotarget 7(39)
41.
Lee S, Seo HJ, Kim S, Eo JS, Oh SC (2017) Prognostic significance of interim 18 F-fluorodeoxyglucose positron emission tomography-computed tomography volumetric parameters in metastatic or recurrent gastric cancer. Asia Pac J Clin Oncol:1–8
42.
43.
Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278(2):563–577CrossRef
44.
Cook GJR, Azad G, Owczarczyk K, Siddique M, Goh V (2018) Challenges and promises of PET radiomics. Int J Radiat Oncol Biol Phys 102(4):1083–1089CrossRef
45.
Lovinfosse P, Visvikis D, Hustinx R, Hatt M (2018) FDG PET radiomics: a review of the methodological aspects. Clin Transl Imaging 6:379–391CrossRef
46.
47.
Jiang Y, Yuan Q, Lv W et al (2018) Radiomic signature of 18F fluorodeoxyglucose PET/CT for prediction of gastric cancer survival and chemotherapeutic benefits. Theranostics 8(21):5915–5928CrossRef
48.
Rosenkrantz AB, Mendiratta-Lala M, Bartholmai BJ et al (2015) Clinical utility of quantitative imaging. Acad Radiol 22(1):33–49CrossRef
Metadata
Title
Gastric cancer and image-derived quantitative parameters: Part 2—a critical review of DCE-MRI and 18F-FDG PET/CT findings
Authors
Lei Tang
Xue-Juan Wang
Hideo Baba
Francesco Giganti
Publication date
01-01-2020
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 1/2020
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-019-06370-x

Other articles of this Issue 1/2020

European Radiology 1/2020 Go to the issue

Chest

Diagnostic outcome and safety of CT-guided core needle biopsy for mediastinal masses: a systematic review and meta-analysis

Molecular Imaging

Can dedicated breast PET help to reduce overdiagnosis and overtreatment by differentiating between indolent and potentially aggressive ductal carcinoma in situ?

Magnetic Resonance

Baseline 3D-ADC outperforms 2D-ADC in predicting response to treatment in patients with colorectal liver metastases

Cardiac

Prevalence and prognostic value of late gadolinium enhancement on CMR in aortic stenosis: meta-analysis

Gastrointestinal

The split scar sign as an indicator of sustained complete response after neoadjuvant therapy in rectal cancer

Nuclear Medicine

Limited clinical value of two consecutive post-transplant renal scintigraphy procedures