Multi-parametric PET/MRI for enhanced tumor characterization of patients with cervical cancer

被引:6
|
作者
Ahangari, Sahar [1 ]
Andersen, Flemming Littrup [1 ,2 ]
Hansen, Naja Liv [1 ]
Nottrup, Trine Jakobi [3 ]
Berthelsen, Anne Kiil [3 ]
Kallehauge, Jesper Folsted [4 ]
Vogelius, Ivan Richter [3 ]
Kjaer, Andreas [1 ,5 ]
Hansen, Adam Espe [1 ,2 ,6 ]
Fischer, Barbara Malene [1 ,2 ]
机构
[1] Univ Copenhagen, Rigshosp, Dept Clin Physiol Nucl Med & PET, Copenhagen, Denmark
[2] Univ Copenhagen, Dept Clin Med, Copenhagen, Denmark
[3] Univ Copenhagen, Rigshosp, Dept Oncol, Sect Radiotherapy, Copenhagen, Denmark
[4] Aarhus Univ Hosp, Danish Ctr Particle Therapy, Aarhus, Denmark
[5] Univ Copenhagen, Dept Biomed Sci, Cluster Mol Imaging, Copenhagen, Denmark
[6] Univ Copenhagen, Rigshosp, Dept Diagnost Radiol, Copenhagen, Denmark
来源
EUROPEAN JOURNAL OF HYBRID IMAGING | 2022年 / 6卷 / 01期
基金
欧盟地平线“2020”;
关键词
Multi-parametric imaging; PET; MRI; Tumor heterogeneity; Radiotherapy; Cervical cancer; DWI; RGD; APPARENT DIFFUSION-COEFFICIENT; WEIGHTED MRI; VOLUME; HETEROGENEITY; CHEMORADIOTHERAPY; BRACHYTHERAPY; RADIOTHERAPY; DELINEATION; PET;
D O I
10.1186/s41824-022-00129-2
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Aim The concept of personalized medicine has brought increased awareness to the importance of inter- and intra-tumor heterogeneity for cancer treatment. The aim of this study was to explore simultaneous multi-parametric PET/MRI prior to chemoradiotherapy for cervical cancer for characterization of tumors and tumor heterogeneity. Methods Ten patients with histologically proven primary cervical cancer were examined with multi-parametric Ga-68-NODAGA-E[c(RGDyK)](2)-PET/MRI for radiation treatment planning after diagnostic F-18-FDG-PET/CT. Standardized uptake values (SUV) of RGD and FDG, diffusion weighted MRI and the derived apparent diffusion coefficient (ADC), and pharmacokinetic maps obtained from dynamic contrast-enhanced MRI with the Tofts model (iAUC(60), K-trans, v(e), and k(ep)) were included in the analysis. The spatial relation between functional imaging parameters in tumors was examined by a correlation analysis and joint histograms at the voxel level. The ability of multi-parametric imaging to identify tumor tissue classes was explored using an unsupervised 3D Gaussian mixture model-based cluster analysis. Results Functional MRI and PET of cervical cancers appeared heterogeneous both between patients and spatially within the tumors, and the relations between parameters varied strongly within the patient cohort. The strongest spatial correlation was observed between FDG uptake and ADC (median r = - 0.7). There was moderate voxel-wise correlation between RGD and FDG uptake, and weak correlations between all other modalities. Distinct relations between the ADC and RGD uptake as well as the ADC and FDG uptake were apparent in joint histograms. A cluster analysis using the combination of ADC, FDG and RGD uptake suggested tissue classes which could potentially relate to tumor sub-volumes. Conclusion A multi-parametric PET/MRI examination of patients with cervical cancer integrated with treatment planning and including estimation of angiogenesis and glucose metabolism as well as MRI diffusion and perfusion parameters is feasible. A combined analysis of functional imaging parameters indicates a potential of multi-parametric PET/MRI to contribute to a better characterization of tumor heterogeneity than the modalities alone. However, the study is based on small patient numbers and further studies are needed prior to the future design of individually adapted treatment approaches based on multi-parametric functional imaging.
引用
收藏
页数:16
相关论文
共 50 条
  • [11] Incorporating Oxygen-Enhanced MRI into Multi-Parametric Assessment of Human Prostate Cancer
    Zhou, Heling
    Hallac, Rami R.
    Yuan, Qing
    Ding, Yao
    Zhang, Zhongwei
    Xie, Xian-Jin
    Francis, Franto
    Roehrborn, Claus G.
    Sims, R. Douglas
    Costa, Daniel N.
    Raj, Ganesh V.
    Mason, Ralph P.
    DIAGNOSTICS, 2017, 7 (03):
  • [12] Multi-parametric MRI Examinations for the Detection of Prostate Cancer
    Graewert, Stephanie
    ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN, 2019, 191 (03): : 185 - 185
  • [13] The use of multi-parametric MRI in the detection of prostate cancer
    Bolton, E. M.
    Quinlan, M.
    Costelloe, J.
    O'Kelly, F.
    Galvin, D.
    Lennon, G.
    Mulvin, D.
    McMahon, C.
    Quinlan, D.
    BJU INTERNATIONAL, 2014, 114 : 21 - 22
  • [14] Multi-parametric FDG PET/MRI as an Early Predictor of Response to Neoadjuvant Chemotherapy in Patients wit Epithelial Ovarian Cancer
    Franceschi, Ana
    Pothuri, Bhavana
    Frey, Melissa
    Chandarana, Hersh
    Jackson, Kimberly
    Friedman, Kent
    JOURNAL OF NUCLEAR MEDICINE, 2018, 59
  • [15] Multi-parametric MRI characterization of inflammation in murine skeletal muscle
    Bryant, Nathan D.
    Li, Ke
    Does, Mark D.
    Barnes, Stephanie
    Gochberg, Daniel F.
    Yankeelov, Thomas E.
    Park, Jane H.
    Damon, Bruce M.
    NMR IN BIOMEDICINE, 2014, 27 (06) : 716 - 725
  • [16] Multi-parametric FDG PET/MRI as an early predictor of response to neoadjuvant chemotherapy in patients with epithelial ovarian cancer.
    Frey, Melissa Kristen
    Sawaged, Zacharia
    Franceschi, Ana M.
    Friedman, Kent P.
    Lutz, Kathleen
    Curtin, John Patrick
    Blank, Stephanie V.
    Pothuri, Bhavana
    JOURNAL OF CLINICAL ONCOLOGY, 2019, 37 (15)
  • [17] Multi-parametric MRI characterization of enzymatically degraded articular cartilage
    Nissi, Mikko J.
    Salo, Elli-Noora
    Tiitu, Virpi
    Liimatainen, Timo
    Michaeli, Shalom
    Mangia, Silvia
    Ellermann, Jutta
    Nieminen, Miika T.
    JOURNAL OF ORTHOPAEDIC RESEARCH, 2016, 34 (07) : 1111 - 1120
  • [18] A Decomposable Model for the Detection of Prostate Cancer in Multi-parametric MRI
    Lay, Nathan
    Tsehay, Yohannes
    Sumathipala, Yohan
    Cheng, Ruida
    Gaur, Sonia
    Smith, Clayton
    Barbu, Adrian
    Lu, Le
    Turkbey, Baris
    Choyke, Peter L.
    Pinto, Peter
    Summers, Ronald M.
    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT II, 2018, 11071 : 930 - 939
  • [19] CONFIDENCE GUIDED ENHANCING BRAIN TUMOR SEGMENTATION IN MULTI-PARAMETRIC MRI
    Reddy, Kishore K.
    Solmaz, Berkan
    Yan, Pingkun
    Avgeropoulos, Nicholas G.
    Rippe, David J.
    Shah, Mubarak
    2012 9TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), 2012, : 366 - 369
  • [20] IMPACT OF MULTIFOCALITY ON PROSTATE CANCER DETECTION BY MULTI-PARAMETRIC MRI
    Tan, Nelly
    Le, Jesse
    Margolis, Daniel
    Lu, David
    King, Kevin
    Raman, Steven
    Reiter, Robert
    JOURNAL OF UROLOGY, 2014, 191 (04): : E588 - E589