Literature DB >> 34383241

GlucoCEST MRI for the Evaluation Response to Chemotherapeutic and Metabolic Treatments in a Murine Triple-Negative Breast Cancer: A Comparison with[18F]F-FDG-PET.

Martina Capozza1, Annasofia Anemone2, Chetan Dhakan3, Melania Della Peruta1, Martina Bracesco1, Sara Zullino2, Daisy Villano2, Enzo Terreno1,2,3, Dario Livio Longo3, Silvio Aime2,3.   

Abstract

PURPOSE: Triple-negative breast cancer (TNBC) patients have usually poor outcome after chemotherapy and early prediction of therapeutic response would be helpful. [18F]F-FDG-PET/CT acquisitions are often carried out to monitor variation in metabolic activity associated with response to the therapy, despite moderate accuracy and radiation exposure limit its application. The glucoCEST technique relies on the use of unlabelled D-glucose to assess glucose uptake with conventional MRI scanners and is currently under active investigations at clinical level. This work aims at validating the potential of MRI-glucoCEST in monitoring the therapeutic responses in a TNBC tumor murine model. PROCEDURES: Breast tumor (4T1)-bearing mice were treated with doxorubicin or dichloroacetate for 1 week. PET/CT with [18F]F-FDG and MRI-glucoCEST were performed at baseline and after 3 cycles of treatment. Metabolic changes measured with [18F]F-FDG-PET and glucoCEST were compared and evaluated with changes in tumor volumes.
RESULTS: Doxorubicin-treated mice showed a significant decrease in tumor growth when compared to the control group. GlucoCEST imaging provided metabolic response after three cycles of treatment. Conversely, no variations were detected in [18F]F-FDG uptake. Dichloroacetate-treated mice did not show any decrease either in tumor volume or in tumor metabolic activity as assessed by both glucoCEST and [18F]F-FDG-PET.
CONCLUSIONS: Metabolic changes during doxorubicin treatment can be predicted by glucoCEST imaging that appears more sensitive than [18F]F-FDG-PET in reporting on therapeutic response. These findings support the view that glucoCEST may be a sensitive technique for monitoring metabolic response, but future studies are needed to explore the accuracy of this approach in other tumor types and treatments.
© 2021. World Molecular Imaging Society.

Entities:  

Keywords:  Dichloroacetate; Doxorubicin; Glucose metabolism; MRI; Therapy monitoring; Triple-negative breast cancer; [18F]F-FDG-PET; glucoCEST

Mesh:

Substances:

Year:  2021        PMID: 34383241     DOI: 10.1007/s11307-021-01637-6

Source DB:  PubMed          Journal:  Mol Imaging Biol        ISSN: 1536-1632            Impact factor:   3.488


  72 in total

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Journal:  Breast Cancer Res Treat       Date:  2011-09-30       Impact factor: 4.872

3.  18F-FDG PET/CT and PET for evaluation of pathological response to neoadjuvant chemotherapy in breast cancer: a meta-analysis.

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Journal:  Acta Radiol       Date:  2012-06-25       Impact factor: 1.990

4.  Glycolytic activity with 18F-FDG PET/CT predicts final neoadjuvant chemotherapy response in breast cancer.

Authors:  Ana María García Vicente; Miguel Ángel Cruz Mora; Antonio Alberto León Martín; María Del Mar Muñoz Sánchez; Fernanda Relea Calatayud; Ober Van Gómez López; Ruth Espinosa Aunión; Ana Gonzalez Ageitos; Angel Soriano Castrejón
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6.  Metabolic monitoring of breast cancer chemohormonotherapy using positron emission tomography: initial evaluation.

Authors:  R L Wahl; K Zasadny; M Helvie; G D Hutchins; B Weber; R Cody
Journal:  J Clin Oncol       Date:  1993-11       Impact factor: 44.544

Review 7.  ¹⁸F-FDG PET/CT for Monitoring of Treatment Response in Breast Cancer.

Authors:  Stefanie Avril; Raymond F Muzic; Donna Plecha; Bryan J Traughber; Shaveta Vinayak; Norbert Avril
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8.  Prognostic Value of MTV, SUVmax and the T/N Ratio of PET/CT in Patients with Glioma: A Systematic Review and Meta-Analysis.

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Review 9.  Imaging Cancer Metabolism: Underlying Biology and Emerging Strategies.

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10.  18F-FDG uptake in PET/CT is a potential predictive biomarker of response to anti-PD-1 antibody therapy in non-small cell lung cancer.

Authors:  Kazuki Takada; Gouji Toyokawa; Yasuto Yoneshima; Kentaro Tanaka; Isamu Okamoto; Mototsugu Shimokawa; Sho Wakasu; Akira Haro; Atsushi Osoegawa; Tetsuzo Tagawa; Yoshinao Oda; Yoichi Nakanishi; Masaki Mori
Journal:  Sci Rep       Date:  2019-09-16       Impact factor: 4.379

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  4 in total

Review 1.  What do we know about dynamic glucose-enhanced (DGE) MRI and how close is it to the clinics? Horizon 2020 GLINT consortium report.

Authors:  Mina Kim; Afroditi Eleftheriou; Luca Ravotto; Bruno Weber; Michal Rivlin; Gil Navon; Martina Capozza; Annasofia Anemone; Dario Livio Longo; Silvio Aime; Moritz Zaiss; Kai Herz; Anagha Deshmane; Tobias Lindig; Benjamin Bender; Xavier Golay
Journal:  MAGMA       Date:  2022-01-15       Impact factor: 2.310

2.  64CuCl2 PET Imaging of 4T1-Related Allograft of Triple-Negative Breast Cancer in Mice.

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3.  Application of MRI and CT Images in Surgical Treatment of Early Cervical Cancer.

Authors:  An Lu; Guohua Lu
Journal:  Scanning       Date:  2022-08-02       Impact factor: 1.750

4.  In Vivo MRI-CEST Tumor pH Imaging Detects Resistance to Proton Pump Inhibitors in Human Prostate Cancer Murine Models.

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Journal:  Cancers (Basel)       Date:  2022-10-07       Impact factor: 6.575

  4 in total

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