Total choline quantification measured by 1H MR spectroscopy as early predictor of response after neoadjuvant treatment for locally advanced breast cancer: The impact of immunohistochemical status

Drisis, Stylianos; Flamen, Patrick; Ignatiadis, M.; Metens, Thierry; Chao, Shih-Li; Chintinne, Marie; Lemort, Marc

doi:10.1002/jmri.26042

Cited by 12 publications

(14 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A recent study showed the use of single‐voxel 1 H MRS to predict the response of chemotherapy treatment at 24–72 hours after administration of the first cycle of chemotherapy . In this study, the measured tCho levels in the tumor‐containing voxels were used to differentiate patients who responded to treatment . This study also emphasized the importance of an early assessment of response to anthracyclines in order to facilitate clinical decision‐making for further treatment …”

Section: Detection Of Gpc As a Biomarker Of Therapy Responsementioning

confidence: 95%

“…1 H MRS assessment of the tCho signal in breast cancer patients, which was achieved with water and fat suppression sequences, measured prior to the start of chemotherapy and after the three cycles of chemotherapy, has shown potential for predicting the response to chemotherapy (Figure ) . A recent study showed the use of single‐voxel 1 H MRS to predict the response of chemotherapy treatment at 24–72 hours after administration of the first cycle of chemotherapy . In this study, the measured tCho levels in the tumor‐containing voxels were used to differentiate patients who responded to treatment .…”

Section: Detection Of Gpc As a Biomarker Of Therapy Responsementioning

confidence: 99%

See 1 more Smart Citation

Focus on the glycerophosphocholine pathway in choline phospholipid metabolism of cancer

et al. 2019

View full text Add to dashboard Cite

Activated choline metabolism is a hallmark of carcinogenesis and tumor progression, which leads to elevated levels of phosphocholine and glycerophosphocholine in all types of cancer tested so far. Magnetic resonance spectroscopy applications have played a key role in detecting these elevated choline phospholipid metabolites. To date, the majority of cancer‐related studies have focused on phosphocholine and the Kennedy pathway, which constitutes the biosynthesis pathway for membrane phosphatidylcholine. Fewer and more recent studies have reported on the importance of glycerophosphocholine in cancer. In this review article, we summarize the recent literature on glycerophosphocholine metabolism with respect to its cancer biology and its detection by magnetic resonance spectroscopy applications.

show abstract

Section: Detection Of Gpc As a Biomarker Of Therapy Responsementioning

confidence: 95%

Section: Detection Of Gpc As a Biomarker Of Therapy Responsementioning

confidence: 99%

Focus on the glycerophosphocholine pathway in choline phospholipid metabolism of cancer

et al. 2019

View full text Add to dashboard Cite

show abstract

“…However, it is worth noting that consistent elevations in PMEs and tCho have been observed in a wide range of tumors, including brain, prostate, lung, skin, ovarian, and breast . As a means to monitor therapeutic response, tumor choline levels have been measured using MRS in animal and human tumors with mixed results, at least partly due to the technical difficulties associated with acquiring choline spectra on a background of high fat in normal breast tissue. The picture is further complicated because ChoK is not the only enzyme that contributes to PC accumulation; it can be produced directly by the actions of PLC on PtdCho, or by the hydrolysis of GPC as a source of additional choline for subsequent phosphorylation.…”

Section: Imaging Metabolic Lipid Changesmentioning

confidence: 99%

Imaging of cancer lipid metabolism in response to therapy

et al. 2019

View full text Add to dashboard Cite

Lipids represent a diverse array of molecules essential to the cell's structure, defense, energy, and communication. Lipid metabolism can often become dysregulated during tumor development. During cancer therapy, targeted inhibition of cell proliferation can likewise cause widespread and drastic changes in lipid composition. Molecular imaging techniques have been developed to monitor altered lipid profiles as a biomarker for cancer diagnosis and treatment response. For decades, MRS has been the dominant non-invasive technique for studying lipid metabolite levels. Recent insights into the oncogenic transformations driving changes in lipid metabolism haverevealed new mechanisms and signaling molecules that can be exploited using optical imaging, mass spectrometry imaging, and positron emission tomography. These novel imaging modalities have provided researchers with a diverse toolbox to examine changes in lipids in response to a wide array of anticancer strategies including chemotherapy, radiation therapy, signal transduction inhibitors, gene therapy, immunotherapy, or a combination of these strategies. The understanding of lipid metabolism in response to cancer therapy continues to evolve as each therapeutic method emerges, and this review seeks to summarize the current field and areas of unmet needs.

show abstract

“…Our work was based on retrospective postprocessing of data acquired from a prospective, nonrandomized, singe center, diagnostic study initiated in our institution from the same authors (EudraCT number: 2011‐006259‐12/ BECT number: B079201111884/ http://clinicaltrials.gov) from February 2013 to January 2017. The results from the initial study have been previously published but our current work adds the PRM analysis of the data. Patients were included in the prospective study according to: female gender, age ≥18 years; previously untreated invasive ductal or lobular breast cancer or any breast cancer ≥2 cm with an indication for neoadjuvant chemotherapy and adequate renal function.…”

Section: Methodsmentioning

confidence: 99%

“…Several magnetic resonance imaging (MRI)0based biomarkers have been assessed with the objective of predicting as early as possible the response to neoadjuvant treatment. These include using quantitative parameters extracted from dynamic contrast‐enhanced (DCE)‐MRI such as K trans and K ep , either by using diffusion‐weighted imaging (DWI) or choline quantification (tCho) . These biomarkers are generated by averaging certain imaging properties from a region of interest (ROI), importantly without taking into account any spatial information.…”

mentioning

confidence: 99%

Early prediction of neoadjuvant treatment outcome in locally advanced breast cancer using parametric response mapping and radial heterogeneity from breast MRI

Drisis

Adoui

Flamen

et al. 2019

Magnetic Resonance Imaging

Self Cite

View full text Add to dashboard Cite

Background: Early prediction of nonresponse is essential in order to avoid inefficient treatments. Purpose: To evaluate if parametrical response mapping (PRM)-derived biomarkers could predict early morphological response (EMR) and pathological complete response (pCR) 24-72 hours after initiation of chemotherapy treatment and whether concentric analysis of nonresponding PRM regions could better predict response. Study Type: This was a retrospective analysis of prospectively acquired cohort, nonrandomized, monocentric, diagnostic study. Population: Sixty patients were initially recruited, with 39 women participating in the final cohort. Field Strength/Sequence: A 1.5T scanner was used for MRI examinations. Assessment: Dynamic contrast-enhanced (DCE)-MR images were acquired at baseline (timepoint 1, TP1), 24-72 hours after the first chemotherapy (TP2), and after the end of anthracycline treatment (TP3). PRM was performed after fusion of T 1 subtraction images from TP1 and TP2 using an affine registration algorithm. Pixels with an increase of more than 10% of their value (PRMdce +) were corresponding nonresponding regions of the tumor. Patients with a decrease of maximum diameter (%dDmax) between TP1 and TP3 of more than 30% were defined as EMR responders. pCR patients achieved a residual cancer burden score of 0. Statistical Tests: T-test, receiver operating characteristic (ROC) curves, and logistic regression were used for the analysis. Results: PRM showed a statistical difference between pCR response groups (P < 0.01) and AUC of 0.88 for the prediction of non-pCR. Logistic regression analysis demonstrated that PRMdce+ and Grade II were significant (P < 0.01) for non-pCR prediction (AUC = 0.94). Peripheral tumor region demonstrated higher performance for the prediction of non-pCR (AUC = 0.85) than intermediate and central zones; however, statistical comparison showed no significant difference. Data Conclusion: PRM could be predictive of non-pCR 24-72 hours after initiation of chemotherapy treatment. Moreover, the peripheral region showed increased AUC for non-pCR prediction and increased signal intensity during treatment for non-pCR tumors, information that could be used for optimal tissue sampling. Level of Evidence: 1 Technical Efficacy Stage: 4

show abstract

Total choline quantification measured by 1H MR spectroscopy as early predictor of response after neoadjuvant treatment for locally advanced breast cancer: The impact of immunohistochemical status

Abstract: 1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2018;48:982-993.

Cited by 12 publications

References 37 publications

Focus on the glycerophosphocholine pathway in choline phospholipid metabolism of cancer

Focus on the glycerophosphocholine pathway in choline phospholipid metabolism of cancer

Imaging of cancer lipid metabolism in response to therapy

Early prediction of neoadjuvant treatment outcome in locally advanced breast cancer using parametric response mapping and radial heterogeneity from breast MRI

Contact Info

Product

Resources

About