Association of pharmacokinetic and metabolic parameters derived using simultaneous PET/MRI: Initial findings and impact on response evaluation in breast cancer

Jena, Amarnath; Taneja, Sangeeta; Singh, Amresh Kumar; Negi, Pradeep; Mehta, Shashi Bhushan; Ahuja, Aashim; Singhal, Manish; Sarin, Ramesh

doi:10.1016/j.ejrad.2017.04.013

Cited by 15 publications

(10 citation statements)

References 27 publications

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“…This finding is of particular interest, not only for staging but also for follow-up and treatment response evaluation, considering that perfusion parameters, such as K trans , have been demonstrated to be potentially predictive of patients' response to therapy. 22,47 In contrast, no significant correlation between mean values of metabolic (SUV) and diffusion (ADC) parameters were found (Figure 4). The literature findings with respect to this are contradictory.…”

Section: Discussionmentioning

confidence: 92%

“…In our population, we confirmed this significant positive correlation between the mean SUV value and perfusion K trans _SSM and k ep _Tofts ( p < 0.05). This finding is of particular interest, not only for staging but also for follow‐up and treatment response evaluation, considering that perfusion parameters, such as K trans , have been demonstrated to be potentially predictive of patients' response to therapy …”

Section: Discussionmentioning

confidence: 95%

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A multi‐parametric PET/MRI study of breast cancer: Evaluation of DCE‐MRI pharmacokinetic models and correlation with diffusion and functional parameters

et al. 2018

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The objective of this study is to compare perfusion parameters, as measured by the shutter speed and the Tofts models applied in DCE‐MRI, in malignant breast lesions. Also, to investigate the relationship between perfusion, morphological and functional parameters extracted by the simultaneous acquisition of positron emission tomography (PET) and MRI. 46 patients with histologically confirmed breast cancer were imaged with a 3 T hybrid PET/MRI system, at staging. 18F‐fluorodeoxyglucose (FDG) PET images were acquired simultaneously with MRI, which included DW‐ and DCE‐MRI. Standardized uptake value (SUV), apparent diffusion coefficient (ADC) and pharmacokinetic maps (from the Tofts and shutter speed models) were generated for each primary lesion and a reference, healthy tissue area. Wilcoxon and Spearman tests were used for the statistical analysis. MRI‐derived parameters (perfusion and diffusion) and PET SUVmean were significantly different between tumour and reference tissue (p < 0.05). Significant correlations were found between the two pharmacokinetic models (p < 0.01) and between SUV and pharmacokinetic parameters (Ktrans, kep, ve and τi). No correlation was observed between ADC and SUV, or between ADC and pharmacokinetic parameters. In conclusion, PET/MRI allows for the characterization of primary lesions in breast cancer. Simultaneous analysis of perfusion, morphological and functional markers reveals good agreement between different pharmacokinetic models. Perfusion parameters showed a good correlation with the SUV in breast lesions. In particular, the shutter speed τi was found to be significantly correlated to 18F‐FDG uptake (negative correlation), indicating an association with tumour metabolic mechanisms.

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Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 95%

A multi‐parametric PET/MRI study of breast cancer: Evaluation of DCE‐MRI pharmacokinetic models and correlation with diffusion and functional parameters

et al. 2018

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“…To reduce the acquisition time (TA) in the calculation of K trans value while still maintaining the adequate diagnostic accuracy has been a matter of research. [ 20 21 22 ] These observations underscored the fact that factors influencing the estimation of K trans needs to be adequately addressed so that it can be used as a reliable parameter in the clinical setting. Many approaches such as variable flip angle (VFA): multiple flip angles (MFA), dual flip angle (DFA), and driven equilibrium single pulse observation of T 1 with high-speed incorporation of RF field in homogeneities (DESPOT1-HIFI) etc have been used to improve T 10 by correcting the B 1 inhomogeneity.…”

Section: Introductionmentioning

confidence: 99%

Ktrans Calculation Using Reference Method Corrected Native T10 for Breast Cancer Diagnosis

Negi

Mehta

Jena

et al. 2023

Journal of Medical Physics

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Purpose: The objective of the study is to use multiple tube phantoms to generate correction factor at different spatial locations for each breast coil cuff to correct the native T 10 value in the corresponding spatial location of the breast lesion. The corrected T 10 value was used to compute K trans and analyze its diagnostic accuracy in the classification of target condition, i.e., breast tumors into malignant and benign. Materials and Methods: Both in vitro phantom study (external reference) and patient’s studies were acquired on simultaneous positron emission tomography/magnetic resonance imaging (PET/MRI) Biograph molecular magnetic resonance (mMR) system using 4 channel mMR breast coil. The spatial correction factors derived using multiple tube phantom were used for a retrospective analysis of dynamic contrast-enhanced (DCE) MRI data of 39 patients with a mean age of 50 years (31–77 years) having 51 enhancing breast lesions. Results: Corrected and non-corrected receiver operating characteristic (ROC) curve analysis revealed a mean K trans value of 0.64 min −1 and 0.60 min −1 , respectively. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy for non-corrected data were 86.21%, 81.82%, 86.20%, 81.81%, and 84.31%, respectively, and for corrected data were 93.10%, 86.36%, 90%, 90.47%, and 90.20% respectively. The area under curve (AUC) of corrected data was improved to 0.959 (95% confidence interval [CI] 0.862–0.994) from 0.824 (95% CI 0.694–0.918) of non-corrected data, and for NPV, it was improved to 90.47% from 81.81%, respectively. Conclusion: T 10 values were normalized using multiple tube phantom which was used for computation of K trans . We found significant improvement in the diagnostic accuracy of corrected K trans values that results in better characterization of breast lesions.

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“…Fast dynamic MRI through pharmacokinetic (PK) modeling indirectly measures neovascularity and is related to computation of volume transfer constant (K trans ), rate constant (k ep ), and extravascular extracellular volume fraction (v e ). [ 9 10 11 12 ] With PK modeling, the alterations in contrast agent concentration in tissue are translated to changes in signal intensity denoted by the alterations in the relaxation time of native T1 value. The accuracy of native T1 calculation is thus pivotal for PK parameter estimation but itself is known to be influenced by a number of factors such as B1 inhomogeneity, optimization of flip angle, RF inhomogeneity, nonlinear RF amplifier, and distortions in slice profile.…”

Section: Introductionmentioning

confidence: 99%

Use of Multiple-Tube Phantom

Negi

Mehta

Jena

2021

Journal of Medical Physics

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Background: Native T1 relaxation time (T10) presents an important prerequisite to reliably quantify pharmacokinetic parameter like Ktrans (volume transfer constant). Native T1 value can be varied because of the inhomogeneity in the breast coil, thus influencing the Ktrans measurement. Purpose: The current study aims to design and use a phantom with multiple tubes for both breast cuffs to assess native T1 inhomogeneity across the dedicated molecular magnetic resonance (mMR) breast coil and adopt corrective method to spatially normalize T1 values to improve homogeneity. Materials and Methods: Two phantoms with multiple tubes (19 tubes) specially designed and filled with contrast medium with known T1 value were placed in each mMR breast coil cuff. Native T1 at various spatial locations was calculated applying dual flip angle sequence. Correction factors were derived at various spatial locations as a function of deviation of the native T1 value from phantom and applied to correct the native T1 relaxation time. Results: A statistically significant difference between native T1 values of the right and left anterior (P = 0.0095), middle (P = 0.0081), and posterior (P = 0.0004) parts of the breast coil. No significant difference was seen in the corrected T1 values between anterior (P = 0.402), middle (P = 0.305), and posterior (P = 0.349) aspects of both sides of the breast coil. Conclusion: Inhomogeneity in the native T1 value exists in dedicated mMR breast coil, and significant improvement can be achieved using specially designed external phantom with multiple tubes.

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Association of pharmacokinetic and metabolic parameters derived using simultaneous PET/MRI: Initial findings and impact on response evaluation in breast cancer

Cited by 15 publications

References 27 publications

A multi‐parametric PET/MRI study of breast cancer: Evaluation of DCE‐MRI pharmacokinetic models and correlation with diffusion and functional parameters

A multi‐parametric PET/MRI study of breast cancer: Evaluation of DCE‐MRI pharmacokinetic models and correlation with diffusion and functional parameters

Ktrans Calculation Using Reference Method Corrected Native T10 for Breast Cancer Diagnosis

Use of Multiple-Tube Phantom

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