Assessment of early treatment response to neoadjuvant chemotherapy in breast cancer using non-mono-exponential diffusion models: a feasibility study comparing the baseline and mid-treatment MRI examinations

Background Diffusion‐weighted imaging (DWI) plays an important role in the differentiation of malignant and benign breast lesions. Purpose To investigate the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched‐exponential DWI models in the differential diagnosis of breast lesions. Study Type Prospective. Population Sixty‐one patients (age range: 25–68 years old; mean age: 46 years old) with 31 malignant lesions, 42 benign lesions, and 28 normal breast tissues diagnosed initially by clinical palpation, ultrasonography, or conventional mammography were enrolled in the study from January to September 2016. Field Strength 3.0T MR scanner, T1WI, T2WI, DWI (conventional and multi‐b values), dynamic contrast‐enhanced. Assessment The apparent diffusion coefficient (ADC) was calculated by monoexponential analysis. The diffusion coefficient (ADCslow), pseudodiffusion coefficient (ADCfast), and perfusion fraction (f) were calculated using the biexponential model. The distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) were obtained using a stretched‐exponential model. All parameters were compared for malignant tumors, benign tumors, and normal breast tissues. A receiver operating characteristic curve was used to compare the ability of these parameters, in order to differentiate benign and malignant breast lesions. Statistical Tests All statistical analyses were performed using statistical software (SPSS). Results ADC, ADCslow, f, DDC, and α values were significantly lower in malignant tumors when compared with normal breast tissues and benign tumors (P < 0.05). However, ADC and f had higher area under the receiver operating characteristic curve (AUC) values (0.889 and 0.919, respectively). Data Conclusion The parameters derived from the biexponential and stretched‐exponential DWI could provide additional information for differentiating between benign and malignant breast tumors when compared with conventional diffusion parameters. Level of Evidence: 4 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;50:1461–1467.

Section: Discussionmentioning

confidence: 46%

Section: Discussionmentioning

confidence: 81%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Monoexponential, Biexponential, and stretched‐exponential models using diffusion‐weighted imaging: A quantitative differentiation of breast lesions at 3.0T

Jin

Zhang

Cheng

et al. 2019

“…For this reason, more sophisticated non‐monoexponential diffusion models, such as the kurtosis model, the stretched exponential model, and the statistical model, were proposed to draw a picture of the complex water molecular motions. In comparison with the monoexponential model, these non‐monoexponential models can give more diffusion‐related parameters and provide complementary information on the properties and features of tumor …”

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confidence: 99%

“…In comparison with the monoexponential model, these nonmonoexponential models can give more diffusion-related parameters and provide complementary information on the properties and features of tumor. 8,14 Recently, non-Gaussian diffusion behavior has been observed in HCC and several studies have also investigated the use of the non-monoexponential diffusion models for the characterization of HCC and the evaluation of treatment response. [15][16][17] However, there is still limited knowledge on which non-monoexponential model can more accurately describe the non-Gaussian DW attenuation signals in HCC.…”

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confidence: 99%

Evaluation of non‐monoexponential diffusion models for hepatocellular carcinoma using b values up to 2000 s/mm²: A short‐term repeatability study

Kuai

Sang

Yao

et al. 2018

Background Non‐monoexponential diffusion models are being used increasingly for the characterization and curative effect evaluation of hepatocellular carcinoma (HCC). But the fitting quality of the models and the repeatability of their parameters have not been assessed for HCC. Purpose To evaluate kurtosis, stretched exponential, and statistical models for diffusion‐weighted imaging (DWI) of HCC, using b‐values up to 2000 s/mm2, in terms of fitting quality and repeatability. Study Type Prospective. Population Eighteen patients with HCC. Field Strength/Sequence Conventional and DW images (b = 0, 200, 500, 1000, 1500, 2000 s/mm2) were acquired at 3.0T. Assessment The parameters of the kurtosis, stretched exponential, and statistical models were calculated on regions of interest (ROIs) of each lesion. Statistical Tests The fitting quality was evaluated through comparing the fitting residuals produced on the average data of ROI between different models using a paired t‐test or Wilcoxon rank‐sum test. Repeatability of the fitted parameters at the median values on the voxelwise data of ROI was assessed using the within coefficient of variation (WCV), the intraclass correlation coefficient (ICC), and the 95% Bland–Altman limits of agreements (BA‐LA). The repeatability was divided into four levels: excellent, good, acceptable, and poor, referring to the values of ICC and WCV. Results Among three models, the stretched exponential model provided the best fit to HCC (P < 0.05), whereas the statistical model produced the largest fitting residuals (P < 0.05). The repeatability of K from the kurtosis model was excellent (ICC 0.915; WCV 8.79%), while the distributed diffusion coefficient (DDC) from the stretched model was just acceptable (ICC 0.477; WCV 27.83%). The repeatability was good for other diffusion‐related parameters. Data Conclusion Considering the model fit and repeatability, the kurtosis and stretched exponential models are the preferred models for the description of the DW signals of HCC with respect to the statistical model. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:297–304.

Diffusion MRI of the breast: Current status and future directions

Iima

Honda

Sigmund

et al. 2019

131

120

Diffusion‐weighted imaging (DWI) is increasingly being incorporated into routine breast MRI protocols in many institutions worldwide, and there are abundant breast DWI indications ranging from lesion detection and distinguishing malignant from benign tumors to assessing prognostic biomarkers of breast cancer and predicting treatment response. DWI has the potential to serve as a noncontrast MR screening method. Beyond apparent diffusion coefficient (ADC) mapping, which is a commonly used quantitative DWI measure, advanced DWI models such as intravoxel incoherent motion (IVIM), non‐Gaussian diffusion MRI, and diffusion tensor imaging (DTI) are extensively exploited in this field, allowing the characterization of tissue perfusion and architecture and improving diagnostic accuracy without the use of contrast agents. This review will give a summary of the clinical literature along with future directions.Level of Evidence: 5Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2020;52:70–90.