Evaluation of breast cancer malignancy, prognostic factors and molecular subtypes using a continuous-time random-walk MR diffusion model

Chang, Helen; Wang, Dawei; Li, Yuting; Xiang, Shaoxin; Yu, Yang; Kong, Pengfei; Fang, Caiyun; Liu, Ming; Wang, Xiangqing; Zhang, Chuanyi; Jia, Wei; Qu, Yan; Liu, Xinhui; Zeng, Qingshi

doi:10.1016/j.ejrad.2023.111003

Cited by 5 publications

(7 citation statements)

References 33 publications

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“…The a value can reflect the temporal heterogeneity of the tissue by describing the probability that a water molecule will be retained or released as it diffuses through a tissue structure. Previous researches have demonstrated that lower a value corresponds to increased tissue heterogeneity (15,17). In this study, a of PCa were significantly lower than that of CP, consistent with previous research theories.…”

Section: Discussionsupporting

confidence: 92%

“…Recently, the continuous-time random walk (CTRW) diffusion model was developed and used to describing the heterogeneity of complex tissue microenvironments and tissue structures by providing three parameters, a, b, and Dm, which reflect temporal and spatial diffusion heterogeneity, and anomalous diffusion coefficient, respectively (12)(13)(14). Due to the advantages of the CTRW model in characterizing non-Gaussian diffusion behavior, it has been applied in recent studies for the assessment of glioma grading (15), the differentiation of high-and low-grade pediatric brain tumors (16), and the differentiation and prognostic assessment of benign and malignant breast lesions (17). Notably, no study has yet applied the CTRW model to prostate diseases.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of prostatic cancer lesion and gleason grade using a continuous-time random-walk diffusion model at high b-values

Sheng,

Chang,

Xue

et al. 2024

Front. Oncol.

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BackgroundDistinguishing between prostatic cancer (PCa) and chronic prostatitis (CP) is sometimes challenging, and Gleason grading is strongly associated with prognosis in PCa. The continuous-time random-walk diffusion (CTRW) model has shown potential in distinguishing between PCa and CP as well as predicting Gleason grading.PurposeThis study aimed to quantify the CTRW parameters (α, β & Dm) and apparent diffusion coefficient (ADC) of PCa and CP tissues; and then assess the diagnostic value of CTRW and ADC parameters in differentiating CP from PCa and low-grade PCa from high-grade PCa lesions.Study typeRetrospective (retrospective analysis using prospective designed data).PopulationThirty-one PCa patients undergoing prostatectomy (mean age 74 years, range 64–91 years), and thirty CP patients undergoing prostate needle biopsies (mean age 68 years, range 46–79 years).Field strength/SequenceMRI scans on a 3.0T scanner (uMR790, United Imaging Healthcare, Shanghai, China). DWI were acquired with 12 b-values (0, 50, 100, 150, 200, 500, 800, 1200, 1500, 2000, 2500, 3000 s/mm2).AssessmentCTRW parameters and ADC were quantified in PCa and CP lesions.Statistical testsThe Mann-Whitney U test was used to evaluate the differences in CTRW parameters and ADC between PCa and CP, high-grade PCa, and low-grade PCa. Spearman’s correlation of the pathologic grading group (GG) with CTRW parameters and ADC was evaluated. The usefulness of CTRW parameters, ADC, and their combinations (Dm, α and β; Dm, α, β, and ADC) to differentiate PCa from CP and high-grade PCa from low-grade PCa was determined by logistic regression and receiver operating characteristic curve (ROC) analysis. Delong test was used to compare the differences among AUCs.ResultsSignificant differences were found for the CTRW parameters (α, Dm) between CP and PCa (all P<0.001), high-grade PCa, and low-grade PCa (α:P=0.024, Dm:P=0.021). GG is correlated with certain CTRW parameters and ADC(α:P<0.001,r=-0.795; Dm:P<0.001,r=-0.762;ADC:P<0.001,r=-0.790). Moreover, CTRW parameters (α, β, Dm) combined with ADC showed the best diagnostic efficacy for distinguishing between PCa and CP as well as predicting Gleason grading. The differences among AUCs of ADC, CTRW parameters and their combinations were not statistically significant (P=0.051–0.526).ConclusionCTRW parameters α and Dm, as well as their combination were beneficial to distinguish between CA and PCa, low-grade PCa and high-grade PCa lesions, and CTRW parameters and ADC had comparable diagnostic performance.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Characterization of prostatic cancer lesion and gleason grade using a continuous-time random-walk diffusion model at high b-values

Sheng,

Chang,

Xue

et al. 2024

Front. Oncol.

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“…The positive correlation between cell density and tumor grade can explain the ability of DWI to assess ASPS histological grade. In breast cancer, hepatocellular carcinoma, cervical cancer, and other solid tumors, ADC values have been reported to be negatively correlated with Ki-67 expression [ 20 – 22 ]. Lee et al [ 23 ] first found a weak negative correlation between ADC values and Ki-67 expression in STS, and in subsequent reports, Yuan et al [ 24 ] found a moderate negative correlation between ADC and D values and Ki-67 expression in a rhabdomyosarcoma mouse model.…”

Section: Discussionmentioning

confidence: 99%

Qualitative and quantitative MRI analysis of alveolar soft part sarcoma: correlation with histological grade and Ki-67 expression

Yuan,

Xie,

Fang

et al. 2024

Insights Imaging

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Objective To investigate the correlation between MRI findings and histological features for preoperative prediction of histological grading and Ki-67 expression level in alveolar soft part sarcoma (ASPS). Methods A retrospective analysis was conducted on 63 ASPS patients (Jan 2017–May 2023). All patients underwent 3.0-T MRI examinations, including conventional sequences, dynamic contrast-enhanced scans with time-intensity curve analysis, and diffusion-weighted imaging with apparent diffusion coefficient (ADC) measurements. Patients were divided into low-grade (histological Grade I) and high-grade (histological Grade II/III) groups based on pathology. Immunohistochemistry was used to assess Ki-67 expression levels in ASPS. Statistical analysis included chi-square tests, Wilcoxon rank-sum test, binary logistic regression analysis, Spearman correlation analysis, and receiver operating characteristic curve analysis of various observational data. Results There were 29 low-grade and 34 high-grade patients (26 males and 37 females) and a wide age range (5–68 years). Distant metastasis, tumor enhancement characteristics, and ADC values were independent predictors of high-grade ASPS. High-grade ASPS had lower ADC values (p = 0.002), with an area under the curve (AUC), sensitivity, and specificity of 0.723, 79.4%, and 58.6%, respectively, for high-grade prediction. There was a negative correlation between ADC values and Ki-67 expression (r = −0.526; p < 0.001). When the cut-off value of ADC was 0.997 × 10−3 mm²/s, the AUC, sensitivity, and specificity for predicting high Ki-67 expression were 0.805, 65.6%, and 83.9%, respectively. Conclusion Qualitative and quantitative MRI parameters are valuable for predicting histological grading and Ki-67 expression levels in ASPS. Critical relevance statement This study will help provide a more nuanced understanding of ASPS and guide personalized treatment strategies. Key Points There is limited research on assessing ASPS prognosis through MRI. Metastasis, enhancement, and ADC correlated with histological grade; ADC related to Ki-67 expression. MRI provides clinicians with valuable information on ASPS grading and proliferation activity. Graphical Abstract

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“…The standardized mean difference in ADC with a 95% confidence interval was used as a summary statistic for ER, PgR, and HER2 categories. A total of 52 articles [ 3 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 ] were finally reviewed and quantitatively summarized ( Fig. 1 ).…”

Section: Relationship Between Adc and Hormone Receptor Status Of Brea...mentioning

confidence: 99%

“…A forest plot of the mean differences in ADCs between ER-positive and -negative breast cancers from 44 studies [ 3 13 14 16 17 18 19 20 21 22 24 26 27 28 29 30 31 32 33 34 35 36 37 38 41 42 43 44 45 46 47 48 49 50 51 52 53 54 56 57 58 59 60 61 ] is given in Figure 2A . There was large heterogeneity among the studies (I 2 = 80%), but overall, ER-positive cancers exhibited significantly lower ADCs than ER-negative cancers ( P < 0.01).…”

Section: Relationship Between Adc and Hormone Receptor Status Of Brea...mentioning

confidence: 99%

Diffusion-Weighted MRI for the Assessment of Molecular Prognostic Biomarkers in Breast Cancer

Iima,

Kataoka,

Honda

et al. 2024

Korean J Radiol

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Evaluation of breast cancer malignancy, prognostic factors and molecular subtypes using a continuous-time random-walk MR diffusion model

Cited by 5 publications

References 33 publications

Characterization of prostatic cancer lesion and gleason grade using a continuous-time random-walk diffusion model at high b-values

Characterization of prostatic cancer lesion and gleason grade using a continuous-time random-walk diffusion model at high b-values

Qualitative and quantitative MRI analysis of alveolar soft part sarcoma: correlation with histological grade and Ki-67 expression

Diffusion-Weighted MRI for the Assessment of Molecular Prognostic Biomarkers in Breast Cancer

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