scholarly journals Histogram Analysis and Visual Heterogeneity of Diffusion-Weighted Imaging with Apparent Diffusion Coefficient Mapping in the Prediction of Molecular Subtypes of Invasive Breast Cancers

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Joao V. Horvat ◽  
Aditi Iyer ◽  
Elizabeth A. Morris ◽  
Aditya Apte ◽  
Blanca Bernard-Davila ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Diffusion Weighted Imaging ◽  
Triple Negative ◽  
Molecular Subtypes ◽  
Histogram Analysis ◽  
Breast Cancers ◽  
Luminal A ◽  
Diffusion Weighted ◽  
Apparent Diffusion

Objective. To investigate if histogram analysis and visually assessed heterogeneity of diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping can predict molecular subtypes of invasive breast cancers. Materials and Methods. In this retrospective study, 91 patients with invasive breast carcinoma who underwent preoperative magnetic resonance imaging (MRI) with DWI at our institution were included. Two radiologists delineated a 2-D region of interest (ROI) on ADC maps in consensus. Tumors were also independently classified into low and high heterogeneity based on visual assessment of DWI. First-order statistics extracted through histogram analysis within the ROI of the ADC maps (mean, 10th percentile, 50th percentile, 90th percentile, standard deviation, kurtosis, and skewness) and visually assessed heterogeneity were evaluated for associations with tumor receptor status (ER, PR, and HER2 status) as well as molecular subtype. Results. HER2-positive lesions demonstrated significantly higher mean (p=0.034), Perc50 (p=0.046), and Perc90 (p=0.040), with AUCs of 0.605, 0.592, and 0.652, respectively, than HER2-negative lesions. No significant differences were found in the histogram values for ER and PR statuses. Neither quantitative histogram analysis based on ADC maps nor qualitative visual heterogeneity assessment of DWI images was able to significantly differentiate between molecular subtypes, i.e., luminal A versus all other subtypes (luminal B, HER2-enriched, and triple negative) combined, luminal A and B combined versus HER2-enriched and triple negative combined, and triple negative versus all other types combined. Conclusion. Histogram analysis and visual heterogeneity assessment cannot be used to differentiate molecular subtypes of invasive breast cancer.

scholarly journals Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging

2021 ◽  
Vol 11 ◽  
Author(s):  
Chengru Song ◽  
Peng Cheng ◽  
Jingliang Cheng ◽  
Yong Zhang ◽  
Shanshan Xie
Keyword(s):  
Diffusion Coefficient ◽  
Nasopharyngeal Carcinoma ◽  
Apparent Diffusion Coefficient ◽  
Diffusion Weighted Imaging ◽  
Diagnostic Performance ◽  
Validation Cohort ◽  
Statistical Significance ◽  
Histogram Analysis ◽  
Diffusion Weighted ◽  
Apparent Diffusion

BackgroundThis study aims to explore the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis for differentiating nasopharyngeal lymphoma (NPL) from nasopharyngeal carcinoma (NPC) following readout-segmented echo-planar diffusion-weighted imaging (RESOLVE sequence).MethodsThirty-eight patients with NPL and 62 patients with NPC, who received routine head-and-neck MRI and RESOLVE (b-value: 0 and 1,000 s/mm2) examinations, were retrospectively evaluated as derivation cohort (February 2015 to August 2018); another 23 patients were analyzed as validation cohort (September 2018 to December 2019). The RESOLVE data were obtained from the MAGNETOM Skyra 3T MR system (Siemens Healthcare, Erlangen, Germany). Fifteen parameters derived from the whole-lesion histogram analysis (ADCmean, variance, skewness, kurtosis, ADC1, ADC10, ADC20, ADC30, ADC40, ADC50, ADC60, ADC70, ADC80, ADC90, and ADC99) were calculated for each patient. Then, statistical analyses were performed between the two groups to determine the statistical significance of each histogram parameter. A receiver operating characteristic curve (ROC) analysis was conducted to assess the diagnostic performance of each histogram parameter for distinguishing NPL from NPC and further tested in the validation cohort; calibration of the selected parameter was tested with Hosmer–Lemeshow test.ResultsNPL exhibited significantly lower ADCmean, variance, ADC1, ADC10, ADC20, ADC30, ADC40, ADC50, ADC60, ADC70, ADC80, ADC90 and ADC99, when compared to NPC (all, P < 0.05), while no significant differences were found on skewness and kurtosis. Furthermore, ADC99 revealed the highest diagnostic efficiency, followed by ADC10 and ADC20. Optimal diagnostic performance (AUC = 0.790, sensitivity = 91.9%, and specificity = 63.2%) could be achieved when setting ADC99 = 1,485.0 × 10−6 mm2/s as the threshold value. The predictive performance was maintained in the validation cohort (AUC = 0.817, sensitivity = 94.6%, and specificity = 56.2%)ConclusionWhole-lesion ADC histograms based on RESOLVE are effective in differentiating NPC from NPL.

scholarly journals Classification of paediatric brain tumours by diffusion weighted imaging and machine learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jan Novak ◽  
Niloufar Zarinabad ◽  
Heather Rose ◽  
Theodoros Arvanitis ◽  
Lesley MacPherson ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Posterior Fossa ◽  
Brain Tumours ◽  
Diffusion Weighted Imaging ◽  
Regions Of Interest ◽  
Apparent Diffusion Coefficients ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Paediatric Brain Tumours

AbstractTo determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10−3 mm2 s−1 with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.

scholarly journals Diffusion-Weighted Imaging of Different Breast Cancer Molecular Subtypes: A Systematic Review and Meta-Analysis

Breast Care ◽  
2021 ◽  
pp. 1-8
Author(s):  
Hans-Jonas Meyer ◽  
Andreas Wienke ◽  
Alexey Surov
Keyword(s):  
Breast Cancer ◽  
Systematic Review ◽  
Diffusion Weighted Imaging ◽  
Triple Negative ◽  
Molecular Subtypes ◽  
Luminal A ◽  
Diagnose Breast Cancer ◽  
Luminal B ◽  
Diffusion Weighted ◽  
Adc Values

Background: Magnetic resonance imaging can be used to diagnose breast cancer (BC).Diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Objectives: This analysis aimed to compare ADC values between molecular subtypes of BC based on a large sample of patients. Method: The MEDLINE library and Scopus database were screened for the associations between ADC and molecular subtypes of BC up to April 2020. The primary end point of the systematic review was the ADC value in different BC subtypes. Overall, 28 studies were included. Results: The included studies comprised a total of 2,990 tumors. Luminal A type was diagnosed in 865 cases (28.9%), luminal B in 899 (30.1%), human epidermal growth factor receptor (Her2)-enriched in 597 (20.0%), and triple-negative in 629 (21.0%). The mean ADC values of the subtypes were as follows: luminal A: 0.99 × 10–3 mm2/s (95% CI 0.94–1.04), luminal B: 0.97 × 10–3 mm2/s (95% CI 0.89–1.05), Her2-enriched: 1.02 × 10–3 mm2/s (95% CI 0.95–1.08), and triple-negative: 0.99 × 10–3 mm2/s (95% CI 0.91–1.07). Conclusions: ADC values cannot be used to discriminate between molecular subtypes of BC.

scholarly journals The role of quantitative diffusion-weighted imaging in characterization of hypovascular liver lesions: A prospective comparison of intravoxel incoherent motion derived parameters and apparent diffusion coefficient

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247301
Author(s):  
Jelena Djokić Kovač ◽  
Marko Daković ◽  
Aleksandra Janković ◽  
Milica Mitrović ◽  
Vladimir Dugalić ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Liver Metastases ◽  
Diffusion Weighted Imaging ◽  
Intraclass Correlation ◽  
Intravoxel Incoherent Motion ◽  
Liver Lesions ◽  
Diffusion Weighted ◽  
Significant Difference ◽  
Apparent Diffusion

Background The utility of intravoxel incoherent motion (IVIM) related parameters in differentiation of hypovascular liver lesions is still unknown. Purpose The purpose of this study was to evaluate the value of IVIM related parameters in comparison to apparent diffusion coefficient (ADC) for differentiation among intrahepatic mass-forming cholangiocarcinoma (IMC), and hypovascular liver metastases (HLM). Methods Seventy-four prospectively enrolled patients (21 IMC, and 53 HLM) underwent 1.5T magnetic resonance examination with IVIM diffusion-weighted imaging using seven b values (0–800 s/mm2). Two independent readers performed quantitative analysis of IVIM-related parameters and ADC. Interobserver reliability was tested using a intraclass correlation coefficient. ADC, true diffusion coefficient (D), perfusion-related diffusion coefficient (D*), and perfusion fraction (ƒ) were compared among the lesions using Kruskal-Wallis H test. The diagnostic accuracy of each parameter was assessed by receiver operating characteristic (ROC) curve analysis. Results The interobserver agreement was good for ADC (0.802), and excellent for D, D*, and ƒ (0.911, 0.927, and 0.942, respectively). ADC, and D values were significantly different among IMC and HLM (both p < 0.05), while there was no significant difference among these lesions for ƒ and D* (p = 0.101, and p = 0.612, respectively). ROC analysis showed higher diagnostic performance of D in comparison to ADC (AUC = 0.879 vs 0.821). Conclusion IVIM-derived parameters in particular D, in addition to ADC, could help in differentiation between most common hypovascular malignant liver lesions, intrahepatic mass—forming cholangiocarcinoma and hypovascular liver metastases.

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