Evaluation of Malignant Breast Lesions Using High-resolution Readout-segmented Diffusion-weighted Echo-planar Imaging: Comparison with Pathology

Histogram analysis comparison of readout-segmented and single-shot echo-planar imaging for differentiating luminal from non-luminal breast cancer

To compare diffusion-kurtosis imaging (DKI) and diffusion-weighted imaging (DWI) parameters of single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI) in the differentiation of luminal vs. non-luminal breast cancer using histogram analysis. One hundred and sixty women with 111 luminal and 49 non-luminal breast lesions were enrolled in this study. All patients underwent ss-EPI and rs-EPI sequences on a 3.0T scanner. Histogram metrics were derived from mean kurtosis (MK), mean diffusion (MD) and the apparent diffusion coefficient (ADC) maps of two DWI sequences respectively. Student's t test or Mann-Whitney U test was performed for differentiating luminal subtype from non-luminal subtype. The ROC curves were plotted for evaluating the diagnostic performances of significant histogram metrics in differentiating luminal from non-luminal BC. The histogram metrics MKmean, MK50th, MK75th of luminal BC were significantly higher than those of non-luminal BC for both two DWI sequences (all P<0.05). Histogram metrics from rs-EPI sequence had better diagnostic performance in differentiating luminal from non-Luminal breast cancer compared to those from ss-EPI sequence. MK75th derived from rs-EPI sequence was the most valuable single metric (AUC, 0.891; sensitivity, 78.4%; specificity, 87.8%) for differentiating luminal from non-luminal BC among all the histogram metrics. Histogram metrics of MK derived from rs-EPI yielded better diagnostic performance for distinguishing luminal from non-luminal BC than that from ss-EPI. MK75th was the most valuable metric among all the histogram metrics.

Multiparametric Approach to Breast Cancer With Emphasis on Magnetic Resonance Imaging in the Era of Personalized Breast Cancer Treatment

ABSTRACT

A multiparametric approach to breast cancer imaging offers the advantage of integrating the diverse contributions of various parameters. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most important MRI sequence for breast imaging. The vascularity and permeability of lesions can be estimated through the use of semiquantitative and quantitative parameters. The increased use of ultrafast DCE-MRI has facilitated the introduction of novel kinetic parameters. In addition to DCE-MRI, diffusion-weighted imaging provides information associated with tumor cell density, with advanced diffusion-weighted imaging techniques such as intravoxel incoherent motion, diffusion kurtosis imaging, and time-dependent diffusion MRI opening up new horizons in microscale tissue evaluation. Furthermore, T2-weighted imaging plays a key role in measuring the degree of tumor aggressiveness, which may be related to the tumor microenvironment. Magnetic resonance imaging is, however, not the only imaging modality providing semiquantitative and quantitative parameters from breast tumors. Breast positron emission tomography demonstrates superior spatial resolution to whole-body positron emission tomography and allows comparable delineation of breast cancer to MRI, as well as providing metabolic information, which often precedes vascular and morphological changes occurring in response to treatment. The integration of these imaging-derived factors is accomplished through multiparametric imaging. In this article, we explore the relationship among the key imaging parameters, breast cancer diagnosis, and histological characteristics, providing a technical and theoretical background for these parameters. Furthermore, we review the recent studies on the application of multiparametric imaging to breast cancer and the significance of the key imaging parameters.

Intraobserver and Interobserver Reproducibility of Breast Diffusion-Weighted Imaging Quantitative Parameters: Readout-Segmented vs. Single-Shot Echo-Planar Imaging

BACKGROUND

The recommended technique for breast diffusion-weighted imaging (DWI) acquisitions is not sufficiently standardized in clinical practice.

PURPOSE

To investigate the intraobserver and interobserver reproducibility of DWI measurements, diffusion-kurtosis imaging (DKI) parameters, and image quality evaluation in breast lesions between single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI).

STUDY TYPE

Prospective.

POPULATION

A total of 295 women with 209 malignant and 86 benign breast lesions.

FIELD STRENGTH/SEQUENCE

A 3-T; fat-saturated T2-weighted MR imaging (T2WI); multi-b-value DWI with both ss-EPI and rs-EPI readouts; T1-weighted dynamic contrast-enhanced MRI (DCE-MRI).

ASSESSMENT

Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values were measured for each lesion on ss-EPI and rs-EPI, respectively. Image quality was visually evaluated regarding image sharpness, geometric distortion, lesion conspicuity, visualization of anatomic structures, and overall quality. Quantitative and qualitative analyses were performed twice with a time interval of 2 weeks.

STATISTICAL TESTS

Intraobserver and interobserver reproducibility were evaluated using intra-class correlation coefficients (ICC), within-subject coefficient of variation (wCV), and Bland-Altman plots.

RESULTS

MK, MD, and ADC quantitative parameters for breast lesions showed excellent intraobserver and interobserver reproducibility, with ICCs >0.75 and wCV values ranging from 2.51% to 7.08% for both sequences. The wCV values in both intraobserver and interobserver measurements were higher in the ss-EPI sequence (3.63%-7.08%) than that of the rs-EPI sequence (2.51%-3.62%). The wCV values differed in subgroups with different histopathological types of lesions, breast density, lesion morphology, and lesion sizes, respectively. Furthermore, rs-EPI (ICCs, 0.76-0.97; wCV values, 2.41%-6.04%) had better intraobserver and interobserver reproducibility than ss-EPI (ICCs, 0.54-0.90; wCV values, 6.18%-13.69%) with regard to image quality.

DATA CONCLUSION

Compared to the ss-EPI, the rs-EPI sequence showed higher intraobserver and interobserver reproducibility for quantitative diffusion-related parameters and image quality assessments measured in breast DWI and DKI.

EVIDENCE LEVEL

2.

TECHNICAL EFFICACY

Stage 2.

Feasibility of high-resolution readout-segmented echo-planar imaging with simultaneous multislice imaging in assessing rectal cancer

PURPOSE

To investigate the feasibility of high-resolution readout-segmented echo-planar imaging (rs-EPI) with simultaneous multislice (SMS) imaging to predict well-differentiated rectal cancer.Kindly check and confirm whether the Author Name 'Hongyun Huang ' is correctly identified.confirm METHODS: A total of eighty-three patients with nonmucinous rectal adenocarcinoma received both prototype SMS high-spatial-resolution and conventional rs-EPI sequences. Image quality was subjectively assessed by two experienced radiologists using a 4-point Likert scale (1 = poor, 4 = excellent). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and apparent diffusion coefficient (ADC) of the lesion were measured by two experienced radiologists in the objective assessment. Paired t tests or Mann‒Whitney U tests were used to compare the two groups. The areas under the receiver operating characteristic (ROC) curves (AUCs) were used to determine the predictive value of the ADCs in discriminating well-differentiated rectal cancer in the two groups. A two-sided p value < 0.05 represented statistical significance.Please check and confirm if the authors and affiliation details have been correctly identified. Amend if necessary.confirm RESULTS: In the subjective assessment, high-resolution rs-EPI had better image quality than conventional rs-EPI (p < 0.001). High-resolution rs-EPI also had a significantly higher SNR and CNR (p < 0.001). The T stage of rectal cancer was inversely correlated with the ADCs measured on high-resolution rs-EPI (r = -0.622, p < 0.001) and rs-EPI (r = -0.567, p < 0.001). The AUC of high-resolution rs-EPI in predicting well-differentiated rectal cancer was 0.768.

CONCLUSION

High-resolution rs-EPI with SMS imaging provided significantly higher image quality, SNRs, and CNRs and more stable ADC measurements than conventional rs-EPI. Additionally, the pretreatment ADC on high-resolution rs-EPI could discriminate well-differentiated rectal cancer.

Diagnostic Utility of an Adjusted DWI Lexicon Using Multiple b-values to Evaluate Breast Lesions in Combination with BI-RADS

PURPOSE

We aimed to investigate the diagnostic feasibility of an adjusted diffusion-weighted imaging (DWI) lexicon using multiple b values to assess breast lesions according to DWI-based breast imaging reporting and data system (BI-RADS).

METHODS

This Institutional Review Board (IRB)-approved prospective study included 127 patients with suspected breast cancer. Breast MRI was performed using a 3T scanner. Breast DW images were acquired using five b-values of 0, 200, 800, 1000, and 1500 s/mm² (5b-value DWI) on 3T MRI. Two readers independently assessed lesion characteristics and normal breast tissue using DWI alone (5b-value DWI and 2b-value DWI with b = 0 and 800 s/mm²) according to DWI-based BI-RADS and in combination with the standard dynamic contrast-enhanced images (combined MRI). Interobserver and intermethod agreements were assessed using kappa statistics. The specificity and sensitivity of lesion classification were evaluated.

RESULTS

Ninety-five breast lesions (39 malignant and 56 benign) were evaluated. Interobserver agreement for lesion assessment on 5b-value DWI was very good (k ≥ 0.82) for DWI-based BI-RADS categories, lesion type, and mass characteristics; good (k = 0.75) in breast composition; and moderate (k ≥ 0.44) in background parenchymal signal (BPS) and non-mass distribution. Intermethod agreement between assessments performed using either 5b-value DWI or combined MRI was good-to-moderate (k = 0.52-0.67) for lesion type; moderate (k = 0.49-0.59) for DWI-based BI-RADS category and mass characteristics; and fair (k = 0.25-0.40) for mass shape, BPS, and breast composition. The sensitivity and positive predictive values (PPVs) for 5b-value DWI were 79.5%, 84.6% and 60.8%, 61.1% for each reader, respectively; 74.4%, 74.4% and 63.0%, 61.7% for 2b-value DWI; and 97.4%, 97.4% and 73.1%, 76.0% for combined MRI. The specificity and negative predictive values (NPVs) were 64.3%, 62.5% and 81.8%, 85.4% for 5b-value DWI; 69.6%, 67.9% and 79.6%, 79.2% for 2b-value DWI; and 75.0%, 78.6% and 97.7%, 97.8% for combined MRI.

CONCLUSION

Good observer agreement was observed in the 5b-value DWI. The 5b-value DWI based on multiple b-values might have the potential to complement the 2b-value DWI; however, their diagnostic performance tended to be inferior to that of combined MRI for the characterization of breast tumors.

Evaluation of breast lesions based on modified BI-RADS using high-resolution readout-segmented diffusion-weighted echo-planar imaging and T2/T1-weighted image

PURPOSE

To evaluate the diagnostic performance of a non-contrast magnetic resonance imaging (MRI) protocol combining high-resolution diffusion-weighted images (HR-DWI) using readout-segmented echo planar imaging, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI), using our modified Breast Imaging-Reporting and Data System (modified BI-RADS).

METHODS

Two experienced radiologists, blinded to the final pathological diagnosis, categorized a total of 108 breast lesions (61 malignant and 47 benign) acquired with the above protocol using the modified BI-RADS with a diagnostic decision tree. The decision tree included subcategories of category 4, as in mammography (categories 2, 3, 4A, 4B, 4C, and 5). These results were compared with the pathological diagnoses.

RESULTS

The area under the ROC curve (AUC) was 0.89 (95% confidence interval [CI]: 0.83-0.95) for reader 1, and 0.89 (95% CI: 0.82-0.96) for reader 2. When categories 4C and above were classified as malignant, the sensitivity, specificity, and accuracy were 73.8%, 93.6%, and 82.4%, for reader 1; and 82.0%, 89.4%, and 85.2% for reader 2, respectively.

CONCLUSION

Our results suggest that using HR-DWI, T1WI/T2WI analyzed with a modified BI-RADS and a decision tree showed promising diagnostic performance in breast lesions, and is worthy of further study.

High-resolution diffusion-weighted imaging compared with conventional diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging with regard to image quality and assessment of breast cancer morphology

PURPOSE

To evaluate the image quality and tumor morphology depiction ability of high resolution (HR) diffusion- weighted imaging (f-DWI) in comparison to conventional DWI (c-DWI) and dynamic contrast- enhanced magnetic resonance imaging (DCE-MRI) in the primary breast cancer setting.

METHODS

The f-DWI, c-DWI, and DCE-MRIs of 160 malignant breast masses were evaluated retrospectively by two independent radiologists. Data on image quality [sharpness, distortion, and perceived signalto- noise ratio (SNR)], apparent diffusion coefficient (ADC) value, lesion size, and tumor morphology (shape, margin, and internal pattern) obtained on f-DWI, c-DWI, and DCE-MRI were compared. Consistency between the readers and imaging methods for morphological parameters was analyzed.

RESULTS

The ADC values measured on f-DWI were significantly lower than those measured on c-DWI for both readers (P < 0.001 for each), whereas mean lesion size was significantly larger in c-DWI than in f-DWI and DCE-MRI for both readers (P < 0.001 for each). Higher consistency values were obtained for f-DWI compared with c-DWI when correlated with DCE-MRI for each morphological parameter. The least distorted images were obtained using DCE-MRI compared with c-DWI and f-DWI for both readers, whereas the highest distortion scores were obtained using c-DWI. Sharpness and perceived SNR scores were rated as significantly higher for f-DWI and DCE-MRI images compared with c-DWI by both readers (P < 0.001 for all). The concordance between c-DWI and DCE-MRI was fair to slight (κ = 0.15 to 0.41), whereas concordance between f-DWI and DCE-MRI was significantly better (κ = 0.68 to 0.87) for each reader and for all morphological parameters (P < 0.001). The highest concordance between the readers was achieved in margin assessment (κ = 0.87 to 0.89) regardless of the MRI method, followed by shape and internal pattern parameters (κ = 0.63 to 0.79).

CONCLUSION

The results demonstrated that f-DWI produces higher-quality images than c-DWI, enabling the morphological features to be identified in similar detail to that offered by HR DCE-MRI. Accordingly, f-DWI, as a method that highly correlates with DCE in determining the morphological characteristics of breast cancers, seems to have potential in the evaluation of breast tumors in patients for whom the use of contrast media is contraindicated.

Evaluation of apparent diffusion coefficient of two-dimensional BLADE turbo gradient- and spin-echo diffusion-weighted imaging with a breast phantom

This study aimed to evaluate the reliability of apparent diffusion coefficient (ADC) values generated with two-dimensional turbo gradient- and spin-echo with BLADE trajectory diffusion-weighted imaging (TGSE-BLADE-DWI) sequence using a breast diffusion phantom. TGSE-BLADE-DWI and single-shot spin-echo echo-planar imaging (SS-EPI-DWI) were performed using a 3.0 T magnetic resonance imaging scanner. Concordance rates of ADC values and the signal-to-noise ratio (SNR) were compared between TGSE-BLADE-DWI and SS-EPI-DWI. TGSE-BLADE-DWI provided a higher concordance rate for ADC values than SS-EPI-DWI when b-values > 2000s/mm² and a slice thickness of 1 mm were used. TGSE-BLADE-DWI showed less image distortion than SS-EPI-DWI. The SNR of TGSE-BLADE-DWI was higher than that of SS-EPI-DWI, except at a number of excitations of 7 and a slice thickness of 1 mm. In conclusion, TGSE-BLADE-DWI can offer a better SNR, less distortion, and more reliable ADC measurements than SS-EPI-DWI in a breast phantom.

Preoperative Localization of Parathyroid Adenomas with Diffusion MR Imaging: Readout-segmented versus Single-shot Echo-planar Imaging

PURPOSE

To evaluate whether readout-segmented echo-planar imaging (RS-EPI) diffusion-weighted imaging (DWI) can reduce image distortion and improve the lesion identification in parathyroid adenomas (PTAs) compared to single-shot EPI (SS-EPI) DWI, and to determine whether PTAs can be differentiated from other soft tissue structures of the head and neck region by using the apparent diffusion coefficient (ADC) value.

METHODS

We retrospectively analyzed the preoperative MR images including DWI of 24 patients with surgically confirmed PTA. RS-EPI and SS-EPI DWI were evaluated by two independent readers for the identification of the lesions and distortion. The ADC values of the PTAs were compared with those of thyroid glands and cervical lymph nodes.

RESULTS

RS-EPI provided significantly less distortion compared to SS-EPI. RS-EPI tended to have better lesion identification compared with SS-EPI without a statistically significant difference. On SS-EPI, the PTAs had significantly higher ADC values compared with the cervical lymph nodes. On RS-EPI, the PTAs had significantly higher ADC values compared with the thyroid glands and cervical lymph nodes.

CONCLUSION

RS-EPI reduces the DWI distortion in PTAs. The ADC value obtained using RS-EPI enables the differentiation of PTAs from nearby structures, such as thyroid glands and cervical lymph nodes.

MR Imaging in the 21st Century: Technical Innovation over the First Two Decades

Clinical MRI systems have continually improved over the years since their introduction in the 1980s. In MRI technical development, the developments in each MRI system component, including data acquisition, image reconstruction, and hardware systems, have impacted the others. Progress in each component has induced new technology development opportunities in other components. New technologies outside of the MRI field, for example, computer science, data processing, and semiconductors, have been immediately incorporated into MRI development, which resulted in innovative applications. With high performance computing and MR technology innovations, MRI can now provide large volumes of functional and anatomical image datasets, which are important tools in various research fields. MRI systems are now combined with other modalities, such as positron emission tomography (PET) or therapeutic devices. These hybrid systems provide additional capabilities.

In this review, MRI advances in the last two decades will be considered. We will discuss the progress of MRI systems, the enabling technology, established applications, current trends, and the future outlook.

Detection and Classification of Breast Lesions With Readout-Segmented Diffusion-Weighted Imaging in a Large Chinese Cohort

Objectives: To evaluate the performance of readout-segmented echo-planar imaging DWI (rs-EPI DWI) in detecting and characterizing breast cancers in a large Chinese cohort with comparison to dynamic contrast-enhanced MRI (DCE-MRI). Methods: The institutional review board approved this retrospective study with waived written informed consent. A total of 520 women (mean age, 43.1- ± 10.5-years) were included from July 2013 to October 2019. First, the ability of rs-EPI DWI in detecting breast lesions identified by DCE-MRI was evaluated. The lesion conspicuity of rs-EPI-DWI and DCE-MRI was compared using the Wilcoxon signed rank test. With pathology as a reference, the performance of rs-EPI DWI and DCE-MRI in distinguishing breast cancers was evaluated and compared using the Chi-square test. Results: Of 520 women, 327/520 (62.9%) patients had 423 lesions confirmed by pathology with 203 benign and 220 malignant lesions. The rs-EPI DWI can detect 90.8% (659/726) (reader 1) and 90.6% (663/732) (reader 2) of lesions identified by DCE-MRI. The lesion visibility was superior for DCE-MRI than rs-EPI-DWI (all p < 0.05). With pathology as a reference, the sensitivities and specificities of rs-EPI DWI in diagnosing breast cancers were 95.9% (211/220) and 85.7% (174/203) for reader 1 and 97.7% (215/220) and 86.2% (175/203) for reader 2. No significant differences were found for the performance of DCE-MRI and rs-EPI DWI in discriminating breast cancers (all p > 0.05). Conclusions: Although with an inferior lesion visibility, rs-EPI DWI can detect about 90% of breast lesions identified by DCE-MRI and has comparable diagnostic capacity to that of DCE-MRI in identifying breast cancer.

The Diagnostic Performance of Diffusion Kurtosis Imaging in the Characterization of Breast Tumors: A Meta-Analysis

Rationale and Objectives: Diffusion kurtosis imaging (DKI) is a promising imaging technique, but the results regarding the diagnostic performance of DKI in the characterization and classification of breast tumors are inconsistent among published studies. This study aimed to pool all published results to provide more robust evidence of the differential diagnosis between malignant and benign breast tumors using DKI. Methods: Studies on the differential diagnosis of breast tumors using DKI-derived parameters were systemically retrieved from PubMed, Embase, and Web of Science without a time limit. Review Manager 5.3 was used to calculate the standardized mean differences (SMDs) and 95% confidence intervals of the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC). Stata 12.0 was used to pool the sensitivity, specificity, and diagnostic odds ratio (DOR) as well as the publication bias and heterogeneity of each parameter. Fagan's nomograms were plotted to predict the post-test probabilities. Results: Thirteen studies including 867 malignant and 460 benign breast lesions were analyzed. Most of the included studies showed a low to unclear risk of bias and low concerns regarding applicability. Breast cancer showed a higher MK (SMD = 1.23, P < 0.001) but a lower MD (SMD = -1.29, P < 0.001) and ADC (SMD = -1.21, P < 0.001) than benign tumors. The MK (SMD = -1.36, P = 0.006) rather than the MD (SMD = 0.29, P = 0.20) or ADC (SMD = 0.26, P = 0.24) can further differentiate invasive ductal carcinoma from ductal carcinoma in situ. The DKI-derived MK (sensitivity = 90%, specificity = 88%, DOR = 66) and MD (sensitivity = 86% and specificity = 88%, DOR = 46) demonstrated superior diagnostic performance and post-test probability (65, 64, and 56% for MK, MD, and ADC) in differentiating malignant from benign breast lesions, with a higher sensitivity and specificity than the DWI-derived ADC (sensitivity = 85% and specificity = 83%, DOR = 29). Conclusion: The DKI-derived MK and MD demonstrate a comparable diagnostic performance in the discrimination of breast tumors based on their microstructures and non-Gaussian characteristics. The MK can further differentiate invasive ductal carcinoma from ductal carcinoma in situ.

The comparison of high-resolution diffusion weighted imaging (DWI) with high-resolution contrast-enhanced MRI in the evaluation of breast cancers

PURPOSE

We sought to investigate the performance of high resolution (HR) diffusion-weighted imaging (DWI) using readout-segmented echo-planar imaging (rs-EPI), compared with high-resolution contrast-enhanced MRI (HR CE-MRI) in terms of morphological accuracy, on the basis of the Breast Imaging and Reporting and Data System (BI-RADS) MRI descriptors and lesion size.

METHODS

This retrospective study included the image data of 94 patients with surgically confirmed malignant breast lesions who had undergone high resolution diffusion-weighted imaging (HR-DWI) and HR CE-MRI. Two radiologists blinded to the final diagnosis independently identified the lesions on HR-DWI, described the morphology of the lesions according to BI-RADS descriptors, and measured lesion size. HR CE-MRI was subsequently evaluated using the same procedure. The inter-method agreement of the morphology was assessed using kappa statistics. Correlation on size was also assessed.

RESULTS

Reader A detected 79 mass lesions and 37 non-mass lesions on HR-DWI and HR CE-MRI. Reader B detected 81 mass lesions and 33 non-mass lesions on HR-DWI and HR CE-MRI. Very high agreement (kappa = 0.81-0.89, p < .05) was observed in the shape and margin assessment of mass lesions, where agreement on internal enhancement/signals was moderate to substantial (kappa = 0.43-0.61, p < .05). Disagreement was mostly seen in the evaluation of rim enhancement. High agreement was observed for non-mass lesion distribution (kappa = 0.76-0.84, p < .05), and agreement on internal enhancement/signals was moderate to fair (kappa = 0.34-0.49, p < .05). Agreement among heterogeneous, clumped, and clustered-ring patterns was variable. Size assessment showed very strong correlation both in mass (Spearman's rho = 0.90-0.96, p < .0001) and non-mass lesions (Spearman's rho = 0.86, p < .0001).

CONCLUSIONS

The findings in morphology and lesion extent showed high agreement between HR-DWI and HR CE-MRI for malignant breast lesions. These results imply the potential of applying HR-DWI for evaluation of malignant breast lesions using BI-RADS MRI.