Reading Protocol for Dynamic Contrast-enhanced MR Images of the Breast: Sensitivity and Specificity Analysis

A review of quantitative diffusion-weighted MR imaging for breast cancer: Towards noninvasive biomarker

Quantitative diffusion-weighted imaging (DWI) is an important adjunct to conventional breast MRI and shows promise as a noninvasive biomarker of breast cancer in multiple clinical scenarios, from the discrimination of benign and malignant lesions, prediction, and evaluation of treatment response to a prognostic assessment of breast cancer. Various quantitative parameters are derived from different DWI models based on special prior knowledge and assumptions, have different meanings, and are easy to confuse. In this review, we describe the quantitative parameters derived from conventional and advanced DWI models commonly used in breast cancer and summarize the promising clinical applications of these quantitative parameters. Although promising, it is still challenging for these quantitative parameters to become clinically useful noninvasive biomarkers in breast cancer, as multiple factors may result in variations in quantitative parameter measurements. Finally, we briefly describe some considerations regarding the factors that cause variations.

Diagnostic role of dynamic contrast-enhanced magnetic resonance imaging in differentiating breast lesions

OBJECTIVE

This study aimed to assess the diagnostic role of perfusion weighted image (DCE-PWI) to differentiate benign from malignant breast lesions.

PATIENTS AND METHODS

The study comprised 32 women who had mammography and/or breast ultrasonography findings that were clinically questionable. All patients were fasting during the magnetic resonance imaging (MRI) test to avoid nausea or dynamic contrast-enhanced vomiting from the contrast medium.

RESULT

In this study, we observed the form of the dynamic curve (time and signal intensity curve) type I (persistent curve) was noted in 12 lesions (37.5%): 10 lesions were benign and two lesions were malignant; type II (plateau curve) was noted in eight lesions (25%): three lesions were benign and five lesions were malignant, and type III (washout curve) noted in 12 lesions (37.5%): one lesion was benign and 11 lesions were malignant.

CONCLUSIONS

The dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) perfusion technique plays an important role in differentiating benign and malignant tumors in breast cancer.

Analysis of the Refraction Effect in Ultrasound Breast Tomography

Ultrasound breast tomography (UBT) is a promising quantitative imaging method. It allows for precise analysis of ultrasound velocity distribution, which is related to tissue density and elasticity, enabling cancer detection. Only a few centers around the world have a prototype of the device for in vivo breast ultrasound tomography imaging. The quality of images reconstructed from measurements of ultrasound pulse transit times is adversely affected by the refraction of beam rays on the breast immersed in water. Refraction can be reduced using waveform tomography, ray-tracing, and ray-linking methods. However, this requires the acquisition of a pre-reconstructed pattern and is limited by extreme computational costs. In this study, the effect of refraction on transit time measurements of ultrasound passing through the female breast was analyzed under immersion conditions in water. It was found that the refraction causes the highest measurement errors in the area of the water/breast interface, and these can be reduced by adjusting the water temperature and changing the breast geometry. The results allow us to improve the quality of breast images reconstructed using an efficient transformation algorithm that assumes rectilinear ultrasound propagation paths between transmitters and receivers. In vivo breast studies were performed on the developed hybrid UBT scanner.

Different Types of Ultrasound Probes Usage for Multi-Angle Conventional 3D Ultrasound Compound Imaging: A Breast Phantom Study

Three-dimensional automated breast ultrasound (ABUS) systems seem to offer excellent results in breast cancer screening tests and its early detection, comparable to handheld ultrasound B-mode scanning, with the benefit of saving physician time and reducing handheld ultrasound issues. Nevertheless, the ABUS systems are not very popular, due to the cost and very narrow application. The multi-angle conventional 3D ultrasound compound imaging method (MACUI) is intended for use with standard B-mode scanners in order to reduce cost but preserve the advantages of ABUS systems. The rotational probe movement is utilized in order to collect images for the three-dimensional reconstruction of the scanned tissue’s anatomy. The authors evaluate the capabilities to increase the scanned volume and quality of reconstructions, which are limited in current MACUI implementations, with a probe tilt and shift. The study shows and discusses the results of the imaging using different probes available for SmartUs Telemed B-Mode scanner at different scanning geometry in order to determine the capabilities of such an ultrasound imaging system. The results discussed in the paper highlight the benefits in quality improvement and scanning area obtained with tilted and shifted probes, as well as the advantages of using a relatively simple convex probe that does not incorporate software beam steering over more advanced devices.

Radiomics of dynamic contrast-enhanced magnetic resonance imaging parametric maps and apparent diffusion coefficient maps to predict Ki-67 status in breast cancer

Purpose

This study was aimed at evaluating whether a radiomics model based on the entire tumor region from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps and apparent diffusion coefficient (ADC) maps could indicate the Ki-67 status of patients with breast cancer.

Materials and methods

This retrospective study enrolled 205 women with breast cancer who underwent clinicopathological examination. Among them, 93 (45%) had a low Ki-67 amplification index (Ki-67 positivity< 14%), and 112 (55%) had a high Ki-67 amplification index (Ki-67 positivity ≥ 14%). Radiomics features were extracted from three DCE-MRI parametric maps and ADC maps calculated from two different b values of diffusion-weighted imaging sequences. The patients were randomly divided into a training set (70% of patients) and a validation set (30% of patients). After feature selection, we trained six support vector machine classifiers by combining different parameter maps and used 10-fold cross-validation to predict the expression level of Ki-67. The performance of six classifiers was evaluated with receiver operating characteristic (ROC) analysis, sensitivity, and specificity in both cohorts.

Results

Among the six classifiers constructed, a radiomics feature set combining three DCE-MRI parametric maps and ADC maps yielded an area under the ROC curve (AUC) of 0.839 (95% confidence interval [CI], 0.768-0.895) within the training set and 0.795 (95% CI, 0.674-0.887) within the independent validation set. Additionally, the AUC value, compared with that for a single parameter map, was moderately increased by combining features from the three parametric maps.

Conclusions

Radiomics features derived from the DCE-MRI parametric maps and ADC maps have the potential to serve as imaging biomarkers to determine Ki-67 status in patients with breast cancer.

Radiomics- Quantitative Biomarker Analysis for Breast Cancer Diagnosis and Prediction: A Review

BACKGROUND

Cancer of the breast has become a global problem for women's health. Though concerns regarding early detection and accurate diagnosis were raised, an effort is required for precision medicine as well as personalized treatment. In the past years, the area of medicinal imaging has seen an unprecedented growth that leads to an advancement of radiomics, which provides countless quantitative biomarkers extracted from modern diagnostic images, including a detailed tumor characterization of breast malignancy.

DISCUSSION

In this research, we presented the methodology and implementation of radiomics, together with its future trends and challenges by the basis of published papers. Radiomics could distinguish between malignant from benign tumors, predict prognostic factors, molecular subtypes of breast carcinoma, treatment response to neoadjuvant chemotherapy (NAC), and recurrence survival. The incorporation of quantitative knowledge with clinical, histopathological and genomic information will enable physicians to afford customized care of treatment for patients with breast cancer.

CONCLUSION

Our research was intended to help physicians and radiologists learn fundamental knowledge about radiomics and also to work collaboratively with researchers to explore evidence for further usage in clinical practice.

Artificial Intelligence Applied to Breast MRI for Improved Diagnosis

Background Recognition of salient MRI morphologic and kinetic features of various malignant tumor subtypes and benign diseases, either visually or with artificial intelligence (AI), allows radiologists to improve diagnoses that may improve patient treatment. Purpose To evaluate whether the diagnostic performance of radiologists in the differentiation of cancer from noncancer at dynamic contrast material-enhanced (DCE) breast MRI is improved when using an AI system compared with conventionally available software. Materials and Methods In a retrospective clinical reader study, images from breast DCE MRI examinations were interpreted by 19 breast imaging radiologists from eight academic and 11 private practices. Readers interpreted each examination twice. In the "first read," they were provided with conventionally available computer-aided evaluation software, including kinetic maps. In the "second read," they were also provided with AI analytics through computer-aided diagnosis software. Reader diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis, with the area under the ROC curve (AUC) as a figure of merit in the task of distinguishing between malignant and benign lesions. The primary study end point was the difference in AUC between the first-read and the second-read conditions. Results One hundred eleven women (mean age, 52 years ± 13 [standard deviation]) were evaluated with a total of 111 breast DCE MRI examinations (54 malignant and 57 nonmalignant lesions). The average AUC of all readers improved from 0.71 to 0.76 (P = .04) when using the AI system. The average sensitivity improved when Breast Imaging Reporting and Data System (BI-RADS) category 3 was used as the cut point (from 90% to 94%; 95% confidence interval [CI] for the change: 0.8%, 7.4%) but not when using BI-RADS category 4a (from 80% to 85%; 95% CI: -0.9%, 11%). The average specificity showed no difference when using either BI-RADS category 4a or category 3 as the cut point (52% and 52% [95% CI: -7.3%, 6.0%], and from 29% to 28% [95% CI: -6.4%, 4.3%], respectively). Conclusion Use of an artificial intelligence system improves radiologists' performance in the task of differentiating benign and malignant MRI breast lesions. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Krupinski in this issue.

The Application of Radiomics in Breast MRI: A Review

Breast cancer has been a worldwide burden of women's health. Although concerns have been raised for early diagnosis and timely treatment, the efforts are still needed for precision medicine and individualized treatment. Radiomics is a new technology with immense potential to obtain mineable data to provide rich information about the diagnosis and prognosis of breast cancer. In our study, we introduced the workflow and application of radiomics as well as its outlook and challenges based on published studies. Radiomics has the potential ability to differentiate between malignant and benign breast lesions, predict axillary lymph node status, molecular subtypes of breast cancer, tumor response to chemotherapy, and survival outcomes. Our study aimed to help clinicians and radiologists to know the basic information of radiomics and encourage cooperation with scientists to mine data for better application in clinical practice.

Joint Prediction of Breast Cancer Histological Grade and Ki-67 Expression Level Based on DCE-MRI and DWI Radiomics

OBJECTIVE

Histologic grade and Ki-67 proliferation status are important clinical indictors for breast cancer prognosis and treatment. The purpose of this study is to improve prediction accuracy of these clinical indicators based on tumor radiomic analysis.

METHODS

We jointly predicted Ki-67 and tumor grade with a multitask learning framework by separately utilizing radiomics from tumor MRI series. Additionally, we showed how multitask learning models (MTLs) could be extended to combined radiomics from the MRI series for a better prediction based on the assumption that features from different sources of images share common patterns while providing complementary information. Tumor radiomic analysis was performed with morphological, statistical and textural features extracted on the DWI and dynamic contrast-enhanced MRI (DCE-MRI) series of the precontrast and subtraction images, respectively.

RESULTS

Joint prediction of Ki-67 status and tumor grade on MR images using the MTL achieved performance improvements over that of single-task-based predictive models. Similarly, for the prediction tasks of Ki-67 and tumor grade, the MTL for combined precontrast and apparent diffusion coefficient (ADC) images achieved AUCs of 0.811 and 0.816, which were significantly better than that of the single-task- based model with p values of 0.005 and 0.017, respectively.

CONCLUSION

Mapping MRI radiomics to two related clinical indicators improves prediction performance for both Ki-67 expression level and tumor grade.

SIGNIFICANCE

Joint prediction of indicators by multitask learning that combines correlations of MRI radiomics is important for optimal tumor therapy and treatment because clinical decisions are made by integrating multiple clinical indicators.

Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques

Breast cancer is a main cause of disease and death for women globally. Because of the limitations of traditional mammography and ultrasonography, magnetic resonance imaging (MRI) has gradually become an important radiological method for breast cancer assessment over the past decades. MRI is free of the problems related to radiation exposure and provides excellent image resolution and contrast. However, a disadvantage is the injection of contrast agent, which is toxic for some patients (such as patients with chronic renal disease or pregnant and lactating women). Recent findings of gadolinium deposits in the brain are also a concern. To address these issues, this paper develops an intravoxel incoherent motion- (IVIM-) MRI-based histogram analysis approach, which takes advantage of several hyperspectral techniques, such as the band expansion process (BEP), to expand a multispectral image to hyperspectral images and create an automatic target generation process (ATGP). After automatically finding suspected targets, further detection was attained by using kernel constrained energy minimization (KCEM). A decision tree and histogram analysis were applied to classify breast tissue via quantitative analysis for detected lesions, which were used to distinguish between three categories of breast tissue: malignant tumors (i.e., central and peripheral zone), cysts, and normal breast tissues. The experimental results demonstrated that the proposed IVIM-MRI-based histogram analysis approach can effectively differentiate between these three breast tissue types.

The role of MRI in predicting Ki-67 in breast cancer: preliminary results from a prospective study

Purpose:

In the last decade contrast-enhanced magnetic resonance imaging (MRI) has gained a growing role as a complementary tool for breast cancer diagnosis. Currently the relationship between the kinetic features of a breast lesion and pathologic prognostic factors has become a popular field of research. Our aim is to verify whether breast MRI could be considered a useful tool to predict Ki-67 score, thus resulting as a breast cancer prognosis indicator.

Methods:

From June to December 2014, we enrolled patients with breast cancer who underwent preoperative dynamic contrast-enhanced MRI at the local health agency. We analyzed the time-signal intensity curves calculating the mean values of the following parameters: the basal enhancement (Ebase), the enhancement ratio (ENHratio), the maximum enhancement (Emax), and the steepest slope of the contrast enhancement curve (Smax). Scatterplots and Pearson correlation test were used to investigate the eventual associations among these parameters.

Results:

A total of 27 patients underwent breast MRI during the study period. The mean ± SD Ki-67 percentage was 27.03 ± 16.8; the mean Emax, Smax, Ebase, and ENHratio were 433.9 ± 120.2, 267.3 ± 96.8, 165.5 ± 77.1, and 187.1 ± 94.8, respectively. Scatterplots suggest a positive correlation between Ki-67 and both Emax and Smax. The correlation tests between Ki-67 and Emax, Ki-67 and Smax showed statistical significance.

Conclusions:

Our preliminary data suggest that enhancement pattern is closely linked to breast cancer proliferation, thus proving the relationship between more proliferating tumors and more rapidly enhanced lesions. This is hypothesis-generating for further studies aimed at promoting breast MRI in the early estimation of cancer prognosis and tumor in vivo response to chemotherapy.

Added value of double reading in diagnostic radiology,a systematic review

Objectives

Double reading in diagnostic radiology can find discrepancies in the original report, but a systematic program of double reading is resource consuming. There are conflicting opinions on the value of double reading. The purpose of the current study was to perform a systematic review on the value of double reading.

Methods

A systematic review was performed to find studies calculating the rate of misses and overcalls with the aim of establishing the added value of double reading by human observers.

Results

The literature search resulted in 1610 hits. After abstract and full-text reading, 46 articles were selected for analysis. The rate of discrepancy varied from 0.4 to 22% depending on study setting. Double reading by a sub-specialist, in general, led to high rates of changed reports.

Conclusions

The systematic review found rather low discrepancy rates. The benefit of double reading must be balanced by the considerable number of working hours a systematic double-reading scheme requires. A more profitable scheme might be to use systematic double reading for selected, high-risk examination types. A second conclusion is that there seems to be a value of sub-specialisation for increased report quality. A consequent implementation of this would have far-reaching organisational effects.

Key Points

• In double reading, two or more radiologists read the same images.

• A systematic literature review was performed.

• The discrepancy rates varied from 0.4 to 22% in various studies.

• Double reading by sub-specialists found high discrepancy rates.

Electronic supplementary material

The online version of this article (10.1007/s13244-018-0599-0) contains supplementary material, which is available to authorised users.

Diffusion-Weighted Imaging for the Discrimination of Benign and Malignant Breast Masses; Utility of ADC and Relative ADC

Purpose:

To determine the contribution of apparent diffusion coefficient (ADC), and relative ADC (rADC) values to differentiate between benign and malignant breast masses.

Materials and Methods:

Magnetic resonance imaging (MRI) of the breast with diffusion-weighted imaging (DWI) of patients with benign or malignant breast masses diagnosed either by histopathological findings or by follow-up imaging were evaluated retrospectively. Histopathological analyses were performed for 71 lesions (80.7%) while the remaining were followed up every six months for one year. DWI was performed using b-values of 0 and 1000 sec/mm², and ADC and rADC were calculated and compared. A receiver operating characteristic (ROC) curve and Youden index were used to evaluate the parameter’s optimal threshold and diagnostic value. Statistical significance was set as p < 0.05.

Results:

Eighty-eight lesions from a total of 81 patients, aged between 16 and 73 (mean age 42 ± 11.3) years were obtained and evaluated. Pathological results of 34 (38.6%) out of 71 lesions were malignant and 37 lesions (42%) were benign. Seventeen (19.3%) lesions remained stable at one-year follow-up and were accepted as benign breast masses. Mean ADC values of benign and malignant lesions were 1.584 × 10^–3mm²/sec and 0.884 × 10^–3mm²/sec (p < 0.05), respectively. Sensitivity and specificity of ADC were 88% and 87%, respectively at a cut-off value of 1.04 × 10^–3mm²/sec. Mean rADC was 0.931 for benign lesions and 0.557 for malignant lesions (p < 0.05). Sensitivity and specificity were 82% and 83% at a cut-off value of 0.639. No prominent superiority of rADC over ADC is identified in the differentiation of breast masses.

Conclusion:

ADC and rADC values derived from DWI can be equally useful in clinical setting to differentiate benign from malignant breast masses.

Multimodal ultrasound computer-assisted tomography: An approach to the recognition of breast lesions

The research here presented aims at developing a new, promising method for the imaging diagnostics of breast lesions - ultrasound tomography (UST). A currently implemented device enables the reconstruction three complementary images for each coronal breast section. Based on in vivo breast examination, the authors developed an approach to breast diagnostics which employs ultrasound transmission and reflection tomography imaging. The obtained transmission images of ultrasound speed distribution show good correlation of glandular tissue areas with their visualization on MRI images. The results also allow a prediction that the implemented UST device offering fusion of reconstructed images may contribute to achieving a new standard for breast cancer diagnostics through non-invasive, fast and cheap screening tests.

Supine Breast MRI Using Respiratory Triggering

RATIONALE AND OBJECTIVES

This study aims to evaluate if navigator-echo respiratory-triggered magnetic resonance acquisition can acquire supine high-quality breast magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Supine respiratory-triggered magnetic resonance imaging (Trig-MRI) was compared to supine non-Trig-MRI to evaluate breathing-induced motion artifacts (group 1), and to conventional prone non-Trig-MRI (group 2, 16-channel breast coil), all at 3T. A 32-channel thorax coil was placed on top of a cover to prevent breast deformation. Ten volunteers were scanned in each group, including one patient. The acquisition time was recorded. Image quality was compared by visual examination and by calculation of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and image sharpness (IS).

RESULTS

Scan time increased from 56.5 seconds (non-Trig-MRI) to an average of 306 seconds with supine Trig-MRI (range: 120-540 seconds). In group 1, the median values (interquartile range) of SNR, CNR, and IS improved from 11.5 (6.0), 7.3 (3.1), and 0.23 (0.2) cm on supine non-Trig-MRI to 38.1 (29.1), 32.8 (29.7), and 0.12 (0) cm (all P < 0.01) on supine Trig-MRI. All qualitative image parameters in group 1 improved on supine Trig-MRI (all P < 0.01). In group 2, SNR and CNR improved from 14.7 (6.8) and 12.6 (5.6) on prone non-Trig-MRI to 36.2 (12.2) and 32.7 (12.1) (both P < 0.01) on supine Trig-MRI. IS was similar: 0.10 (0) cm vs 0.11 (0) cm (P = 0.88).

CONCLUSIONS

Acquisition of high-quality supine breast MRI is possible when respiratory triggering is applied, in a similar setup as during subsequent treatment. Image quality improved when compared to supine non-triggered breast MRI and prone breast MRI, but at the cost of increased acquisition time.

Is the necrosis/wall ADC ratio useful for the differentiation of benign and malignant breast lesions?

OBJECTIVE

To determine whether the necrosis/wall apparent diffusion coefficient (ADC) ratio is useful for the malignant-benign differentiation of necrotic breast lesions.

METHODS

Breast MRI was performed using a 3-T system. In this retrospective study, calculation of the necrosis/wall ADC ratio was based on ADC values measured from the necrosis and from the wall of malignant and benign breast lesions by diffusion-weighted imaging (DWI). By synchronizing post-contrast T₁ weighted images, the separate parts of wall and necrosis were maintained. All the diagnoses were pathologically confirmed. Statistical analyses were conducted using an independent sample t-test and receiver operating characteristic analysis. The intraclass and interclass correlations were evaluated.

RESULTS

A total of 66 female patients were enrolled, 38 of whom had necrotic breast carcinomas and 28 of whom had breast abscesses. The ADC values were obtained from both the wall and necrosis. The mean necrosis/wall ADC ratio (± standard deviation) was 1.61 ± 0.51 in carcinomas, and it was 0.65 ± 0.33 in abscesses. The area under the curve values for necrosis ADC, wall ADC and the necrosis/wall ADC ratio were 0.680, 0.068 and 0.942, respectively. A wall/necrosis ADC ratio cut-off value of 1.18 demonstrated a sensitivity of 97%, specificity of 93%, a positive-predictive value of 95%, a negative-predictive value of 96% and an accuracy of 95% in determining the malignant nature of necrotic breast lesions. There was a good intra- and interclass reliability for the ADC values of both necrosis and wall.

CONCLUSION

The necrosis/wall ADC ratio appears to be a reliable and promising tool for discriminating breast carcinomas from abscesses using DWI. Advances in knowledge: ADC values of the necrosis obtained by DWI are valuable for malignant-benign differentiation in necrotic breast lesions. The necrosis/wall ADC ratio appears to be a reliable and promising tool in the breast imaging field.

Can unenhanced breast MRI be used to decrease negative biopsy rates?

PURPOSE

We aimed to determine whether low-risk breast masses can be effectively managed with unenhanced magnetic resonance imaging (MRI) combining T2-weighted sequences with diffusion-weighted imaging (DWI) instead of immediate biopsy to decrease negative biopsy rates.

METHODS

After institutional review board and patient approvals, 141 consecutive women with 156 low-risk breast masses, who underwent unenhanced MRI and later on received a final diagnosis, were included in the study. There were 72 BI-RADS 3 masses in women with relative risk factors and 84 BI-RADS 4A masses, all referred for biopsy. Apparent diffusion coefficient (ADC) cutoff was 0.90×10-3 mm2/s. According to ADC values and T2-weighted imaging characteristics, masses were classified as either malignant or benign. Unenhanced MRI results were compared with final diagnoses obtained by histopathology or imaging surveillance, and diagnostic values were calculated.

RESULTS

Of 156 masses, 112 underwent biopsy. Four malignancies were diagnosed, three of which having ADC values lower than the cutoff. In women who rejected the biopsy, masses were stable during a follow-up of at least two years (n=44). MRI revealed 91% specificity and 99% negative predictive value (NPV) for detection of breast cancer.

CONCLUSION

Combination of T2-weighted imaging with DWI is a feasible method to further characterize breast masses with a low probability of malignancy. With the use of unenhanced MRI instead of immediate biopsy, it might be possible to decrease negative biopsy rates of low-risk breast masses.

Contribution of IVIM to Conventional Dynamic Contrast-Enhanced and Diffusion-Weighted MRI in Differentiating Benign from Malignant Breast Masses

BACKGROUND

The aim of this study was to determine whether the indicators obtained from intravoxel incoherent motion (IVIM) imaging can improve the characterization of benign and malignant breast masses compared with conventional dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted magnetic resonance imaging (DW-MRI).

PATIENTS AND METHODS

This study included 23 benign and 31 malignant breast masses of 48 patients. Main indicators were initial enhancement ratio (IER), time-signal intensity curve (TIC), apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudodiffusivity (D*), and perfusion fraction (f). The discriminative abilities of the different models were compared by means of receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) analysis.

RESULTS

D had the highest AUC (0.980), sensitivity (93.55%), specificity (100%), and diagnostic accuracy (96.36%). Both D and TIC could provide the independent predicted features for malignant breast masses. The combination of D and TIC had an AUC of up to 0.990.

CONCLUSION

D of IVIM can effectively complement existing conventional DCE-MRI and DW-MRI in differentiating malignant from benign breast masses. IVIM combined with DCE-MRI is a robust means of evaluating breast masses.

Determination of recall rates for assessment in high-risk women undergoing annual surveillance breast MRI

AIM

To review all surveillance breast magnetic resonance imaging (MRI) examinations performed over a 6-year period at an Irish national centre to determine the recall rate, biopsy rate, and cancer-detection rates.

MATERIALS AND METHODS

All breast MRI examinations performed for surveillance purposes in women at high risk of developing breast cancer between January 2009 and December 2014 were reviewed. The Breast Imaging-Reporting and Data System (BI-RADS) score for each MRI examination was determined, the type of additional imaging performed, and the method of biopsy, if performed, was recorded. Histology of the biopsy specimens was reviewed.

RESULTS

Data for 715 women undergoing 1445 surveillance MRI examinations were identified. Of the examinations, 10.9% (157/1445) had MRI BI-RADS scores that required recall for further imaging and 6.3% (91/1445) required a biopsy. Recall rates were 14.2% (86/607) and 8.5% (71/838) in the prevalent and incident rounds, respectively. The overall cancer detection rate was 17 per 1000.

CONCLUSION

The current UK guideline was not achieved and no studies to date have achieved the target of <7%. Aiming for this target could risk lowering the cancer-detection rate. The authors would suggest a target rate of <15% and <10% for the prevalent round and incident rounds, respectively.

Integration of DCE-MRI and DW-MRI Quantitative Parameters for Breast Lesion Classification

OBJECTIVE

The purpose of our study was to evaluate the diagnostic value of an imaging protocol combining dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) in patients with suspicious breast lesions.

MATERIALS AND METHODS

A total of 31 breast lesions (15 malignant and 16 benign proved by histological examination) in 26 female patients were included in this study. For both DCE-MRI and DW-MRI model free and model based parameters were computed pixel by pixel on manually segmented ROIs. Statistical procedures included conventional linear analysis and more advanced techniques for classification of lesions in benign and malignant.

RESULTS

Our findings indicated no strong correlation between DCE-MRI and DW-MRI parameters. Results of classification analysis show that combining of DCE parameters or DW-MRI parameter, in comparison of single feature, does not yield a dramatic improvement of sensitivity and specificity of the two techniques alone. The best performance was obtained considering a full combination of all features. Moreover, the classification results combining all features are dominated by DCE-MRI features alone.

CONCLUSION

The combination of DWI and DCE-MRI does not show a potential to dramatically increase the sensitivity and specificity of breast MRI. DCE-MRI alone gave the same performance as in combination with DW-MRI.

Magnetic resonance imaging-guided occult breast lesion localization and simultaneous sentinel lymph node mapping

Background

Radio-guided occult lesion localization is a valid technique for the diagnosis of suspicious non-palpable lesions. Here we determine the feasibility of pre-operative localization of occult suspect non-palpable breast lesions using radio-guided occult lesion localization, as well as for identifying the sentinel lymph node.

Methods

This is a descriptive study of data collected retrospectively. Pre-operative mapping of 34 breast lesions in 25 patients suspected of being malignant was performed using conventional imaging methods with a magnetic resonance imaging-guided radiopharmaceutical injection.

Results

The mean time required to perform the localization was 25 minutes. After resection of the lesions using a gamma probe, malignancy was confirmed in fifteen patients (60.0%), with nine invasive ductal carcinomas, two invasive lobular carcinomas, and four in situ ductal carcinomas The resection was confirmed by the complete removal of the radioactive material. The pathologic results and images were concordant in all but two cases, which were submitted for new magnetic resonance imaging examinations and surgery that confirmed the malignancies. Of the 15 patients with confirmed malignancies, 10 had sentinel lymph node resection. Of these, eight were negative for metastases, one had micro-metastases and one had confirmed metastases. Three patients had full axillary node dissection, with metastases found in only one. No side effects were observed with magnetic resonance-guided radiopharmaceutical injection.

Conclusions

The sentinel node occult lesion localization technique is a simple, reproducible and effective alternative approach to occult lesions compared to other methods, such as mammotomy and the hook-wire localization technique, for mapping suspect breast lesions and identifying lymph node metastasis.

Sonoelastography in distinguishing benign from malignant complex breast mass and making the decision to biopsy

Objective

To evaluate the additional effect of sonoelastography on the radiologist's ability for distinguishing benign from malignant complex breast masses and to decide whether to perform biopsy by B-mode US.

Materials and Methods

One hundred eighteen complex breast masses (15 malignant lesions, 103 benign lesions) were included. Five blinded readers independently assessed the likelihood of the malignancy score from 1 to 5 for two data sets (B-mode ultrasound alone and B-mode ultrasound with sonoelastography). Elasticity scores were categorized as 0, 1, or 2 based on the degree and distribution of strain of the echogenic component within complex masses. The readers were asked to downgrade the likelihood of the malignancy score when an elasticity score of 0 was assigned and to upgrade the likelihood of the malignancy score when an elasticity score of 2 was assigned. The likelihood of the malignancy score was maintained as it was for the lesions with an elasticity score of 1. The Az values, sensitivities, and specificities were compared.

Results

The Az value of B-mode ultrasound with sonoelastography (mean, 0.863) was greater than that of B-mode ultrasound alone (mean, 0.731; p = 0.001-0.007) for all authors. The specificity of B-mode ultrasound with sonoelastography (mean, 37.1%) was greater than that of B-mode ultrasound alone (mean, 3.8%; p < 0.001) for all readers. The addition of sonoelastography led to changes in decisions. A mean of 33.6% of benign masses were recommended for follow-up instead of biopsy.

Conclusion

For complex breast masses, sonoelastography allows increase in both the accuracy in distinguishing benign from malignant lesions and the specificity in deciding whether to perform biopsy.

An imaging protocol for dynamic contrast-enhanced breast MRI with 3.0T: using sagittal sequence interleaved between axial sequences

BACKGROUND

B1 transmission-field inhomogeneity has been reported at 3.0 Tesla (T) breast imaging. Enhancement measurements of breast cancers at 3.0T may be insufficient for some patients and improvements in imaging protocols are needed.

PURPOSE

To quantify B1 inhomogeneities in normal tissue and malignant masses at 3.0T breast MR imaging and to evaluate effect of an imaging protocol using an interleaved sagittal sequence in dynamic contrast-enhanced MRI (DCE-MRI).

MATERIAL AND METHODS

A total of 76 patients were included who underwent DCE-MRI of the breast at 3.0T with an imaging protocol consisting of 1st, 2nd, and 4-6th bilateral axial sequences, and 3rd and 7th unilateral sagittal sequences. Signal intensity (SI) of normal breast tissue was measured at nipple level in four bilateral locations (anterior, posterior, medial, and lateral). Mean whole breast and location specific SI were calculated and compared between right and left breast using a paired t-test. All malignant masses were classified into three groups according to tumor size on MRI (≤2 cm, 2-4 cm, >4 cm). SI of malignant masses was measured independently on axial and sagittal sequences. The axial-sagittal SI gap in each mass was calculated and difference between right and left breast was compared using the t test. Size of each malignant mass was compared with pathologic findings to assess performance of the imaging protocol.

RESULTS

SI of normal breast tissue were lower for the right breast (R-L difference, -91.9; P < 0.0001) and in all four locations (anterior, P < 0.01; posterior, P < 0.01; medial, P < 0.0001; lateral, P < 0.0001). SI of malignant masses were lower for the right breast among same size of the lesions (P < 0.0001), particularly < 4 cm (P < 0.0001). Decreased right to left difference in SI was produced with an interleaved sagittal sequence, as axial-sagittal gap of malignant masses was significant when tumor locates on the right side (P < 0.001). The concordance rate in predicting size of mass in this imaging protocol was 92.2%.

CONCLUSION

The interleaved sagittal sequence is helpful to adjust reduced SI of malignant masses on right breast at 3.0T. This imaging protocol is clinically applicable by adding a single sequence during DCE-MRI of the breast.

Impact of breast MR in non-screening Australian clinical practice: audit data from a single-reader single-centre site

AIM

The aim of this study was to evaluate the accuracy and clinical impact of single-reader breast MR (BMR) used as a clinical 'problem solving' tool.

METHODS

Observational, retrospective, ethics approved data collection for all BMR were from May 2006 to February 2009 (n=143). Cases were stratified into groups according to indication for referral. MR data included single-reader MR diagnosis and breast imaging reporting and data system category (per-patient basis), MR descriptors of lesions (breast imaging reporting and data system lexicon), lesion number and location. Composite reference standard was established from surgical histology, core histology, cytology, MR imaging follow-up, conventional imaging follow-up and clinical follow-up in that order of priority. Impact was qualitatively captured by estimating change in management as the result of BMR.

RESULTS

Eighty-two cases were included and 61 were excluded (41 insufficient follow-up times, three known benign mass for clarification, two worried well screening and 15 other reasons). There was no statistically significant difference in included and excluded patient profiles. Our largest group of referrals was of patients with suspicious or unhelpful conventional imaging. BMR identified five malignancies in that group but missed four. In our smaller group of patients with metastatic axillary lymph nodes, BMR identified the occult primary cancer in all five cases.

CONCLUSION

In this 'problem solving' patient population, breast MR shows greatest impact in patients with carcinoma metastases to axillary nodes, but primary not visible. In symptomatic women with unhelpful imaging or with suspicious imaging but no pre-MR diagnosis, MR identified 5/41 carcinomas, but missed 4/41.

Breast ultrasound tomography versus MRI for clinical display of anatomy and tumor rendering: preliminary results

OBJECTIVE

The objective of our study was to determine the clinical display thresholds of an ultrasound tomography prototype relative to MRI for comparable visualization of breast anatomy and tumor rendering.

SUBJECTS AND METHODS

Thirty-six women were imaged with MRI and our ultrasound tomography prototype. The ultrasound tomography scan generated reflection, sound-speed, and attenuation images. The reflection images were fused with the components of the sound-speed and attenuation images that achieved thresholds to represent parenchyma or solid masses using an image arithmetic process. Qualitative and quantitative comparisons of MRI and ultrasound tomography clinical images were used to identify anatomic similarities and optimized thresholds for tumor shapes and volumes.

RESULTS

Thresholding techniques generated ultrasound tomography images comparable to MR images for visualizing fibrous stroma, parenchyma, fatty tissues, and tumors. In 25 patients, tumors were cancerous and in 11, benign. Optimized sound-speed thresholds of 1.46±0.1 and 1.52±0.03 km/s were identified to best represent the extent of fibroglandular tissue and solid masses, respectively. An arithmetic combination of attenuation images using a threshold of 0.16±0.04 dB/cm (mean±SD) further characterized benign from malignant masses. No significant difference in tumor volume was noted between benign or malignant masses by ultrasound tomography or MRI (p>0.1) using these universal thresholds.

CONCLUSION

Ultrasound tomography is able to image and render breast tissues in a manner comparable to MRI. Using universal ultrasound tomography threshold values for rendering the size and distribution of benign and malignant tissues appears feasible without IV contrast material.

Distinguishing benign from malignant masses at breast US: combined US elastography and color doppler US--influence on radiologist accuracy

PURPOSE

To investigate the effect of the combined use of ultrasonographic (US) elastography and color Doppler US on the accuracy of radiologists in distinguishing benign from malignant nonpalpable breast masses and in making the decision for biopsy recommendations at B-mode US.

MATERIALS AND METHODS

This prospective study was conducted with institutional review board approval; written informed consent was obtained. A cohort of 367 biopsy-proved cases in 319 women (age range, 22-78 years; mean age, 48.6 years) with B-mode US, US elastographic, and Doppler US images was included. Five blinded readers independently scored the likelihood of malignancy for four data sets (ie, B-mode US alone, B-mode US and elastography, B-mode US and Doppler US, and B-mode US, US elastography, and Doppler US). The area under the receiver operating characteristic curve (A(z)) values, sensitivities, and specificities of each data set were compared.

RESULTS

The A(z) of B-mode US, US elastography, and Doppler US (average, 0.844; range, 0.797-0.876) was greater than that of B-mode US alone (average, 0.771; range, 0.738-0.798) for all readers (P = .001 for readers 1, 2, and 3; P < .001 for reader 4; P = .002 for reader 5). When both elastography and Doppler scores were negative, leading to strict downgrading, the specificity increased for all readers from an average of 25.3% (75.4 of 298; range, 6.4%-40.9%) to 34.0% (101.2 of 298; range, 26.5%-48.7%) (P < .001 for readers 1, 2, 4, and 5; P = .016 for reader 3) without a significant change in sensitivity.

CONCLUSION

Combined use of US elastography and color Doppler US increases both the accuracy in distinguishing benign from malignant masses and the specificity in decision-making for biopsy recommendation at B-mode US.

Extra-mammary findings in breast MRI

OBJECTIVES

Incidental extra-mammary findings in breast Magnetic Resonance Imaging (MRI) may be benign in nature, but may also represent a metastasis or another important lesion. We aimed to analyse the prevalence and clinical relevance of these unexpected findings.

METHODS

A retrospective review of 1535 breast MRIs was conducted. Only axial sequences were reassessed. Confirmation examinations were obtained in all cases.

RESULTS

285 patients had a confirmed incidental finding, which were located in the liver (51.9%), lung (11.2%), bone (7%), mediastinal lymph nodes (4.2%) or consisted of pleural/pericardial effusion (15.4%). 20.4% of incidental findings were confirmed to be malignant. Positive predictive value for MRI to detect a metastatic lesion was high if located within the bone (89%), lymph nodes (83%) and lung (59%), while it was low if located within the liver (9%) or if it consisted of pleural/pericardial effusion (6%). The axial enhanced sequence showed superior sensitivity to unenhanced images in detecting metastatic lesions, especially if only smaller (≤10 mm.) lesions were considered.

CONCLUSIONS

The prevalence of metastatic incidental extra-mammary findings is not negligible. Particular attention should be to incidental findings located within the lung, bone and mediastinal lymph nodes.

Quantification techniques to minimize the effects of native T1 variation and B1 inhomogeneity in dynamic contrast-enhanced MRI of the breast at 3 T

The variation of the native T(1) (T(10)) of different tissues and B(1) transmission-field inhomogeneity at 3 T are major contributors of errors in the quantification of breast dynamic contrast-enhanced MRI. To address these issues, we have introduced new enhancement indices derived from saturation-recovery snapshot-FLASH (SRSF) images. The stability of the new indices, i.e., the SRSF enhancement factor (EF(SRSF)) and its simplified version (EF'(SRSF)) with respect to differences in T(10) and B(1) inhomogeneity was compared against a typical index used in breast dynamic contrast-enhanced MRI, i.e., the enhancement ratio (ER), by using computer simulations. Imaging experiments with Gd-DTPA-doped gel phantoms and a female volunteer were also performed. A lower error was observed in the new indices compared to enhancement ratio in the presence of typical T(10) variation and B(1) inhomogeneity. At changes of relaxation rate (ΔR(1)) of 8 s(-1), the differences between a T(10) of 1266 and 566 ms are <1, 12, and 58%, respectively, for EF(SRSF), EF'(SRSF), and ER, whereas differences of 20, 8, and 51%, respectively, result from a 50% B(1) field reduction at the same ΔR(1). These quantification techniques may be a solution to minimize the effect of T(10) variation and B(1) inhomogeneity on dynamic contrast-enhanced MRI of the breast at 3 T.

Double reading of radiological examinations in Norway

BACKGROUND

Double reading of images is a part of the quality assurance activities at many radiological centers.

PURPOSE

To investigate the extent of and routines for double reading in Norway and the institutional heads' attitudes toward double reading.

MATERIAL AND METHODS

A questionnaire was addressed to the heads of all radiological institutions in Norway. The questionnaire concerned staffing, examinations performed, extent of double reading per imaging modality (except mammography screening), guidelines for double reading, checks of completed radiology reports, frequency of regular quality assurance meetings to discuss missed findings, and the heads' attitudes toward double reading.

RESULTS

The response rate was 73% (53/73). The percentage across imaging modalities of examinations being double read was 41% overall: 56% at university hospitals, 37% at local hospitals, and 18% at private centers. Double reading was most common for positron emission tomography (PET)/PET-computed tomography (CT) examinations (100%), and clinical mammography (91%). Almost all examinations read by residents were double read. Only 15% of institutions had written guidelines for double reading, 15% performed random double readings of completed examinations, and 55% organized regular meetings to discuss missed findings. Forty-six percent of the institutional heads wanted an increased use of double reading.

CONCLUSION

Double reading is common in Norway, especially in residency training, mammography, and PET/PET-CT. It is less common at private centers. Established routines for double reading are scarce. Many institutional heads want more double reading. The potential of double reading to assure quality in radiology should be better exploited.

Psychological impact and acceptability of magnetic resonance imaging and X-ray mammography: the MARIBS Study

Background:

As part of the Magnetic Resonance Imaging for Breast Screening (MARIBS), Study women with a family history of breast cancer were assessed psychologically to determine the relative psychological impact and acceptability of annual screening using magnetic resonance imaging (MRI) and conventional X-ray mammography (XRM).

Methods:

Women were assessed psychologically at baseline (4 weeks before MRI and XRM), immediately before, and immediately after, both MRI and XRM, and at follow-up (6 weeks after the scans).

Results:

Overall, both procedures were found to be acceptable with high levels of satisfaction (MRI, 96.3% and XRM, 97.7% NS) and low levels of psychological morbidity throughout, particularly at 6-week follow-up. Low levels of self-reported distress were reported for both procedures (MRI, 13.5% and XRM, 7.8%), although MRI was more distressing (P=0.005). Similarly, higher anticipatory anxiety was reported before MRI than before XRM (P=0.003). Relative to XRM, MRI-related distress was more likely to persist at 6 weeks after the scans in the form of intrusive MRI-related thoughts (P=0.006) and total MRI-related distress (P=0.014). More women stated that they intended to return for XRM (96.3%) than for MRI (88% P<0.0005). These effects were most marked for the first year of screening, although they were also statistically significant in subsequent years.

Conclusion:

Given the proven benefits of MRI in screening for breast cancer in this population, these data point to the urgent need to provide timely information and support to women undergoing MRI.