Main points

• Synthetic diffusion-weighted imaging (sDWI) is a mathematical computation technique to generate a high b value DWI image. No extra acquisition time is required.

• Synthetic DWI is superior to DWI sequence due to fewer artifacts, lack of inhomogeneity in fat suppression, and a high signal-to-noise ratio.

• Synthetic DWI is superior to DWI sequences for lesion visibility, particularly in dense breasts. Thus, sDWI should be considered when conducting breast magnetic resonance imaging scans.

Introduction

Conventional breast magnetic resonance imaging (MRI) has the highest sensitivity for breast cancer detection, staging of known cancer, and evaluation of response to neoadjuvant chemotherapy. In recent years, specifically according to the Dense Tissue and Early Breast Neoplasm Screening trial¹ and the EA1411 Eastern Cooperative Oncology Group–American College of Radiology (ACR) Imaging Network study,² the indication spectrum of breast MRI has widened. The European Society of Breast Imaging now recommends offering screening breast MRI every 2–4 years in women aged 50–70 years with extremely dense breasts.³ However, MRI is limited by high costs, which include the cost of contrast material administration, intravenous (IV) supplies, point-of-care renal function screening, and on-site physician coverage for adverse contrast material-related events. Furthermore, prolonged examination time is an additional concern. With the latest concerns regarding the safety of gadolinium-based contrast agents, diffusion-weighted imaging (DWI) has been recommended as an encouraging alternative to dynamic contrast-enhanced MRI for detecting early breast cancer. In addition, an improvement in tumor visibility without contrast injection could improve the cost-effectiveness of MRI. DWI is a fast, widely available, unenhanced MRI technique that provides a unique radiologic image contrast by providing information on the cellular environment of tissues in vivo. In recent years, this sequence has been used in addition to conventional sequences and decreases false positivity.

However, DWI has many limitations, such as a decrease in signal-to-noise ratio (SNR) and experiencing eddy current distortions when using a high b value; studies have been conducted to overcome these limitations and to improve this sequence.⁴ The principal basis for using DWI for disease detection relies on maximizing the image contrast between diseased tissue and the background. The extent to which this occurs depends on the intrinsic tissue diffusivity, the T2 relaxation time, and the diffusion weighting (b value) of the motion probing gradients that are applied. The selection of the b value is a key point as it directly affects the image SNR, lesion contrast-to-noise ratio, and apparent diffusion coefficients (ADCs). The b value can enhance both the lesion detection sensitivity and specificity, but it also leads to a decreased SNR. Furthermore, the perfusion effect is minimized.^5,6 However, acquiring images at higher b values (>1.000 sec/mm²) leads to more distortion due to susceptibility effects and eddy currents and lengthens imaging times.^7,8,9,10 One of the new techniques for improving the accuracy of DWI is synthetic DWI (sDWI). sDWI is a mathematical computation technique that builds on previously described principles and calculates a high b value (or any b value) image from DWI images acquired with at least two different lower b values.^11,12 Once the ADC is known, it can be used to extrapolate the expected signal intensity for each image voxel to any computed b value using the equation S(b) = S(0) e^−ᵇ*ADC, thus generating a computed DWI image.^6,13,14 The calculation of synthetic high b values is a strategy to enhance contrast already present in lower b value images and is potentially useful to detect and depict lesions but lacks the power of non-Gaussian diffusion to characterize tissues.

sDWI is superior to conventional DWI with fewer artifacts, no inhomogeneity in fat suppression, and a high SNR. There are many reports^15,16,17,18 on the efficacy of sDWI for imaging organs such as the prostate; however, there are limited reports on the evaluation of breast lesions.^18,19

The aim of this study is to investigate the feasibility of the sDWI technique for lesion detection and to compare it with conventional DWI.

Methods

Patients selection

This study involved a retrospective analysis of acquired data. The medical Ethics Committee of Acıbadem University approved this single institution study (2023-09/303), and informed consent was waived. All the enhancing lesions on breast MRI images between March 2018 and September 2021 were included in the study. The exclusion criteria were as follows: cases with no histopathological diagnosis or 2 years follow-up; cases with biopsy history prior to MRI; cases involving MRI scans following neoadjuvant chemotherapy.

A total of 139 breast MRI scans were evaluated, and four patients were excluded due to artifacts and technical inadequacy (insufficient fat suppression). Consequently, 135 lesions in 128 patients were evaluated (median age: 47.51 ± 11.15 years; age range: 27–79 years). Among these, 117 lesions had histopathological diagnoses, either with core needle biopsy or vacuum-assisted biopsy, and the remaining 18 lesions were stable in the 2-year follow-up and were regarded as benign.

Magnetic resonance imaging technique

All examinations were performed using a 1.5 Tesla (T) MRI device (Aera; Siemens Healthcare) using an 18-channel breast matrix surface receiver coil with prone positioning. Care was taken to perform the MRI scans of premenopausal women between days 5 and 15 of the menstrual cycle. Multiparametric MRI images (fat-sat STIR T2W sequence, a pre-contrast DWI sequence, and a dynamic contrast-enhanced T1W sequence) were obtained for all the patients. For the dynamic contrast-enhanced sequences, 0.1 mmol/kg of body weight of contrast material (Gadovist; Bayer Healthcare Pharmaceutical, Berlin, Germany) was injected. Diffusion-weighted echo-planar images (time of repetition: 3.000–7.000 ms, time of echo: 50–60 ms, field of view: 260–300 mm, matrix: 192 × 192, number of excitations: 1, sectional thickness: 4 mm with a 1 mm intersection gap) were obtained in the axial plane prior to contrast administration. The DWI was obtained using diffusion gradient b values of 50–800 sec/mm². ADC maps were calculated from raw DWI images using all b values and applying the standard monoexponential regression approach performed automatically by the scanner software. sDWI images at b = 1.500 sec/mm² were automatically constructed in a commercially available workstation using syngo.via VB10 software (Siemens Healthcare, Erlangen, Germany).

Data analysis

The evaluation was performed by three radiologists with at least 10 years of experience in breast radiology. One radiologist evaluated the sDWI images in addition to all sequences, whereas the other two radiologists, who were blinded to the clinical diagnoses and all imaging findings, evaluated only the conventional DWI and sDWI images. Imaging data were analyzed on a dedicated workstation (Multi-Modality Work-Place, Siemens Healthineers). Detection of hyperintense lesions on sDWI and DWI was acknowledged as positive for malignancy suspicion as on DWI, and the readers assigned a qualitative positive or negative assessment.

Lesion size was defined as the largest diameter of the enhancing lesion in the first minute post-contrast T1W sequence. For patients with more than one lesion, the largest lesion was included in the study.

Breast densities were categorized into four groups (type A, B, C, and D) according to the American College of Radiology Breast Imaging Reporting and Data System atlas terminology.²⁰

Statistical analysis

Data of continuous variables were presented as a mean ± standard deviation, minimum–maximum, and percentile. A comparison of two variables that were independent and not normally distributed was performed using the Mann–Whitney U test. The chi-squared test (or, when appropriate, Fisher’s exact test) was used to investigate the relationship between the categorical variables.

Receiver operating characteristic curve analysis was performed for the determination of ADC cut-off values according to the statistically significant parameters. Subsequently, the diagnostic values and confidence intervals (CIs) were obtained.

The inter-reader agreement was evaluated using intra-class correlation and the Fleiss κ test.

Statistical analysis was performed using MedCalc Statistical Software version 12.7.7 (MedCalc Software bvba, Ostend, Belgium; http://www.medcalc.org; 2013). All P values of <0.05 were considered statistically significant.

Results

Eighty-two lesions were malignant (confirmed via histopathologic diagnosis) (mean size: 27.4 ± 20.55 mm, range: 3–100 mm), and 53 lesions were benign (35 lesions were confirmed via histopathologic diagnosis, and 18 lesions were stable in the 2-year follow-up and regarded as benign) (mean size: 13.06 ± 7.66 mm, range: 4–36 mm) (Table 1).

Diagnoses of benign lesions included fibrocystic changes (n = 10; 18.8%), fibroadenoma (n = 7; 13.2%), usual epithelial hyperplasia (n = 1; 1.8%), fat necrosis (n = 2; 3.7%), adenosis (n = 4; 7.5%), stromal fibrosis (n = 8; 15.0%), radial scar (n = 2; 3.7%), intramammary lymph node (n = 1; 1.8%), and stable in the 2-year follow-up (n = 18; 33.9%). Malignant lesion subtypes consisted of invasive ductal carcinoma (IDC) (n = 70; 85.3%), invasive lobular carcinoma (n = 3; 3.6%), metaplastic carcinoma (n = 1; 1.2%), and ductal carcinoma in situ (DCIS) (n = 8; 9.7%).

The diagnostic performance of ADC value to differentiate malignant breast masses from benign masses was as follows: sensitivity 92.68% (95% CI: 84–97), specificity 79.25% (95% CI: 65–89), using an ADC cut-off value of 1.189 x 10⁻³ mm²/sec, which is comparable with the literature data.^21,22,23,24

Of the 82 malignant lesions, 75 were hyperintense on sDWI, whereas 7 were isointense (Figure 1). Four of the 7 sDWI isointense malignant lesions were DCIS. Two of the remaining three IDCs (80 and 10 mm in size and both Luminal B cancers) were located peripherally in the axillary tail, and the lesions were not visualized due to insufficient fat-suppression and distortion in that area (Figure 2). One triple-negative IDC lesion appearing isointense on the DWI image showed diffusion restriction when evaluated with an ADC map. Of the seven isointense cases, six were also isointense on DWI. There was one case in which the biopsy result of DCIS was hyperintense on DWI with a high ADC value (1.504 x 10⁻³ mm²/sec). Therefore, it was interpreted as no diffusion restriction and DWI hyperintensity may be due to the T2 effect. When the DWIs were evaluated with ADC mapping (using a cut-off value of 1.189 x 10⁻³ mm²/sec), three cases showed diffusion restriction, whereas four did not (Table 2).

When the stand-alone DWI sequence was evaluated, 60 of the 82 malignant lesions were hyperintense, and the remaining 22 were isointense. Of these 22 isointense lesions, 6 were isointense on both sDWI and DWI, whereas 16 lesions were hyperintense solely on sDWI. When the DWI sequence was compared with ADC mapping, 15 of 16 lesions (in one lesion ADC value is 1.239 mm²/sec) showed restricted diffusion with ADC values less than the cut-off value of 1.189 x 10⁻³ mm²/sec.

Comparison of DWI acquired with b = 800 diffusion gradient to sDWI at b = 1.500 value (Table 3) in the detection of malignant lesions showed that sDWI was significantly effective (P < 0.001).

Of the 53 benign lesions, 38 were isointense on sDWI, whereas 15 were hyperintense (Figure 3). Of these 15 hyperintense lesions, 4 were isointense on DWI and the remaining 11 were hyperintense (Table 4). When compared with ADC mapping, 6 of these 11 lesions had ADC values above the cut-off value of 1.189 x 10⁻³ mm²/sec. The remaining 5 lesions had ADC values below the cut-off value.

For the 53 benign lesions, 33 were hyperintense, and 20 were isointense on DWI images. ADC mapping showed values below the cut-off value of 1.189 x 10⁻³ mm²/sec in 11 of these 53 benign lesions.

When the sDWI and DWI sequences for benign lesions were compared, the false positivity rates were 28.30% and 62.26%, respectively. If DWI sequences are assessed in conjunction with the ADC map, the rate of false positive results is 20.75%.

The diagnostic performance of DWI and sDWI to differentiate malignant breast masses from benign masses was as follows: sensitivity 73.1% (95% CI: 62–82), specificity 37.7% (95% CI: 24–52); sensitivity 91.5% (95% CI: 83–96), specificity 71.7% (95% CI: 57–83), respectively. The diagnostic accuracy of DWI and sDWI was 59.2% and 83.7%, respectively.

Lesion size represents a significant limitation when evaluating lesions on the DWI sequence. In this investigation, a total of seven malignant lesions were identified that appeared isointense in the sDWI sequence, rendering them undetectable. These lesions displayed a size range spanning from 10–80 mm, with an average size of 22.85 mm. Within the DWI sequence, 22 out of 82 malignant lesions exhibited isointensity and remained undetectable. These lesions varied in size from 9–80 mm, with an average size of 23.54 mm. Notably, there was one lesion measuring <1 cm (9 mm) that could not be detected in the DWI sequence.

In addition, the study identified a total of 32 lesions falling within the size range of 3–9 mm (<1 cm). Among these, 9 were malignant and 23 were benign. As explained earlier, all but one of these nine malignant lesions were detectable. Among the benign lesions, 11 displayed isointensity in both sequences, 7 showed hyperintensity solely in the DWI sequence, and 6 were hyperintense in both the DWI and sDWI sequences. When comparing the relationship between size and detectability in both benign and malignant lesions, no statistically significant difference (P = 0.0867) was found. These findings suggest that size does not significantly impact the assessment of lesions in the DWI and sDWI sequences.

The distribution of the individual amounts of fibroglandular tissue (FGT) is important because difficulties with lack of fat saturation are more common in breasts with a high percentage of fat.¹² The performance of DWI and sDWI sequences can be affected by the distribution of FGT. In this study, the composition of the female group included 24 (18.75%) women within ACR category B, 75 (58.59%) women within category C, and 35 (27.34%) women within category D. Only one case was categorized as “type A,” and this category was thus disregarded (shown in Table 5). No statistically significant difference was found between the breast parenchymal distribution and signal distribution DWI and sDWI sequences regarding type B, type C, and type D (DWI P = 0.066; sDWI P = 0.335).

Synthetic DWI inter-reader agreement was almost perfect for lesion visibility (shown in Table 6) and was statistically significant (κ: 0.922, P < 0.001).

Discussion

DWI has been proposed as an unenhanced option for breast cancer screening via MRI, and synthetic b values may improve lesion visibility without increasing the acquisition time while avoiding the disadvantages of performing DWI at extremely high b values. In this study, DWI was assessed for tumor visibility and breast cancer detection by a combination of acquired b values (800 sec/mm²), ADC maps, and synthetic b values (1.500 sec/mm²). Synthetic b values of 1.500 sec/mm² provided the best lesion conspicuity. Benign lesions were more conspicuous at lower b values, whereas malignant tumors appeared brighter than the surrounding parenchyma at higher b values, particularly in breast composition categories C and D, where lesions can be masked on mammograms by the density of FGT. The study shows that sDWI sequences are superior to DWI sequences for lesion visibility, and the results corroborate those in the recent literature.^11,18

In this study, the lesion visibility was assessed using DWI and sDWI. The former was significantly less sensitive than the latter (73.1% vs. 91.5%, P < 0.001). Furthermore, the detection rate of cancer was not significantly different when the DWI sequences were evaluated in conjunction with ADC mapping (92.68%). In two independent studies,^11,18 the conventional DWI of cancer to parenchyma contrast ratio of malignant lesions was compared with DWI with higher b values. The authors reported that the tumor-to-parenchymal contrast ratio of sDWI was significantly higher than that of conventional DWI, without compromising the cancer detection rate. In another study, Blackledge et al.¹⁶ claimed that sDWI raised the rate of lesion detection in comparison to DWI. O’Flynn et al.¹⁹ also reported that sDWI increased sensitivity for breast cancer. However, these studies involved smaller cohorts, and only malignant lesions were evaluated.

The prime focus of DWI is to differentiate between benign and malignant lesions to prevent unnecessary breast biopsies or enable screening without admission of IV contrast media. Only 19%–36% of the lesions that are biopsied due to MR examination results turn out to be malignant.^25,26 It is particularly important to differentiate benign lesions, which show contrast enhancement resulting in false positive results. There is limited data on the evaluation of benign lesions on sDWI.¹⁸ Unlike other studies, in this study, both malignant and benign lesions were evaluated. The rate of false positivity of sDWI and DWI was 28.30% and 62.26%, respectively. The high rate of false positivity on DWI has been attributed to the T2 shine-through effect.¹⁶ However, the false positivity was 20.75% when DWI was evaluated with an ADC map (Table 2). This data indicates that by first examining the sDWI images and then evaluating any questionable lesions using the ADC map, the opportunity exists to achieve a quicker and more precise diagnosis, while also avoiding unnecessary biopsies.

Studies conducted in recent years have shown that the combined evaluation of early phase contrast images and DWI can replace late-phase and kinetic-curve evaluation, meaning results can be achieved with a much shorter imaging time.²⁷ Furthermore, in recent years, an annual or biannual screening MRI has been recommended for high-risk patients with dense breasts, and an abbreviated MRI is aimed at achieving fast and accurate results.²⁸ The primary objective of breast MRI is to enhance the precision of diagnosis while minimizing the likelihood of overdiagnosis. In most of the abbreviated MRI protocols, DWI sequences are included.^29,30,31 This study shows that adding sDWI scans, which do not require additional acquisition time in the evaluation, has the potential to increase the diagnostic accuracy of abbreviated MRI evaluations.

The performance of DWI and sDWI sequences can be affected by the distribution of FGT. Fat suppression cannot be made homogeneously in fatty breasts in diffusion-weighted sequences. Furthermore, fatty breasts have a lower ADC value compared with dense breasts in the retroareolar region and upper outer quadrant.^12,32 This study did not identify any correlation between breast density and the detectability of lesions on either DWI or sDWI. Similarly, prior studies^32,33 showed that the visibility of breast lesions on DWI was not influenced by breast density. However, since the optimal evaluation is often made with mammography in women with fatty breasts, MRI is rarely required for the evaluation of the patient and thus, the number of fatty breasts in the study group is extremely low.

This study has a number of limitations. First, it is a single-center study. A multicentral study will be valuable to showing the reproducibility of the findings. Second, this study evaluated only lesion detection. Although the image quality in the sDWI series is relatively high, no quantitative assessment was conducted. Furthermore, the role of DWI in the visualization of non-mass enhancement is not definite.^34,35,36 In this study, this patient group was not evaluated separately; this evaluation should be conducted in further studies.

To conclude, the findings indicate that sDWI exhibits significantly greater sensitivity than conventional DWI in assessing both malignant and benign lesions. The results indicate that the inclusion of sDWI image evaluation in the interpretation of breast MRI scans has the potential for a better outcome.

Conflict of interest disclosure

The authors declared no conflicts of interest.