Performance of Diffusion-weighted Imaging-based Noncontrast MRI Protocols for Diagnosis of Breast Cancer: A Systematic Review and Meta-Analysis.

Background Diffusion-weighted imaging (DWI) is increasingly recognized as a powerful diagnostic tool and tested alternative to contrast-enhanced (CE) breast MRI. Purpose To perform a systematic review and meta-analysis that assesses the diagnostic performance of DWI-based noncontrast MRI protocols (ncDWI) for the diagnosis of breast cancer. Materials and Methods A systematic literature search in PubMed for articles published from January 1985 to September 2023 was performed. Studies were excluded if they investigated malignant lesions or selected patients and/or lesions only, used DWI as an adjunct technique to CE MRI, or were technical studies. Statistical analysis included pooling of diagnostic accuracy and investigating between-study heterogeneity. Additional subgroup comparisons of ncDWI to CE MRI and standard mammography were performed. Results A total of 28 studies were included, with 4406 lesions (1676 malignant, 2730 benign) in 3787 patients. The pooled sensitivity and specificity of ncDWI were 86.5% (95% CI: 81.4, 90.4) and 83.5% (95% CI: 76.9, 88.6), and both measures presented with high between-study heterogeneity (I 2 = 81.6% and 91.6%, respectively; P < .001). CE MRI (18 studies) had higher sensitivity than ncDWI (95.1% [95% CI: 92.9, 96.7] vs 88.9% [95% CI: 82.4, 93.1], P = .004) at similar specificity (82.2% [95% CI: 75.0, 87.7] vs 82.0% [95% CI: 74.8, 87.5], P = .97). Compared with ncDWI, mammography (five studies) showed no evidence of a statistical difference for sensitivity (80.3% [95% CI: 56.3, 93.3] vs 56.7%; [95% CI: 41.9, 70.4], respectively; P = .09) or specificity (89.9% [95% CI: 85.5, 93.1] vs 90% [95% CI: 61.3, 98.1], respectively; P = .62), but ncDWI had a higher area under the summary receiver operating characteristic curve (0.93 [95% CI: 0.91, 0.95] vs 0.78 [95% CI: 0.74, 0.81], P < .001). Conclusion A direct comparison with CE MRI showed a modestly lower sensitivity at similar specificity for ncDWI, and higher diagnostic performance indexes for ncDWI than standard mammography. Heterogeneity was high, thus these results must be interpreted with caution. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kataoka and Iima in this issue.

Automated analysis of the total choline resonance peak in breast proton magnetic resonance spectroscopy.

The aim of the current study was to compare the performance of fully automated software with human expert interpretation of single-voxel proton magnetic resonance spectroscopy (1H-MRS) spectra in the assessment of breast lesions. Breast magnetic resonance imaging (MRI) (including contrast-enhanced T1-weighted, T2-weighted, and diffusion-weighted imaging) and 1H-MRS images of 74 consecutive patients were acquired on a 3-T positron emission tomography-MRI scanner then automatically imported into and analyzed by SpecTec-ULR 1.1 software (LifeTec Solutions GmbH). All ensuing 117 spectra were additionally independently analyzed and interpreted by two blinded radiologists. Histopathology of at least 24 months of imaging follow-up served as the reference standard. Nonparametric Spearman's correlation coefficients for all measured parameters (signal-to-noise ratio [SNR] and integral of total choline [tCho]), Passing and Bablok regression, and receiver operating characteristic analysis, were calculated to assess test diagnostic performance, as well as to compare automated with manual reading. Based on 117 spectra of 74 patients, the area under the curve for tCho SNR and integrals ranged from 0.768 to 0.814 and from 0.721 to 0.784 to distinguish benign from malignant tissue, respectively. Neither method displayed significant differences between measurements (automated vs. human expert readers, p > 0.05), in line with the results from the univariate Spearman's rank correlation coefficients, as well as the Passing and Bablok regression analysis. It was concluded that this pilot study demonstrates that 1H-MRS data from breast MRI can be automatically exported and interpreted by SpecTec-ULR 1.1 software. The diagnostic performance of this software was not inferior to human expert readers.

Current use and future perspectives of contrast-enhanced mammography (CEM): a survey by the European Society of Breast Imaging (EUSOBI).

OBJECTIVES: To perform a survey among members of the European Society of Breast Imaging (EUSOBI) regarding the use of contrast-enhanced mammography (CEM). METHODS: A panel of nine board-certified radiologists developed a 29-item online questionnaire, distributed to all EUSOBI members (inside and outside Europe) from January 25 to March 10, 2023. CEM implementation, examination protocols, reporting strategies, and current and future CEM indications were investigated. Replies were exploratively analyzed with descriptive and non-parametric statistics. RESULTS: Among 434 respondents (74.9% from Europe), 50% (217/434) declared to use CEM, 155/217 (71.4%) seeing less than 200 CEMs per year. CEM use was associated with academic settings and high breast imaging workload (p < 0.001). The lack of CEM adoption was most commonly due to the perceived absence of a clinical need (65.0%) and the lack of resources to acquire CEM-capable systems (37.3%). CEM protocols varied widely, but most respondents (61.3%) had already adopted the 2022 ACR CEM BI-RADS® lexicon. CEM use in patients with contraindications to MRI was the most common current indication (80.6%), followed by preoperative staging (68.7%). Patients with MRI contraindications also represented the most commonly foreseen CEM indication (88.0%), followed by the work-up of inconclusive findings at non-contrast examinations (61.5%) and supplemental imaging in dense breasts (53.0%). Respondents declaring CEM use and higher CEM experience gave significantly more current (p = 0.004) and future indications (p < 0.001). CONCLUSIONS: Despite a trend towards academic high-workload settings and its prevalent use in patients with MRI contraindications, CEM use and progressive experience were associated with increased confidence in the technique. CLINICAL RELEVANCE STATEMENT: In this first survey on contrast-enhanced mammography (CEM) use and perspectives among the European Society of Breast Imaging (EUSOBI) members, the perceived absence of a clinical need chiefly drove the 50% CEM adoption rate. CEM adoption and progressive experience were associated with more extended current and future indications. KEY POINTS: • Among the 434 members of the European Society of Breast Imaging who completed this survey, 50% declared to use contrast-enhanced mammography in clinical practice. • Due to the perceived absence of a clinical need, contrast-enhanced mammography (CEM) is still prevalently used as a replacement for MRI in patients with MRI contraindications. • The number of current and future CEM indications marked by respondents was associated with their degree of CEM experience.

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis.

Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google Scholar, Embase (Ovid), and Web of Science databases for studies published from January 2017 to June 2022. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values were reviewed. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Comparative (QUADAS-2 and QUADAS-C, respectively). A random effects meta-analysis and meta-regression analysis were performed for overall studies and for different study types (reader studies vs historic cohort studies) and imaging techniques (digital mammography vs DBT). Results In total, 16 studies that include 1 108 328 examinations in 497 091 women were analyzed (six reader studies, seven historic cohort studies on digital mammography, and four studies on DBT). Pooled AUCs were significantly higher for standalone AI than radiologists in the six reader studies on digital mammography (0.87 vs 0.81, P = .002), but not for historic cohort studies (0.89 vs 0.96, P = .152). Four studies on DBT showed significantly higher AUCs in AI compared with radiologists (0.90 vs 0.79, P < .001). Higher sensitivity and lower specificity were seen for standalone AI compared with radiologists. Conclusion Standalone AI for screening digital mammography performed as well as or better than radiologists. Compared with digital mammography, there is an insufficient number of studies to assess the performance of AI systems in the interpretation of DBT screening examinations. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Scaranelo in this issue.

Residual fibroglandular breast tissue after mastectomy is associated with an increased risk of a local recurrence or a new primary breast cancer".

BACKGROUND: Residual fibroglandular breast tissue (RFGT) following a mastectomy has been claimed to be associated with the occurrence of an in-breast local recurrence (IBLR) or new primary tumor (NP). Yet, scientific evidence proving this assumption is lacking. The primary aim of the study was to verify whether RFGT following a mastectomy is a risk factor for an IBLR or NP. METHODS: This retrospective analysis included all patients that underwent a mastectomy and were followed up at the Department of Obstetrics and Gynecology of the Medical University of Vienna between 01.01.2015 and 26.02.2020. RFGT volume (assessed on magnetic resonance imaging) was correlated with the prevalence of an IBLR and a NP. RESULTS: A total of 105 patients (126 breasts) following a therapeutic mastectomy were included. After a mean follow-up of 46.0 months an IBLR had occurred in 17 breasts and a NP in 1 breast. A significant difference in RFGT volume was observed between the disease-free cohort and the subgroup with an IBLR or NP (p = .017). A RFGT volume of ≥ 1153 mm3 increased the risk by the factor 3.57 [95%CI 1.27; 10.03]. CONCLUSIONS: RFGT volume is associated with an increased risk for an IBLR or NP.

A survey by the European Society of Breast Imaging on radiologists' preferences regarding quality assurance measures of image interpretation in screening and diagnostic mammography.

OBJECTIVES: Quality assurance (QA) of image interpretation plays a key role in screening and diagnostic mammography, maintaining minimum standards and supporting continuous improvement in interpreting images. However, the QA structure across Europe shows considerable variation. The European Society of Breast Imaging (EUSOBI) conducted a survey among the members to collect information on radiologists' preferences regarding QA measures in mammography. MATERIALS AND METHODS: An anonymous online survey consisting of 25 questions was distributed to all EUSOBI members and national breast radiology bodies in Europe. The questions were designed to collect demographic characteristics, information on responders' mammography workload and data about QA measures currently used in their country. Data was analysed using descriptive statistical analysis, the χ2 test, linear regression, and Durbin-Watson statistic test. RESULTS: In total, 251 breast radiologists from 34 countries completed the survey. Most respondents were providing both screening and symptomatic services (137/251, 54.6%), working in an academic hospital (85/251, 33.9%) and reading 1000-4999 cases per year (109/251, 43.4%). More than half of them (133/251, 53%) had established QA measures in their workplace. Although less than one-third (71/251, 28.3%) had to participate in regular performance testing, the vast majority (190/251, 75.7%) agreed that a mandatory test would be helpful to improve their skills. CONCLUSION: QA measures were in place for more than half of the respondents working in screening and diagnostic mammography to evaluate their breast imaging performance. Although there were substantial differences between countries, the importance of having QA in the workplace and implemented was widely acknowledged by radiologists. CLINICAL RELEVANCE STATEMENT: Although several quality assurance (QA) measures of image interpretation are recommended by European bodies or national organisations, the QA in mammography is quite heterogenous between countries and reporting settings, and not always actively implemented across Europe. KEY POINTS: The first survey that presents radiologists' preferences regarding QA measures of image interpretation in mammography. Quality assurance measures in the workplace are better-established for breast screening compared to diagnostic mammography. Radiologists consider that performance tests would help to improve their mammography interpretation skills.

Influence of dilution on arterial-phase artifacts and signal intensity on gadoxetic acid-enhanced liver MRI.

OBJECTIVES: To investigate the effect of saline-diluted gadoxetic acid, done for arterial-phase (AP) artifact reduction, on signal intensity (SI), and hence focal lesion conspicuity on MR imaging. METHODS: We retrospectively examined 112 patients who each had at least two serial gadoxetic acid-enhanced liver MRIs performed at 1 ml/s, first with non-diluted (ND), then with 1:1 saline-diluted (D) contrast. Two blinded readers independently analyzed the artifacts and graded dynamic images using a 5-point scale. The absolute SI of liver parenchyma, focal liver lesions (if present), aorta, and portal vein at the level of the celiac trunk and the SI of the paraspinal muscle were measured in all phases. The signal-to-norm (SINorm) of the vascular structures, hepatic parenchyma and focal lesions, and the contrast-to-norm (CNorm) of focal liver lesions were calculated. RESULTS: AP artifacts were significantly reduced with dilution. Mean absolute contrast-enhanced liver SI was significantly higher on the D exams compared to the ND exams. Likewise, SINorm of liver parenchyma was significantly higher in all contrast-enhanced phases except transitional phase on the D exams. SINorm values in the AP for the aorta and in the PVP for portal vein were significantly higher on the diluted exams. The CNorm was not significantly different between ND and D exams for lesions in any imaging phase. The interclass correlation coefficient was excellent (0.89). CONCLUSION: Gadoxetic acid dilution injected at 1ml/s produces images with significantly fewer AP artifacts but no significant loss in SINorm or CNorm compared to standard non-diluted images. KEY POINTS: • Diluted gadoxetic acid at slow injection (1 ml/s) yielded images with higher SINorm of the liver parenchyma and preserved CNorm for focal liver lesions. • Gadoxetic acid-enhanced MRI injected at 1 ml/s is associated with arterial-phase (AP) artifacts in 31% of exams, which may degrade image quality and limits focal liver lesion detection. • Saline dilution of gadoxetic acid 1:1 combined with a slow injection rate of 1 ml/s significantly reduced AP artifacts from 31 to 9% and non-diagnostic AP artifacts from 16 to 1%.

Image quality of DWI at breast MRI depends on the amount of fibroglandular tissue: implications for unenhanced screening.

OBJECTIVES: To compare image quality of diffusion-weighted imaging (DWI) and contrast-enhanced breast MRI (DCE-T1) stratified by the amount of fibroglandular tissue (FGT) as a measure of breast density. METHODS: Retrospective, multi-reader, bicentric visual grading analysis study on breast density (A-D) and overall image and fat suppression quality of DWI and DCE-T1, scored on a standard 5-point Likert scale. Cross tabulations and visual grading characteristic (VGC) curves were calculated for fatty breasts (A/B) versus dense breasts (C/D). RESULTS: Image quality of DWI was higher in the case of increased breast density, with good scores (score 3-5) in 85.9% (D) and 88.4% (C), compared to 61.6% (B) and 53.5% (A). Overall image quality of DWI was in favor of dense breasts (C/D), with an area under the VGC curve of 0.659 (p < 0.001). Quality of DWI and DCE-T1 fat suppression increased with higher breast density, with good scores (score 3-5) for 86.9% and 45.7% of density D, and 90.2% and 42.9% of density C cases, compared to 76.0% and 33.6% for density B and 54.7% and 29.6% for density A (DWI and DCE-T1 respectively). CONCLUSIONS: Dense breasts show excellent fat suppression and substantially higher image quality in DWI images compared with non-dense breasts. These results support the setup of studies exploring DWI-based MR imaging without IV contrast for additional screening of women with dense breasts. CLINICAL RELEVANCE STATEMENT: Our findings demonstrate that image quality of DWI is robust in women with an increased amount of fibroglandular tissue, technically supporting the feasibility of exploring applications such as screening of women with mammographically dense breasts. KEY POINTS: • Image and fat suppression quality of diffusion-weighted imaging are dependent on the amount of fibroglandular tissue (FGT) which is closely connected to breast density. • Fat suppression quality in diffusion-weighted imaging of the breast is best in women with a high amount of fibroglandular tissue. • High image quality of diffusion-weighted imaging in women with a high amount of FGT in MRI supports that the technical feasibility of DWI can be explored in the additional screening of women with mammographically dense breasts.

Contrast-enhanced Mammography versus Contrast-enhanced Breast MRI: A Systematic Review and Meta-Analysis.

Background Contrast-enhanced mammography (CEM) is a more accessible alternative to contrast-enhanced MRI (CE-MRI) in breast imaging, but a summary comparison of published studies is lacking. Purpose To directly compare the performance of CEM and CE-MRI regarding sensitivity, specificity, and negative predictive value in detecting breast cancer, involving all publicly available studies in the English language. Materials and Methods Two readers extracted characteristics of studies investigating the comparative diagnostic performance of CEM and CE-MRI in detecting breast cancer. Studies published until April 2021 were eligible. Sensitivity, specificity, negative predictive value, and positive and negative likelihood ratios were calculated using bivariate random effects models. A Fagan nomogram was used to identify the maximum pretest probability at which posttest probabilities of a negative CEM or CE-MRI examination were in line with the 2% malignancy rate benchmark for downgrading a Breast Imaging Reporting and Data System (BI-RADS) category 4 to a BI-RADS category 3 result. I 2 statistics, Deeks funnel plot asymmetry test for publication bias, and meta-regression were used. Results Seven studies investigating 1137 lesions (654 malignant, 483 benign) with an average cancer prevalence of 65.3% (range: 47.3%-82.2%) were included. No publication bias was found (P = .57). While the positive likelihood ratio was equal at a value of 3.1 for CE-MRI and 3.6 for CEM, the negative likelihood ratio of CE-MRI (0.04) was lower than that with CEM (0.12). CE-MRI had higher sensitivity for breast cancer than CEM (97% [95% CI: 86, 99] vs 91% [95% CI: 77, 97], respectively; P < .001) but lower specificity (69% [95% CI: 46, 85] vs 74% [95% CI: 52, 89]; P = .09). A Fagan nomogram demonstrated that the maximum pretest probability at which both tests could rule out breast cancer was 33% for CE-MRI and 14% for CEM. Furthermore, iodine concentration was positively associated with CEM sensitivity and negatively associated with its specificity (P = .04 and P < .001, respectively). Conclusion Contrast-enhanced MRI had superior sensitivity and negative likelihood ratios with higher pretest probabilities to rule out malignancy compared with contrast-enhanced mammography. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Mann and Veldhuis in this issue.

Breast MRI: does a clinical decision algorithm outweigh reader experience?

OBJECTIVES: Due to its high sensitivity, DCE MRI of the breast (MRIb) is increasingly used for both screening and assessment purposes. The Kaiser score (KS) is a clinical decision algorithm, which formalizes and guides diagnosis in breast MRI and is expected to compensate for lesser reader experience. The aim was to evaluate the diagnostic performance of untrained residents using the KS compared to off-site radiologists experienced in breast imaging using only MR BI-RADS. METHODS: Three off-site, board-certified radiologists, experienced in breast imaging, interpreted MRIb according to the MR BI-RADS scale. The same studies were read by three residents in radiology without prior training in breast imaging using the KS. All readers were blinded to clinical information. Histology was used as the gold standard. Statistical analysis was conducted by comparing the AUC of the ROC curves. RESULTS: A total of 80 women (median age 52 years) with 93 lesions (32 benign, 61 malignant) were included. The individual within-group performance of the three expert readers (AUC 0.723-0.742) as well as the three residents was equal (AUC 0.842-0.928), p > 0.05, respectively. But, the rating of each resident using the KS significantly outperformed the experts' ratings using the MR BI-RADS scale (p ≤ 0.05). CONCLUSION: The KS helped residents to achieve better results in reaching correct diagnoses than experienced radiologists empirically assigning MR BI-RADS categories in a clinical "problem solving MRI" setting. These results support that reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience. KEY POINTS: • Reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience in a clinical "problem solving MRI" setting. • The Kaiser score, which provides a clinical decision algorithm for structured reporting, helps residents to reach an expert level in breast MRI reporting and to even outperform experienced radiologists using MR BI-RADS without further formal guidance.

One view or two views for wide-angle tomosynthesis with synthetic mammography in the assessment setting?

OBJECTIVES: To evaluate the diagnostic performance in the assessment setting of three protocols: one-view wide-angle digital breast tomosynthesis (WA-DBT) with synthetic mammography (SM), two-view WA-DBT/SM, and two-view digital mammography (DM). METHODS: Included in this retrospective study were patients who underwent bilateral two-view DM and WA-DBT. SM were reconstructed from the WA-DBT data. The standard of reference was histology and/or 2 years follow-up. Included were 205 women with 179 lesions (89 malignant, 90 benign). Four blinded readers randomly evaluated images to assess density, lesion type, and level of suspicion according to BI-RADS. Three protocols were evaluated: two-view DM, one-view (mediolateral oblique) WA-DBT/SM, and two-view WA-DBT/SM. Detection rate, sensitivity, specificity, and accuracy were calculated and compared using multivariate analysis. Reading time was assessed. RESULTS: The detection rate was higher with two-view WA-DBT/SM (p = 0.063). Sensitivity was higher for two-view WA-DBT/SM compared to two-view DM (p = 0.001) and one-view WA-DBT/SM (p = 0.058). No significant differences in specificity were found. Accuracy was higher with both one-view WA-DBT/SM and two-view WA-DBT/SM compared to DM (p = 0.003 and > 0.001, respectively). Accuracy did not differ between one- and two-view WA-DBT/SM. Two-view WA-DBT/SM performed better for masses and asymmetries. Reading times were significantly longer when WA-DBT was evaluated. CONCLUSIONS: One-view and two-view WA-DBT/SM can achieve a higher diagnostic performance compared to two-view DM. The detection rate and sensitivity were highest with two-view WA-DBT/SM. Two-view WA-DBT/SM appears to be the most appropriate tool for the assessment of breast lesions. KEY POINTS: • Detection rate with two-view wide-angle digital breast tomosynthesis (WA-DBT) is significantly higher than with two-view digital mammography in the assessment setting. • Diagnostic accuracy of one-view and two-view WA-DBT with synthetic mammography (SM) in the assessment setting is higher than that of two-view digital mammography. • Compared to one-view WA-DBT with SM, two-view WA-DBT with SM seems to be the most appropriate tool for the assessment of breast lesions.

Influence of aging and gadolinium exposure on T1, T2, and T2*-relaxation in healthy women with an increased risk of breast cancer with and without prior exposure to gadoterate meglumine at 3.0-T brain MR imaging.

OBJECTIVES: We examined the effects of aging and of gadolinium-based contrast agent (GBCA) exposure on MRI measurements in brain nuclei of healthy women. METHODS: This prospective, IRB-approved single-center case-control study enrolled 100 healthy participants of our high-risk screening center for hereditary breast cancer, who had received at least six doses of macrocyclic GBCA (exposed group) or were newly entering the program (GBCA-naïve group). The cutoff "at least six doses" was chosen to be able to include a sufficient number of highly exposed participants. All participants underwent unenhanced 3.0-T brain MRI including quantitative T1, T2, and R2* mapping and T1- and T2-weighted imaging. The relaxation times/signal intensities were derived from region of interest measurements in the brain nuclei performed by a radiologist and a neuroradiologist, both board certified. Statistical analysis was based on descriptive evaluations and uni-/multivariable analyses. RESULTS: The participants (exposed group: 49, control group: 51) were aged 42 ± 9 years. In a multivariable model, age had a clear impact on R2* (p < 0.001-0.012), T2 (p = 0.003-0.048), and T1 relaxation times/signal intensities (p < 0.004-0.046) for the majority of deep brain nuclei, mostly affecting the substantia nigra, globus pallidus (GP), nucleus ruber, thalamus, and dentate nucleus (DN). The effect of prior GBCA administration on T1 relaxation times was statistically significant for the DN, GP, and pons (p = 0.019-0.037). CONCLUSIONS: In a homogeneous group of young to middle-aged healthy females aging had an effect on T2 and R2* relaxation times and former GBCA applications influenced the measured T1 relaxation times. KEY POINTS: The quantitative T1, T2, and R2* relaxation times measured in women at high risk of developing breast cancer showed characteristic bandwidth for all brain nuclei examined at 3.0-T MRI. The effect of participant age had a comparatively strong impact on R2*, T2, and T1 relaxation times for the majority of brain nuclei examined. The effect of prior GBCA administrations on T1 relaxation times rates was comparatively less pronounced, yielding statistically significant results for the dentate nucleus, globus pallidus, and pons. Healthy women with and without previous GBCA-enhanced breast MRI exhibited age-related T2* and T2 relaxation alterations at 3.0 T-brain MRI. T1 relaxation alterations due to prior GBCA administration were comparatively less pronounced.

Economic potential of abbreviated breast MRI for screening women with dense breast tissue for breast cancer.

OBJECTIVES: Abbreviated breast MRI (AB-MRI) was introduced to reduce both examination and image reading times and to improve cost-effectiveness of breast cancer screening. The aim of this model-based economic study was to analyze the cost-effectiveness of full protocol breast MRI (FB-MRI) vs. AB-MRI in screening women with dense breast tissue for breast cancer. METHODS: Decision analysis and a Markov model were designed to model the cumulative costs and effects of biennial screening in terms of quality-adjusted life years (QALYs) from a US healthcare system perspective. Model input parameters for a cohort of women with dense breast tissue were adopted from recent literature. The impact of varying AB-MRI costs per examination as well as specificity on the resulting cost-effectiveness was modeled within deterministic sensitivity analyses. RESULTS: At an assumed cost per examination of $ 263 for AB-MRI (84% of the cost of a FB-MRI examination), the discounted cumulative costs of both MR-based strategies accounted comparably. Reducing the costs of AB-MRI below $ 259 (82% of the cost of a FB-MRI examination, respectively), the incremental cost-effectiveness ratio of FB-MRI exceeded the willingness to pay threshold and the AB-MRI-strategy should be considered preferable in terms of cost-effectiveness. CONCLUSIONS: Our preliminary findings indicate that AB-MRI may be considered cost-effective compared to FB-MRI for screening women with dense breast tissue for breast cancer, as long as the costs per examination do not exceed 82% of the cost of a FB-MRI examination. KEY POINTS: • Cost-effectiveness of abbreviated breast MRI is affected by reductions in specificity and resulting false positive findings and increased recall rates. • Abbreviated breast MRI may be cost-effective up to a cost per examination of 82% of the cost of a full protocol examination. • Abbreviated breast MRI could be an economically preferable alternative to full protocol breast MRI in screening women with dense breast tissue.

Breast cancer screening in women with extremely dense breasts recommendations of the European Society of Breast Imaging (EUSOBI).

Breast density is an independent risk factor for the development of breast cancer and also decreases the sensitivity of mammography for screening. Consequently, women with extremely dense breasts face an increased risk of late diagnosis of breast cancer. These women are, therefore, underserved with current mammographic screening programs. The results of recent studies reporting on contrast-enhanced breast MRI as a screening method in women with extremely dense breasts provide compelling evidence that this approach can enable an important reduction in breast cancer mortality for these women and is cost-effective. Because there is now a valid option to improve breast cancer screening, the European Society of Breast Imaging (EUSOBI) recommends that women should be informed about their breast density. EUSOBI thus calls on all providers of mammography screening to share density information with the women being screened. In light of the available evidence, in women aged 50 to 70 years with extremely dense breasts, the EUSOBI now recommends offering screening breast MRI every 2 to 4 years. The EUSOBI acknowledges that it may currently not be possible to offer breast MRI immediately and everywhere and underscores that quality assurance procedures need to be established, but urges radiological societies and policymakers to act on this now. Since the wishes and values of individual women differ, in screening the principles of shared decision-making should be embraced. In particular, women should be counselled on the benefits and risks of mammography and MRI-based screening, so that they are capable of making an informed choice about their preferred screening method. KEY POINTS: • The recommendations in Figure 1 summarize the key points of the manuscript.

An A.I. classifier derived from 4D radiomics of dynamic contrast-enhanced breast MRI data: potential to avoid unnecessary breast biopsies.

OBJECTIVES: Due to its high sensitivity, DCE MRI of the breast (bMRI) is increasingly used for both screening and assessment purposes. The high number of detected lesions poses a significant logistic challenge in clinical practice. The aim was to evaluate a temporally and spatially resolved (4D) radiomics approach to distinguish benign from malignant enhancing breast lesions and thereby avoid unnecessary biopsies. METHODS: This retrospective study included consecutive patients with MRI-suspicious findings (BI-RADS 4/5). Two blinded readers analyzed DCE images using a commercially available software, automatically extracting BI-RADS curve types and pharmacokinetic enhancement features. After principal component analysis (PCA), a neural network-derived A.I. classifier to discriminate benign from malignant lesions was constructed and tested using a random split simple approach. The rate of avoidable biopsies was evaluated at exploratory cutoffs (C1, 100%, and C2, ≥ 95% sensitivity). RESULTS: Four hundred seventy (295 malignant) lesions in 329 female patients (mean age 55.1 years, range 18-85 years) were examined. Eighty-six DCE features were extracted based on automated volumetric lesion analysis. Five independent component features were extracted using PCA. The A.I. classifier achieved a significant (p < .001) accuracy to distinguish benign from malignant lesion within the test sample (AUC: 83.5%; 95% CI: 76.8-89.0%). Applying identified cutoffs on testing data not included in training dataset showed the potential to lower the number of unnecessary biopsies of benign lesions by 14.5% (C1) and 36.2% (C2). CONCLUSION: The investigated automated 4D radiomics approach resulted in an accurate A.I. classifier able to distinguish between benign and malignant lesions. Its application could have avoided unnecessary biopsies. KEY POINTS: • Principal component analysis of the extracted volumetric and temporally resolved (4D) DCE markers favored pharmacokinetic modeling derived features. • An A.I. classifier based on 86 extracted DCE features achieved a good to excellent diagnostic performance as measured by the area under the ROC curve with 80.6% (training dataset) and 83.5% (testing dataset). • Testing the resulting A.I. classifier showed the potential to lower the number of unnecessary biopsies of benign breast lesions by up to 36.2%, p < .001 at the cost of up to 4.5% (n = 4) false negative low-risk cancers.

Applications of artificial intelligence in prostate cancer imaging.

PURPOSE OF REVIEW: The purpose of this review was to identify the most recent lines of research focusing on the application of artificial intelligence (AI) in the diagnosis and staging of prostate cancer (PCa) with imaging. RECENT FINDINGS: The majority of studies focused on the improvement in the interpretation of bi-parametric and multiparametric magnetic resonance imaging, and in the planning of image guided biopsy. These initial studies showed that AI methods based on convolutional neural networks could achieve a diagnostic performance close to that of radiologists. In addition, these methods could improve segmentation and reduce inter-reader variability. Methods based on both clinical and imaging findings could help in the identification of high-grade PCa and more aggressive disease, thus guiding treatment decisions. Though these initial results are promising, only few studies addressed the repeatability and reproducibility of the investigated AI tools. Further, large-scale validation studies are missing and no diagnostic phase III or higher studies proving improved outcomes regarding clinical decision making have been conducted. SUMMARY: AI techniques have the potential to significantly improve and simplify diagnosis, risk stratification and staging of PCa. Larger studies with a focus on quality standards are needed to allow a widespread introduction of AI in clinical practice.

[Artificial intelligence in breast imaging : Areas of application from a clinical perspective]. / Künstliche Intelligenz in der Mammadiagnostik : Anwendungsgebiete aus klinischer Perspektive.

CLINICAL/METHODOLOGICAL ISSUE: Central to breast imaging is the coordination of clinical and multimodal imaging information with percutaneous image-guided biopsies and surgical procedures. A wide range of problems arise due to this complexity: missed cancers, overdiagnosis, false-positive findings, unnecessary further imaging, biopsies and surgeries. STANDARD RADIOLOGICAL METHODS: Breast imaging comprises the following diagnostic tests: mammography, tomosynthesis, contrast-enhanced mammography, (multiparametric) ultrasound, magnetic resonance imaging, computed tomography, nuclear medicine derived imaging and hybrid methods. METHODOLOGICAL INNOVATIONS: Artificial intelligence (AI) promises to alleviate practically all these problems of breast imaging. AI has the potential to avoid missed cancers and false-positive findings. Furthermore, it could guide an efficient use of imaging methods and it may potentially be used to define biological phenotypes of breast cancer. PERFORMANCE: AI-based software is being developed for various applications. Most developed are systems that support mammography screening. Problems are monocentric approaches and the focus on short-term financial success. ACHIEVEMENTS: AI promises to improve breast imaging by simplifying and speeding up the workflow, by reducing monotonous tasks and by pointing out problems. This is likely to set free physician capacities that could be invested in improved communication with patients and interdisciplinary colleagues. PRACTICAL RECOMMENDATIONS: The present article mainly addresses clinical needs in breast imaging, pointing out potential areas of use for artificial intelligence. Depending on the definition, a wide array of helpful software tools for breast imaging are already available. Global solutions, however, are still missing.

Low-Dose, Contrast-Enhanced Mammography Compared to Contrast-Enhanced Breast MRI: A Feasibility Study.

Contrast-enhanced MRI (CE-MRI) is the most sensitive technique for breast cancer detection. Contrast-enhanced mammography (CEM) is emerging as a possible alternative to CE-MRI. PURPOSE: To evaluate the diagnostic performance of a low radiation dose contrast-enhanced mammography (L-CEM) in women with suspicious findings on conventional imaging compared to CE-MRI of the breast. STUDY TYPE: Prospective, single center. POPULATION: Women with suspicious findings on mammography, tomosynthesis, or ultrasound, and no contraindications for L-CEM or CE-MRI. Eighty women were included. FIELD STRENGTH/SEQUENCE: 1.5 and 3T CE-MRI, standard protocol for breast, with dedicated coils, according to international guidelines. L-CEM was performed using a dedicated prototype. ASSESSMENT: Three, off-site, blinded readers evaluated the images according to the BI-RADS lexicon in a randomized order, each in two separate reading sessions. Histology served as a gold standard. STATISTICAL TEST: Lesion detection rate, sensitivity, specificity, and negative and positive predictive values (NPV, PPV) were calculated and compared with multivariate statistics. RESULTS: Included were 80 women (mean age, 54.3 years ±11.2 standard deviation) with 93 lesions (32 benign, 61 malignant). The detection rate was significantly higher with CE-MRI (92.5-94.6%; L-CEM 79.6-91.4%, P = 0.014). Sensitivity (L-CEM 65.6-90.2%; CE-MRI 83.6-93.4%, P = 0.086) and NPV (L-CEM 59.6-71.4%; CE-MRI 63.0-76.5%, P = 0.780) did not differ between the modalities. Specificity (L-CEM 46.9-96.9%; CE-MRI 37.5-53.1%, P = 0.001) and PPV (L-CEM 76.4-97.6%; CE-MRI 73.3-77.3%, P = 0.007) were significantly higher with L-CEM. Variations between readers were significant for sensitivity and NPV. The accuracy of L-CEM was as good as CE-MRI (75.3-76.3% vs. 72.0-75.3%, P = 0.514). DATA CONCLUSION: L-CEM showed a high sensitivity and accuracy in women with suspicious findings on conventional imaging. Compared to CE-MRI, L-CEM has the potential to increase specificity and PPV. L-CEM might help to reduce false-positive biopsies while obtaining sensitivity comparable to that of CE-MRI LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:589-595.

Substantial radiation dose reduction with consistent image quality using a novel low-dose stone composition protocol.

PURPOSE: To assess a novel low-dose CT-protocol, combining a 150 kV spectral filtration unenhanced protocol (Sn150 kVp) and a stone-targeted dual-energy CT (DECT) in patients with urolithiasis. METHODS: 232 (151 male, 49 ± 16.4 years) patients with urolithiasis received a low-dose non-contrast enhanced CT (NCCT) for suspected urinary stones either on a third-generation dual-source CT system (DSCT) using Sn150 kVp (n = 116, group 1), or on a second-generation DSCT (n = 116 group 2) using single energy (SE) 120 kVp. For group 1, a subsequent dual-energy CT (DECT) with a short stone-targeted scan range was performed. Objective and subjective image qualities were assessed. Radiation metrics were compared. RESULTS: 534 stones (group 1: n = 242 stones; group 2: n = 292 stones) were found. In group 1, all 215 stones within the stone-targeted DECT-scan range were identified. DE analysis was able to distinguish between UA and non-UA calculi in all collected stones. 11 calculi (5.12%) were labeled as uric acid (UA) while 204 (94.88%) were labeled as non-UA calculi. There was no significant difference in overall Signal-to-noise-ratio between group 1 and group 2 (p = 0.819). On subjective analysis both protocols achieved a median Likert rating of 2 (p = 0.171). Mean effective dose was significantly lower for combined Sn150 kVp and stone-targeted DECT (3.34 ± 1.84 mSv) compared to single energy 120 kVp NCCT (4.45 ± 2.89 mSv) (p < 0.001), equaling a 24.9% dose reduction. CONCLUSION: The evaluated novel low-dose stone composition protocol allows substantial radiation dose reduction with consistent high diagnostic image quality.

The Kaiser score reliably excludes malignancy in benign contrast-enhancing lesions classified as BI-RADS 4 on breast MRI high-risk screening exams.

OBJECTIVES: MRI is an integral part of breast cancer screening in high-risk patients. We investigated whether the application of the Kaiser score, a clinical decision-support tool, may be used to exclude malignancy in contrast-enhancing lesions classified as BI-RADS 4 on breast MRI screening exams. METHODS: This retrospective study included 183 consecutive, histologically proven, suspicious (MR BI-RADS 4) lesions detected within our local high-risk screening program. All lesions were evaluated according to the Kaiser score for breast MRI by three readers blinded to the final histopathological diagnosis. The Kaiser score ranges from 1 (lowest, cancer very unlikely) to 11 (highest, cancer very likely) and reflects increasing probabilities of malignancy, with scores greater than 4 requiring biopsy. Receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic accuracy. RESULTS: There were 142 benign and 41 malignant lesions, diagnosed in 159 patients (mean age, 43.6 years). Median Kaiser scores ranged between 2 and 5 in benign and 7 and 8 in malignant lesions. For all lesions, the Kaiser score's accuracy, represented by the area under the curve (AUC), ranged between 86.5 and 90.2. The sensitivity of the Kaiser score was high, between 95.1 and 97.6% for all lesions, and was best in mass lesions. Application of the Kaiser score threshold for malignancy (≤ 4) could have potentially avoided 64 (45.1%) to 103 (72.5%) unnecessary biopsies in 142 benign lesions previously classified as BI-RADS 4. CONCLUSIONS: The use of Kaiser score in high-risk MRI screening reliably excludes malignancy in more than 45% of contrast-enhancing lesions classified as BI-RADS 4. KEY POINTS: • The Kaiser score shows high diagnostic accuracy in identifying malignancy in contrast-enhancing lesions in patients undergoing high-risk screening for breast cancer. • The application of the Kaiser score may avoid > 45% of unnecessary breast biopsies in high-risk patients. • The Kaiser score aids decision-making in high-risk breast cancer MRI screening programs.