Virtual Touch IQ elastography reduces unnecessary breast biopsies by applying quantitative "rule-in" and "rule-out" threshold values.

Our purpose was to evaluate Virtual Touch IQ (VTIQ) elastography and identify quantitative "rule-in" and "rule-out" thresholds for the probability of malignancy, which can help avoid unnecessary breast biopsies. 189 patients with 196 sonographically evident lesions were included in this retrospective, IRB-approved study. Quantitative VTIQ images of each lesion measuring the respective maximum Shear Wave Velocity (SWV) were obtained. Paired and unpaired, non-parametric statistics were applied for comparisons as appropriate. ROC-curve analysis was used to analyse the diagnostic performance of VTIQ and to specify "rule-in" and "rule-out" thresholds for the probability of malignancy. The standard of reference was either histopathology or follow-up stability for >24 months. 84 lesions were malignant and 112 benign. Median SWV of benign lesions was significantly lower than that of malignant lesions (p 98% with a concomitant significant (p = 0.032) reduction in false positive cases of almost 15%, whereas a "rule-in" threshold of 6.5 m/s suggested a probability of malignancy of >95%. In conclusion, VTIQ elastography accurately differentiates malignant from benign breast lesions. The application of quantitative "rule-in" and "rule-out" thresholds is feasible and allows reduction of unnecessary benign breast biopsies by almost 15%

A Simple Ultrasound Based Classification Algorithm Allows Differentiation of Benign from Malignant Breast Lesions by Using Only Quantitative Parameters.

PURPOSE: We hypothesized that different quantitative ultrasound (US) parameters may be used as complementary diagnostic criteria and aimed to develop a simple classification algorithm to distinguish benign from malignant breast lesions and aid in the decision to perform biopsy or not. PROCEDURES: One hundred twenty-four patients, each with one biopsy-proven, sonographically evident breast lesion, were included in this prospective, IRB-approved study. Each lesion was examined with B-mode US, Color/Power Doppler US and elastography (Acoustic Radiation Force Impulse-ARFI). Different quantitative parameters were recorded for each technique, including pulsatility (PI) and resistive Index (RI) for Doppler US and lesion maximum, intermediate, and minimum shear wave velocity (SWVmax, SWVinterm, and SWVmin) as well as lesion-to-fat SWV ratio for ARFI. Receiver operating characteristic curve (ROC) analysis was used to evaluate the diagnostic performance of each quantitative parameter. Classification analysis was performed using the exhaustive chi-squared automatic interaction detection method. Results include the probability for malignancy for every descriptor combination in the classification algorithm. RESULTS: Sixty-five lesions were malignant and 59 benign. Out of all quantitative indices, maximum SWV (SWVmax), and RI were included in the classification algorithm, which showed a depth of three ramifications (SWVmax ≤ or > 3.16; if SWVmax ≤ 3.16 then RI ≤ 0.66, 0.66-0.77 or > 0.77; if RI ≤ 0.66 then SWVmax ≤ or > 2.71). The classification algorithm leads to an AUC of 0.887 (95 % CI 0.818-0.937, p < 0.0001), a sensitivity of 98.46 % (95 % CI 91.7-100 %), and a specificity of 61.02 % (95 % CI 47.4-73.5 %). By applying the proposed algorithm, a false-positive biopsy could have been avoided in 61 % of the cases. CONCLUSIONS: A simple classification algorithm incorporating two quantitative US parameters (SWVmax and RI) shows a high diagnostic performance, being able to accurately differentiate benign from malignant breast lesions and lower the number of unnecessary breast biopsies in up to 60 % of all cases, avoiding any subjective interpretation bias

Breast lesion detection and characterization with contrast-enhanced magnetic resonance imaging: Prospective randomized intraindividual comparison of gadoterate meglumine (0.15 mmol/kg) and gadobenate dimeglumine (0.075 mmol/kg) at 3T.

BACKGROUND: Contrast-enhanced magnetic resonance imaging (CE-MRI) of the breast is highly sensitive for breast cancer detection. Multichannel coils and 3T scanners can increase signal, spatial, and temporal resolution. In addition, the T1 -reduction effect of a gadolinium-based contrast agent (GBCA) is higher at 3T. Thus, it might be possible to reduce the dose of GBCA at 3T without losing diagnostic information. PURPOSE: To compare a three-quarter (0.075 mmol/kg) dose of the high-relaxivity GBCA gadobenate dimeglumine, with a 1.5-fold higher than on-label dose (0.15 mmol/kg) of gadoterate meglumine for breast lesion detection and characterization at 3T CE-MRI. STUDY TYPE: Prospective, randomized, intraindividual comparative study. POPULATION: Eligible were patients with imaging abnormalities (BI-RADS 0, 4, 5) on conventional imaging. Each patient underwent two examinations, 24-72 hours apart, one with 0.075 mmol/kg gadobenate and the other with 0.15 mmol/kg gadoterate administered in a randomized order. In all, 109 patients were prospectively recruited. FIELD STRENGTH/SEQUENCE: 3T MRI with a standard breast protocol (dynamic-CE, T2 w-TSE, STIR-T2 w, DWI). ASSESSMENT: Histopathology was the standard of reference. Three blinded, off-site breast radiologists evaluated the examinations using the BI-RADS lexicon. STATISTICAL TESTS: Lesion detection, sensitivity, specificity, and diagnostic accuracy were calculated per-lesion and per-region, and compared by univariate and multivariate analysis (Generalized Estimating Equations, GEE). RESULTS: Five patients were excluded, leaving 104 women with 142 histologically verified breast lesions (109 malignant, 33 benign) available for evaluation. Lesion detection with gadobenate (84.5-88.7%) was not inferior to gadoterate (84.5-90.8%) (P ≥ 0.165). At per-region analysis, gadobenate demonstrated higher specificity (96.4-98.7% vs. 92.6-97.3%, P ≤ 0.007) and accuracy (96.3-97.8% vs. 93.6-96.1%, P ≤ 0.001) compared with gadoterate. Multivariate analysis demonstrated superior, reader-independent diagnostic accuracy with gadobenate (odds ratio = 1.7, P < 0.001 using GEE). DATA CONCLUSION: A 0.075 mmol/kg dose of the high-relaxivity contrast agent gadobenate was not inferior to a 0.15 mmol/kg dose of gadoterate for breast lesion detection. Gadobenate allowed increased specificity and accuracy. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1157-1165

Microstructural breast tissue characterization: A head-to-head comparison of Diffusion Weighted Imaging and Acoustic Radiation Force Impulse elastography with clinical implications

Abstract Purpose Head-to-head comparison of Diffusion Weighted Imaging (DWI) and Acoustic Radiation Force Impulse (ARFI) elastography regarding the characterization of breast lesions in an assessment setting. Method Patients undergoing an ultrasound examination including ARFI and an MRI protocol including DWI for the characterization of a BI-RADS 3–5 breast lesion between 06/2013 and 10/2016 were eligible for inclusion in this retrospective, IRB-approved study. 60 patients (30–84 years, median 50) with a median lesion size of 16 mm (range 5–55 mm) were included. The maximum shear wave velocity (SWVmax) and mean apparent diffusion coefficient (ADCmean) for each lesion were retrospectively evaluated by a radiologist experienced in the technique. Histology was the reference standard. Diagnostic performances of ARFI and DWI were assessed using ROC curve analysis. Spearman's rank correlation coefficient and multivariate logistic regression were used to investigate the independence of both tests regarding their diagnostic information to distinguish benign from malignant lesions. Results Corresponding areas under the ROC curve for differentiation of benign (n = 16) and malignant (n = 49) lesions were 0.822 (ARFI) and 0.871 (DWI, p-value = 0.48). SWVmax and ADCmean values showed a significant negative correlation (ρ = −0.501, p-value Conclusion Significant correlation between quantitative findings of ARFI and DWI in breast lesions exists. Thus, ARFI provides similar diagnostic information as a DWI-including protocol of an additional "problem-solving" MRI for the characterization of a sonographically evident breast lesion, improving the immediate patient management in the assessment setting

A simple classification system (the Tree flowchart) for breast MRI can reduce the number of unnecessary biopsies in MRI-only lesions.

OBJECTIVES: To assess whether using the Tree flowchart obviates unnecessary magnetic resonance imaging (MRI)-guided biopsies in breast lesions only visible on MRI. METHODS: This retrospective IRB-approved study evaluated consecutive suspicious (BI-RADS 4) breast lesions only visible on MRI that were referred to our institution for MRI-guided biopsy. All lesions were evaluated according to the Tree flowchart for breast MRI by experienced readers. The Tree flowchart is a decision rule that assigns levels of suspicion to specific combinations of diagnostic criteria. Receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic accuracy. To assess reproducibility by kappa statistics, a second reader rated a subset of 82 patients. RESULTS: There were 454 patients with 469 histopathologically verified lesions included (98 malignant, 371 benign lesions). The area under the curve (AUC) of the Tree flowchart was 0.873 (95% CI: 0.839-0.901). The inter-reader agreement was almost perfect (kappa: 0.944; 95% CI 0.889-0.998). ROC analysis revealed exclusively benign lesions if the Tree node was ≤2, potentially avoiding unnecessary biopsies in 103 cases (27.8%). CONCLUSIONS: Using the Tree flowchart in breast lesions only visible on MRI, more than 25% of biopsies could be avoided without missing any breast cancer. KEY POINTS: • The Tree flowchart may obviate >25% of unnecessary MRI-guided breast biopsies. • This decrease in MRI-guided biopsies does not cause any false-negative cases. • The Tree flowchart predicts 30.6% of malignancies with >98% specificity. • The Tree's high specificity aids in decision-making after benign biopsy results

Multiparametric high-resolution 3-D sonography with ColorPower-Doppler, elastography and contrast-enhanced sonography for an improved detection and characterization of breast tumors : Multiparametric ultrasound of the breast

Brustkrebs ist die häufigste Krebsart bei Frauen in weiten Teilen der Welt und die häufigste krebsbedingte Todesursache für Frauen weltweit. Ultraschall (US) der Brust ist eine wertvolle Ergänzung zur Mammographie, weist jedoch eine variable, allgemein eher moderate Spezifität sowie eine hohe Untersucherabhängigkeit auf. Der üblicherweise durchgeführte B-Mode US erfasst ausschließlich morphologische Informationen. In den letzten Jahren wurden mehrere komplementäre US-Modalitäten in die Klinik eingeführt, welche einen Einblick in funktionelle Gewebeeigenschaften ermöglichen: Elastographie, Doppler und kontrastmittelverstärkter US (KMUS). Da diese Verfahren quantitative Parameter erfassen, können sie potentiell als bildgebende Biomarker eingesetzt werden. Das Ziel dieser Arbeit war die Evaluation eines multiparametrischen (mp) Ansatzes, um den Mehrwert der genannten komplementären US-Modalitäten zum B-Mode US für die Differenzierung von benignen und malignen Brustläsionen zu evaluieren. Ein Fokus lag dabei auf der Erhöhung der Spezifität des Brust-US zwecks Vermeidung unnötiger Brustbiopsien. Der erste Teil evaluierte eine neue quantitative Elastographie-Technik, Virtual Touch IQ (VTIQ) bezüglich diagnostischer Genauigkeit und Reproduzierbarkeit im klinischen Einsatz. Nach den Ergebnissen dieser Studie zeigen bösartige Brusttumoren konsequent höhere Scherwellengeschwindigkeiten (SWV) und Läsion-zu-Fett-SWV-Verhältnisse als gutartige. Überdies weisen die akquirierten Messungen eine moderate Interprüfer-Reproduzierbarkeit auf. Somit kann diese Technik im klinischen Umfeld für die Differenzierung von gutartigen von bösartigen Brusttumoren eingesetzt werden. Der nächste Teil untersuchte, ob durch Einführung von SWV-Schwellenwerten in der VTIQ maligne Brustläsionen effektiv ausgeschlossen oder bestätigt werden können. Diese Studie zeigte, dass solche "Ein-" und "Ausschluss-" Kriterien existieren und klinisch anwendbar sind. Das "Ausschlusskriterium" kann die Anzahl der unnötigen, falsch positiven Biopsieempfehlungen nach Brust-US signifikant zu reduzieren, während das "Einschlusskriterium" die diagnostische Sicherheit des Untersuchers erhöhen kann. Der dritte Teil dieser Arbeit bewertete mehrere quantitative Parameter die mittels Doppler und VTIQ-Elastographie erhoben wurden und zielte auf die Entwicklung eines Klassifikationsalgorithmus für US-detektierte Brustläsionen. Der berechnete Algorithmus schließt nur einen quantitativen Parameter aus Doppler (Resistive Index) und einen aus VTIQ (maximale SWV) ein und zeigte eine hohe diagnostische Genauigkeit für die Charakterisierung von Brustläsionen. Daraus ergab sich explorativ ein Potential für eine Reduktion falsch positiver Biopsien um >60%. Der letzte Teil fokussierte auf die Evaluierung des mp Brust-US durch die Prüfung verschiedener Kombinationen von quantitativen US-Parametern (Doppler, VTIQ und KMUS) mit B-Mode US. Die Ergebnisse dieser Studie zeigten unabhängig vom Erfahrungsstand des Untersuchers die höchste diagnostische Genauigkeit für die Kombination von drei Parametern im mpUS (B-Mode US, VTIQ und CEUS). Die gleichzeitige Bewertung der Vaskularisation (CEUS) und der Elastizität (VTIQ) vom Gewebe haben offenbar einen komplementären Wert. Auch dieser Ansatz zeigte ein signifikantes Potential zur Reduktion von falsch positiven Brustbiopsien. Abschließend wurden im Rahmen dieser These empirische Daten generiert, welche durch multiparametrische Kombination morphologischer und funktioneller US-Modalitäten ein hohes Potenzial zur Erhöhung der Spezifität des Brust-US und somit der Vermeidung unnötiger Biopsien aufzeigen. Die quantitative Beurteilung der Gewebeelastizität erlaubt mittels Schwellenwerten eine akkurate Risikostratifizierung von Brustläsionen im US. Die höchste diagnostische Genauigkeit des Brust-US wurde durch die gleichzeitige Bewertung der Gewebemorphologie, Elastizität und Vaskularisation erreicht.Breast cancer is the most common form of cancer in women throughout large parts of the world and the leading cause of female cancer-related death worldwide. Breast ultrasound (US) is a valuable adjunct to mammography- however, it demonstrates a variable, but generally moderate specificity and a high-degree of inter-examiner variability. The usually performed B mode US only offers morphological information about tumors. In recent years several complementary US modalities have been developed, which offer a deeper insight into functional tissue properties, including elastography, Doppler and contrast enhanced US (CEUS). All of them have the advantage of offering quantitative parameters, which may potentially be used as imaging biomarkers. The aim of this thesis was to evaluate the added value of each of the aforementioned complementary modalities to B mode US in a multiparametric (mp) approach for the differentiation of benign from malignant breast lesions, thus raising the specificity of breast US and obviating unnecessary breast biopsies. The first part evaluates a new quantitative elastographic technique, namely Virtual Touch IQ (VTIQ) by assessing its diagnostic performance and its reproducibility in the clinical setting. According to the findings of this study, malignant breast tumors consistently show higher shear wave velocities (SWV) and lesion-to-fat SWV ratios than benign ones. Moreover, the acquired measurements demonstrate a moderate inter-examiner reproducibility, proving that this technique can be used in the clinical setting for the differentiation of benign from malignant breast tumors. The next part investigates the introduction of VTIQ-measured SWV threshold values, than can effectively exclude or confirm malignancy of breast lesions. The results of this study show that the introduction of such “rule-in” and “rule-out” cut off values is feasible. The “rule-out” criterion has the potential to significantly reduce the number of unnecessary, false-positive biopsy recommendations of breast US, while the “rule-in” criterion can raise the diagnostic confidence of the examiner. The third part of this thesis assesses several quantitative parameters acquired from Doppler and VTIQ elastography and focuses on the development of a classification algorithm for US detected breast lesions. The calculated algorithm, using only one quantitative parameter from Doppler (resistive index) and one from VTIQ (maximum SWV) demonstrates a high diagnostic accuracy for breast lesion characterization, helping to significantly decrease false-positive biopsies by >60%. The final part focuses on the evaluation of mp breast US by testing several combinations of quantitative US parameters (Doppler, VTIQ and CEUS) with B mode US. The findings of this study prove that mpUS with three parameters (B mode US, VTIQ and CEUS) demonstrates the highest diagnostic performance, irrespective of the experience level of the examiner and that the simultaneous assessment of tissue vascularity (CEUS) and elasticity (VTIQ) have a complementary value. This approach also leads to a significant reduction in false-positive breast biopsies. To conclude, this thesis adds to a growing body of evidence, which suggests that the addition of functional US modalities has the potential to increase the specificity of breast US and obviate unnecessary biopsy recommendations. The quantitative assessment of tissue elasticity provides threshold values that can confirm or exclude breast malignancy. Nevertheless, the highest diagnostic accuracy of breast US is accomplished by a concurrent evaluation of tissue morphology, elasticity and vascularization.Abweichender Titel laut Übersetzung der Verfasserin/des VerfassersArbeit an der Bibliothek noch nicht eingelangt - Daten nicht geprüftMedizinische Universität Wien, Diss., 2018(VLID)287041

New diagnostic tools for breast cancer

Imaging plays a major role in the diagnosis, treatment, and follow-up of breast cancer. Findings that require further assessment will be detected both at screening and curative mammography. Most findings that are further worked up tend to yield benign diagnoses. Consequently, there is an ongoing search for new tools to reduce recalls and unnecessary biopsies while maintaining or improving cancer detection rates. The clinically most promising methods in this respect are described and discussed in this review.(VLID)363258

Correct determination of the enhancement curve is critical to ensure accurate diagnosis using the Kaiser score as a clinical decision rule for breast MRI

10.1016/j.ejrad.2021.109630European Journal of Radiology13810963

Density and tailored breast cancer screening: practice and prediction an overview

Mammography, as the primary screening modality, has facilitated a substantial decrease in breast cancer-related mortality in the general population. However, the sensitivity of mammography for breast cancer detection is decreased in women with higher breast densities, which is an independent risk factor for breast cancer. With increasing public awareness of the implications of a high breast density, there is an increasing demand for supplemental screening in these patients. Yet, improvements in breast cancer detection with supplemental screening methods come at the expense of increased false-positives, recall rates, patient anxiety, and costs. Therefore, breast cancer screening practice must change from a general one-size-fits-all approach to a more personalized, risk-based one that is tailored to the individual womans risk, personal beliefs, and preferences, while accounting for cost, potential harm, and benefits. This overview will provide an overview of the available breast density assessment modalities, the current breast density screening recommendations for women at average risk of breast cancer, and supplemental methods for breast cancer screening. In addition, we will provide a look at the possibilities for a risk-adapted breast cancer screening.(VLID)479970

Virtual Touch IQ elastography reduces unnecessary breast biopsies by applying quantitative “rule-in” and “rule-out” threshold values

Our purpose was to evaluate Virtual Touch IQ (VTIQ) elastography and identify quantitative “rule-in” and “rule-out” thresholds for the probability of malignancy, which can help avoid unnecessary breast biopsies. 189 patients with 196 sonographically evident lesions were included in this retrospective, IRB-approved study. Quantitative VTIQ images of each lesion measuring the respective maximum Shear Wave Velocity (SWV) were obtained. Paired and unpaired, non-parametric statistics were applied for comparisons as appropriate. ROC-curve analysis was used to analyse the diagnostic performance of VTIQ and to specify “rule-in” and “rule-out” thresholds for the probability of malignancy. The standard of reference was either histopathology or follow-up stability for >24 months. 84 lesions were malignant and 112 benign. Median SWV of benign lesions was significantly lower than that of malignant lesions (p<0.001). The application of a “rule-out” threshold of 1.9m/s lead to a sensitivity of >98% with a concomitant significant (p=0.032) reduction in false positive cases of almost 15%, whereas a “rule-in” threshold of 6.5m/s suggested a probability of malignancy of >95%. In conclusion, VTIQ elastography accurately differentiates malignant from benign breast lesions. The application of quantitative “rule-in” and “rule-out” thresholds is feasible and allows reduction of unnecessary benign breast biopsies by almost 15%.(VLID)464138