Dynamic Magnetic Resonance Mammography Research Articles

Curvelet analysis of breast masses on dynamic magnetic resonance mammography

This study is devoted to extracting significant texture features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast using curvelet features and to classify breast masses into malignant and benign using the calculated features. The authors utilised the first generation of curvelet transform in the interpretation of breast tumours on DCE-MRI. The analysis is performed after injecting 23 patients with a contrast agent and 23 mass lesions were extracted from these patients. Then, 288 statistical parameters were extracted by calculating the mean and variance of the curvelet coefficients of tumour texture in sub-band images. Due to a large number of extracted features and the presence of redundant and inter-correlated descriptors, they used a combination of genetic algorithm (GA) and Pearson's correlation for feature selection and a three-layer artificial neural network (ANN) for classification of malignant and benign breast lesions. The GA-ANN model has yielded a good diagnostic accuracy (96%), sensitivity (92%) and specificity (100%). Also, the area under the receiver operating characteristic curve was 0.955. The curvelet transform was able to effectively quantify the distribution of contrast agent in tumour texture, which is different in malignant and benign tumours.

Magnetic resonance imaging of intraductal papillomas: typical findings and differential diagnosis.

Even upon core biopsy, accurate classification of benign intraductal papillomas (IPs) can be difficult. Accordingly, IPs are still frequently surgically resected. Therefore, accurate classification of IP by magnetic resonance mammography (MRM) would potentially optimize patient management. However, the few investigations assessing MRM of IP included small patient collectives, and overall accuracy is still unknown. We performed this investigation to analyze the morphologic and dynamic MRM profiles of IP in more detail and to identify the overall accuracy of MRM for differential diagnosis of IP versus malignant breast lesions. Consecutive patients scheduled for MRM (standardized scanning protocols: dynamic T1-weighted gradient echo before/after Gd-DTPA [gadolinium diethylenetriamine pentaacetate; 0.1 mmol/kg body weight]; T2-weighted turbo spin echo) with subsequent surgicopathologic verification were enrolled. For the detailed assessment of morphologic and dynamic profiles, 2 experienced radiologists (>500 MRM examinations; blinded to surgicopathologic verification) performed prospective evaluation of MRM, in consensus, applying 17 predefined MRM descriptors. From this database, all patients showing IP (n = 83) or malignant breast lesions (n = 648) were further evaluated statistically: univariate analyses (association of single descriptors with IP/breast cancer: contingency table statistics) and multivariate analyses were performed to identify accurate descriptor combinations (CHAID [CHi-squared Automatic Interaction Detection]) and overall accuracy of MRM for differential diagnosis of IP versus malignant breast lesions (logistic regression; receiver operating characteristics [ROC], area under the ROC curve). There were 82.4% of MRM descriptors significantly associated with IP (n = 14; P < 0.05). The accuracy of single descriptors (odds ratio [OR], ≤10.6) could be further increased by descriptor combinations (double combination: OR ≤12.7; triple combination: OR ≤15.0). With area under the ROC curve = 0.90, there was a high overall accuracy of MRM for the differential diagnosis of IP versus malignant breast lesions. A detailed assessment of MRM allows precise characterization of benign IPs and accurate differentiation from malignant breast lesions.

SU-E-I-65: Pitfalls in the Production of Enhancement Kinetic Curves in 3T Dynamic Magnetic Resonance Mammography and Means of Avoidance

Purpose: The purpose of the present study is to investigate suggested means for the reduction or even elimination of errors that appear in enhancement kinetic curves in order to avoid pitfalls and increase the sensitivity and specificity of the method. Methods: This retrospective study included 115 women who underwent breast MRI in a magnetic resonance unit 3‐Tesla. In the MRI acquisition the following sequences were used: a) axial T2‐TSE, b) axial STIR and c) Vibrant (six phases) unenhanced and contrast‐enhanced axial T1‐weighted fat saturation. In the semi‐automated technique there was no consistency in the location of the selected region of interest — ROI in all the phases of the dynamic acquisition during the assessment of the kinetic curves. The measurements were repeated by positioning the ROIs manually from stable reference points in all the phases and the enhancement kinetic curves were subsequently plotted based on the signal intensity. Results: 115 patients were examined and 376 abnormalities were investigated. In 81 cases, a change of the enhancement kinetic curve type was found between the two methods. In large and dense breasts there was not any change in the type of the kinetic curves calculated between the two methods, whereas in the large but non‐dense breasts, 13 lesions were found to be of different type. In the case of the small and dense breasts only 4 lesions changed type, whereas in the case of the small and non‐dense breasts, 64 lesions changed type out of which 50 were observed in left breasts and 14 in right breasts. Conclusion: The derivation of enhancement kinetic curves should be performed by controlling and verifying that the ROIs lay at the same location of the lesion in all the phases of the dynamic study. In these cases, the use of stable reference points should be employed.

Normal Breast Parenchyma: Contrast Enhancement Kinetics at Dynamic MR Mammography—Influence of Anthropometric Measures and Menopausal Status

To study T1 baseline signal intensity (SI) and contrast material enhancement kinetics of normal breast parenchyma by using dynamic contrast-enhanced (DCE) magnetic resonance (MR) mammography and to determine the influence of anthropometric measures and menopausal status on the variability of these features. Institutional review board approval and written informed consent were obtained. Between June 2008 and September 2011, 345 women (age range, 26-81 years; mean age, 51.3 years ± 11.6 [standard deviation]) underwent DCE MR mammography, with T1-weighted three-dimensional MR images (repetition time msec/echo time msec, 8.86/4.51; flip angle, 25°) acquired with a 1.5-T whole-body MR unit before and 1, 2, 3, 4, and 5 minutes after a gadobutrol bolus injection of 0.1 mmol per kilogram of body weight. Regions of interest were traced manually, and T1 SI of parenchyma was recorded. The influence of different predictors of T1 baseline SI and contrast enhancement was studied by using random-effects models. T1 baseline SI varied considerably between women, with a mean of 167.7 ± 49.2 (71.4-424.7 [range]) and 175.9 ± 48.9 (51.8-458.3) in the right and the left breast, respectively (P < .01). T1 baseline SI increased linearly with age (P < .0001) and body weight (P < .0001). After contrast material delivery, relative percentage of enhancement was 8.1%, 13.8%, 18.2%, 22.1%, and 24.6% at 1, 2, 3, 4, and 5 minutes, respectively, but varied considerably between women. Contrast enhancement was 9.3% in the lowest quintile and 47.4% in the highest. Contrast enhancement increased with body weight (P < .01) but decreased in postmenopausal women (P < .01). Women with higher baseline T1 SI tended to have a higher contrast enhancement slope. Anthropometric measures and menopausal status contribute to a large variability in contrast enhancement of normal breast parenchyma. This might influence the interpretation of contrast enhancement kinetics of breast lesions and current strategies for determining contrast medium dose for breast MR imaging.

A method for limiting pitfalls in the production of enhancement kinetic curves in 3T dynamic magnetic resonance mammography.

The aim of the present study is to investigate means for the reduction or even elimination of enhancement kinetic curve errors due to breast motion in order to avoid pitfalls and to increase the sensitivity and specificity of the method. 115 women underwent breast Magnetic Resonance Imaging (MRI). All patients were properly immobilized in a dedicated bilateral phased array coil. A magnetic resonance unit 3-Tesla (Signa, GE Healthcare) was used. The following sequences were applied: (I) axial Τ2-TSE, (II) axial STIR and (III) Vibrant axial T1-weighted fat saturation (six phases). Kinetic curves were derived semi-automatically using the software of the system and manually by positioning the regions of interest (ROI) from stable reference points in all the phases. 376 abnormalities in 115 patients were investigated. In 81 (21.5%) cases, a change of the enhancement kinetic curve type was found when the two different methods were used. In cases of large fatty breasts, a change of the enhancement kinetic curve type in 13 lesions was found. In cases of small and dense breasts, only in 4 lesions the kinetic curve type changed, whereas in cases of small and fatty breasts, the kinetic curve type changed in 64 lesions (50 were observed in left breasts and 14 in right breasts). The derivation of enhancement kinetic curves should be performed by controlling and verifying that the ROIs lay at the same location of the lesion in all the phases of the dynamic study.

Application of Computer-aided Diagnosis (CAD) in MR-Mammography (MRM): Do We Really Need Whole Lesion Time Curve Distribution Analysis?

The identification of the most suspect enhancing part of a lesion is regarded as a major diagnostic criterion in dynamic magnetic resonance mammography. Computer-aided diagnosis (CAD) software allows the semi-automatic analysis of the kinetic characteristics of complete enhancing lesions, providing additional information about lesion vasculature. The diagnostic value of this information has not yet been quantified. Consecutive patients from routine diagnostic studies (1.5 T, 0.1 mmol gadopentetate dimeglumine, dynamic gradient-echo sequences at 1-minute intervals) were analyzed prospectively using CAD. Dynamic sequences were processed and reduced to a parametric map. Curve types were classified by initial signal increase (not significant, intermediate, and strong) and the delayed time course of signal intensity (continuous, plateau, and washout). Lesion enhancement was measured using CAD. The most suspect curve, the curve-type distribution percentage, and combined dynamic data were compared. Statistical analysis included logistic regression analysis and receiver-operating characteristic analysis. Fifty-one patients with 46 malignant and 44 benign lesions were enrolled. On receiver-operating characteristic analysis, the most suspect curve showed diagnostic accuracy of 76.7 +/- 5%. In comparison, the curve-type distribution percentage demonstrated accuracy of 80.2 +/- 4.9%. Combined dynamic data had the highest diagnostic accuracy (84.3 +/- 4.2%). These differences did not achieve statistical significance. With appropriate cutoff values, sensitivity and specificity, respectively, were found to be 80.4% and 72.7% for the most suspect curve, 76.1% and 83.6% for the curve-type distribution percentage, and 78.3% and 84.5% for both parameters. The integration of whole-lesion dynamic data tends to improve specificity. However, no statistical significance backs up this finding.

Magnetic resonance imaging of inflammatory breast carcinoma and acute mastitis. A comparative study

The aim of this study was to evaluate the potential of magnetic resonance mammography (MRM) to distinguish inflammatory breast carcinomas (IBC) from acute mastitis (AM). This study compared MRM examinations of two selected groups of patients: 48 subjects with IBC and 42 patients with AM. No statistical differences were revealed between the two groups for morphology of masses and of non-mass-like enhancement, breast enlargement, diffuse skin thickening, abnormal nipple configuration, prominent vessels, and also for cutaneous/subcutaneous, perimamillar and diffuse oedema. However, initial and postinitial dynamic characteristics significantly differed between the two groups (p < 0.001). In IBC, more masses with a greater average size were detected (p < 0.05). The following morphological criteria were also observed more often in IBC (p < 0.05): T2-hypointensity of masses (77.5%/18.2%), blooming sign (62.5%/31.8%), infiltration of pectoralis major muscle (interruption of fat plane: 54.2%/16.7%; pathological enhancement: 33.3%/7.1%), perifocal (66.7%/33.3%), prepectoral (72.9%/31.0%) and intramuscular pectoral oedema (41.7%/7.1%). The main localisation of AM was subareolar, of IBC central or dorsal (p < 0.001). The discrimination between AM and IBC remains a diagnostic challenge because of overlapping imaging features. However, the combination of multiple dynamic and morphological MRM criteria seems to have the potential for a differential diagnosis.

Characterization of breast lesions with CE-MR multimodal morphological and kinetic analysis: Comparison with conventional mammography and high-resolution ultrasound

Objective Evaluation of the diagnostic value of magnetic resonance mammography and comparison with conventional mammography and ultrasonography in cases of women with suspicious breast lesions. Subjects and methods Sixty-nine women (age range 39–68 years) with 78 focal breast lesions were examined with mammography, ultrasonography and dynamic magnetic resonance mammography. The lesions were classified according to the Breast Imaging Reporting and Data System (BI-RADS) lexicon of the American College of Radiology for each diagnostic method. Histological reports were available after biopsy or surgical excision of the lesions. Results Pathological examination confirmed that 53 lesions were malignant and 25 benign. Conventional mammography estimated a total of 59/78 lesions as malignant with 44 true positive lesions, ultrasonography estimated a total of 50/78 lesions as malignant with 44 true positive lesions and magnetic resonance mammography estimated a total of 66/78 lesions as malignant with 52 true positive lesions. Sensitivity and specificity of magnetic resonance mammography in the diagnosis of malignancy was 98.1% and 44%, of conventional mammography 83% and 40% and of ultrasonography 83% and 76%. Negative predictive value for magnetic resonance mammography was 91.7%, for ultrasonography 67.9% and for mammography 52.6% for malignancies. Conclusion Magnetic resonance mammography has the highest negative predictive value compared with mammography and ultrasound in cases of suspicious breast lesions. The combination of morphologic and enhancement criteria can improve the diagnostic capability of magnetic resonance mammography (MRM) in breast lesion characterization.

Signal intensity of normal breast tissue at MR mammography on midfield: Applying a random coefficient model evaluating the effect of doubling the contrast dose

Purpose To prospectively investigate the effect on signal intensity (SI) of healthy breast parenchyma on magnetic resonance mammography (MRM) when doubling the contrast dose from 0.1 to 0.2 mmol/kg bodyweight. Materials and methods Informed consent and institutional review board approval were obtained. Twenty-five healthy female volunteers (median age: 24 years (range: 21–37 years) and median bodyweight: 65 kg (51–80 kg)) completed two dynamic MRM examinations on a 0.6 T open scanner. The inter-examination time was 24 h (23.5–25 h). The following sequences were applied: axial T2W TSE and an axial dynamic T1W FFED, with a total of seven frames. At day 1, an i.v. gadolinium (Gd) bolus injection of 0.1 mmol/kg bodyweight (Omniscan) (low) was administered. On day 2, the contrast dose was increased to 0.2 mmol/kg (high). Injection rate was 2 mL/s (day 1) and 4 mL/s (day 2). Any use of estrogen containing oral contraceptives (ECOC) was recorded. Post-processing with automated subtraction, manually traced ROI (region of interest) and recording of the SI was performed. A random coefficient model was applied. Results We found an SI increase of 24.2% and 40% following the low and high dose, respectively ( P < 0.0001); corresponding to a 65% (95% CI: 37–99%) SI increase, indicating a moderate saturation. Although not statistically significant ( P = 0.06), the results indicated a tendency, towards lower maximal SI in the breast parenchyma of ECOC users compared to non-ECOC users. Conclusion We conclude that the contrast dose can be increased from 0.1 to 0.2 mmol/kg bodyweight, if a better contrast/noise relation is desired but increasing the contrast dose above 0.2 mmol/kg bodyweight is not likely to improve the enhancement substantially due to the moderate saturation observed. Further research is needed to determine the impact of ECOC on the relative enhancement ratio, and further studies are needed to determine if a possible use of ECOC should be considered a compromising factor, if an MRM is indicated in a young woman.

MR-guided vacuum-assisted breast biopsy with a handheld biopsy system: clinical experience and results in postinterventional MR mammography after 24 h

This prospective study evaluates the feasibility of the magnetic resonance (MR)-guided vacuum-assisted breast biopsy with a handheld vacuum-biopsy system and documents the biopsy results with MR mammography 24 h after the procedure. MR-guided biopsy was undertaken in 33 patients with 34 lesions on dynamic MR mammography. The interventions were performed with the handheld 10-gauge Vacora vacuum-biopsy system. In all cases, dynamic MR mammography was performed 24 h after the procedure to determine the extent of the lesion removal and to identify the lesions that were missed. In 5/34 (14.7%) lesions, biopsy was not performed because no suspicious lesion was identified on the day of biopsy. In 25/29 (86.2%) lesions, the biopsy was successfully performed with a complete removal in 4/29 (13.8%) and a partial removal of 21/29 (72.4%) lesions. In 4/29 (13.8%) interventions the lesion was missed with the biopsy. In one case, histopathology after surgical excision revealed ductal carcinoma in situ. Histopathology revealed 9/29 (31%) malignant and 20/29 (68.9%) benign lesions. MR-guided vacuum-assisted breast biopsy with the handheld Vacora vacuum-biopsy system is technically feasible in most cases. MR mammography 24 h after the biopsy should be performed in those cases in which the biopsy success is unclear immediately after the procedure.

Contrast kinetics of the malignant breast tumour—Border versus centre enhancement on dynamic midfield MRI

PurposeTo quantify the border versus centre enhancement of malignant breast tumours on dynamic magnetic resonance mammography. Materials and methodsFifty-two women diagnosed with primary breast cancer underwent dynamic magnetic resonance mammography (Omniscan 0.2mmol/kg bodyweight) on a midfield scanner (0.6T), prior to surgery. The following five variables were recorded from the border and centre regions of the tumours: Early Enhancement, Time to Peak, Wash-in rate, Wash-out rate and Area under Curve. Information on histology type, oestrogen and progesterone receptor status was collected. Statistical analysis was performed in SAS 9.1 as paired samples t-tests. ResultsFifty of 52 malignant tumours displayed a faster Early Enhancement in the border region compared to the centre (p<0.0001). Significant differences between the border and centre values were found for Time to Peak, Wash-in rate, Wash-out rate and Area under Curve. Hormone receptor positive tumours displayed an over-all highly significant difference between border and centre enhancement, whereas no significant differences for any of the five variables were recorded in neither oestrogen nor progesterone hormone receptor negative tumours. ConclusionThe border/centre enhancement difference in malignant breast tumours is easily visualized on midfield dynamic magnetic resonance mammography. The dynamic behaviour is significantly correlated to histological features and receptor status of the tumours.

Is 0.6T magnetic resonance mammography adequate in the detection of breast cancer?

To evaluate whether relevant diagnostic information can be achieved when using magnetic resonance mammography (MRM) on mid-field as a supplement to conventional imaging and clinical examination in women with primary breast cancer. 30 women (55 breasts containing 49 malignant tumors) planned for uni- or bilateral mastectomy were examined with dynamic MRM on mid-field, 0.6T. The women were examined with mammography (M) and ultrasonography (US) prior to MRM. The descriptions of the conventional examinations were evaluated retrospectively, whereas the MRM was evaluated prospectively, with knowledge of the M+US findings. Imaging findings suggesting malignancy were registered and correlated with pathology after mastectomy. A home-made rating system for evaluation of the detected lesions was tested. MRM detected seven additional malignant tumors, failed to detect three lesions and characterized four as gray-zone lesions according to the rating system. Sensitivity of finding the tumors with M+US was 79.0%, with a PPV for malignant tumors of 84.4%. One breast in which MRM found a malignant tumor had not initially been examined with US. Sensitivity with MRM was 91.6%, with a positive predictive value of malignant tumors of 97.7%. MRM on mid-field seems to improve the detection of cancers when used as a supplement to M+US in women with primary breast cancer. We believe that the results are fair compared to MRM on high-field, although further research and refinement are needed.

Classification of Signal-Time Curves Obtained by Dynamic Magnetic Resonance Mammography

This study compares the performance of quantitative methods for the characterization of signal-time curves acquired by dynamic contrast-enhanced magnetic resonance mammography from 253 females. Signal-time curves obtained from 105 parenchyma, 162 malignant, and 91 benign tissue regions were examined (243 lesions were histopathologically validated). A neural network, a nearest-neighbor, and a threshold classifier were applied to either the entire signal-time curve or pharmacokinetic and descriptive parameters calculated from the curves to differentiate between 2 (malignant or benign) or 3 tissue classes (malignant, benign, or parenchyma). The classifiers were tuned and evaluated according to their performance on 2 distinct subsets of the curves. The accuracy determined for the neural network and the nearest-neighbor classifiers was nearly identical (approximately 80% in case of 3 tissue classes, and approximately 76% in case of the 2 classes). In contrast, the accuracy of the threshold classifier applied to the discrimination of 3 classes was low (65%). Quantitative classifiers can support the radiologist in the diagnosis of breast lesions.

Evaluation of tumor angiogenesis with contrast-enhanced dynamic magnetic resonance mammography.

The goal of this research was to correlate dynamic magnetic resonance (MR) mammographic contrast enhancement and microvessel densities in breast masses. Forty-six female patients with breast masses detected by mammography and/or ultrasonography were included in the study. MR contrast enhancements of the lesions were investigated dynamically using axial three-dimensional fast low-angle shot sequences. After excisional biopsy or mastectomy, immunohistochemical staining with factor VIII-RA was performed, followed by microvessel density measurements. Contrast enhancement patterns in dynamic MR mammography were compared with microvessel density measurements using Student's t-test, Pearson's moment correlation coefficients, and one-way analysis of variance (ANOVA). Malignant lesions exhibited three different enhancement patterns: 1) a peak enhancement within 120 seconds (early phase), followed by a decrease in the delayed phase (25 cases); 2) an increase in the early phase, followed by a plateau in the delayed phase (9 cases); and 3) an increase throughout the examination without any peak (5 cases). In benign lesions, signal intensity did not exhibited a peak in five cases, whereas in two cases enhancement was increased in the early phase and made a plateau in the delayed phase. A significant correlation was found between microvessel density and the percentage of maximal signal increase following paramagnetic contrast administration (r=0.322, p<0.05). Dynamic enhancement patterns and rates of maximal signal increase predict microvessel density in breast malignancies and may possibly be used as prognostic indicators.

False-negative findings of malignant breast lesions on preoperative magnetic resonance mammography

The aim of this study was to evaluate causes and percentages of false negative diagnoses of malignant breast lesions on preoperative dynamic magnetic resonance mammography (MRM).MRM was performed in 223 patients with 234 histopathologically proven malignant breast lesions (193 invasive carcinoma, 41 CIS) which were analyzed prospectively by routine analysis prior to surgery and re-analyzed by specialists, retrospectively. False negative findings were re-evaluated with respect to contrast enhancement, size and shape of lesions, reading errors, and technical problems. Preoperative analysis missed 27 of 234 malignant breast lesions (sensitivity 88.5%) including 15 of 193 invasive cancers (sensitivity 92%) and 12 of 41 CIS (sensitivity 71%). Five of 193 invasive cancers (four invasive lobular, one invasive tubular carcinoma) and five of 41 CIS lesions were missed due to delayed or no contrast enhancement. The remaining 17 false negative diagnoses were due to reading errors (n=8), previous core biopsies (n=3), metal induced artefacts (n=3), localization outside the field of view (n=1), incorrect injection (n=1) or movement artefacts (n=1).Using dynamic MR mammography, there were 4.3% slow contrast enhancing malignant breast lesions and a maximum sensitivity of 95.7% for detection of all malignant breast lesions (97.4% for invasive breast cancer, 87.8% for carcinoma in situ) can be achieved in a preselected preoperative population.

MRI of Breast Lesions

AbstractIn Magnetic Resonance Mammography (MRM) high spatial as well as temporal resolution is of utmost importance for differentiating between malignant and benign lesions. Therefore, a so‐called dynamic technique (i.e., the repetitive imaging of the same slices before and in short time intervals after the injection of contrast medium) is essential to detect the differences in initial enhancements between malignant and benign lesions which are reflected by the tumorangiogenetic vascular network of malignant lesions. This unit presents a basic protocol and several alternate protocols for dynamic MRM.

Granular cell tumor of the breast: A case report describing dynamic MR mammography

A case of granular cell tumor of the breast in a 36-year-old woman is reported. The patient presented with a hard mass,1.5 cm in diameter in the upper-outer quadrant of the left breast. Physical examination and ultrasonography suggested the presence of breast carcinoma. An aspiration biopsy cytology(ABC)specimen wasevaluated as class II, and dynamic magnetic resonance(MR)mammography indicated a benign tumor. Granular cell tumor was finally diagnosed on examination of an excisional biopsy specimen. Granular cell tumor of the breast can mimic breast carcinoma on physical examination, mammography, ultrasonography, and even gross inspection. Dynamic MR mammography has the potential distinguish this condition from carcinoma. Awareness of this disease and prudent use of diagnostic procedures, including MR mammography, will help prevent misdiagnosis and unnecessary surgery.

Preoperative Diagnosis of Breast Diseases by Dynamic MR Mammography:Cut-off Point Establishment for Signal Intensity Ratio.

We have demonstrated that the dynamic study for breast lesions by magnetic resonance imaging(MRI)can differentiate benign from malignant lesions objectively.The cases were 57 histopathologically appraised breast lesions, including 20 cases of breast cancer, 28 cases of mastopathy, 8 cases of fibroadenoma and 1 caseof intraductal papillomatosis. We plotted time-signal intensity ratio curves and then determined 95% confidence intervals, plotting the signal intensity ratio for both breast cancer and mastopathy every 30 seconds during dynamic magnetic resonance mammography(MRM)after gadolinium-diethylenetriamine pentaacetic acid(Gd-DTPA)administration, and further established cut-off points to differentiate between them. We then tried of estimate objectively the benign-malignant differentiation to breast lesions by confirming their signal intensity ratio to be more or less than the cut-off points. We advocate this procedure, and call it the " dynamic ratio method. " As a result, we found highly significant differences between breast cancer and mastopathy at 30 and 60 seconds after Gd-DTPA administration(P < 0.0001). We also confirmed that the cut-off point for the dynamic ratio method was equivalent to 1.4 and 1.8 times the precontrast signal intensity value at30 and 60 seconds after administration of Gd-DTPA respectively. By performing this dynamic ratio method preoperatively we can assess objectively not only the malignancy of breast lesions, but also neighboring infiltration, extending intraductal component, and lymph node metastasis. Furthermore, the dynamic ratio method provides detailed information for selecting the appropriate region for breast conserving surgery preoperatively, and can be expected to reduce unnecessary biopsies of benign cases. The dynamic ratio method had a sensitivity of 95.0%, a specificity of 81.1% and a positive predictive value of 73.1%. Also, for detectinginvasive ductal carcinoma, the sensitivity of the dynamic ratio method was 100.0%.

Surgical Research Society Abstracts

BJS (British Journal of Surgery)Volume 84, Issue 11 p. 1572-1624 Surgical Research Society Abstracts First published: 06 December 2005 https://doi.org/10.1111/j.1365-2168.1997.00117.xCitations: 1AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract The following abstracts were presented at the 86th meeting of the Surgical Research Society. The meeting was organized by the Department of Surgery, University of Nottingham, and held on 9-11 July 1997 in the University of Nottingham. One hundred and fifty-nine papers were presented during the scientific sessions. The Patey Prize was awarded to Mr P. J. Drew for his paper entitled ‘Clinical application of dynamic magnetic resonance mammography – evaluation of 622 scans’. Citing Literature Volume84, Issue11November 1997Pages 1572-1624 RelatedInformation

Dynamic magnetic resonance mammography of both breasts following local excision and radiotherapy for breast carcinoma : Murray AD, Redpath TW, Needham G, et al. (Department of Radiology, Aberdeen Royal Infirmary, Forestrhill, Aberdeen AB9 2ZB, UK). Brit J Radiol 1996;69:594–600

Dynamic magnetic resonance mammography of both breasts following local excision and radiotherapy for breast carcinoma : Murray AD, Redpath TW, Needham G, et al. (Department of Radiology, Aberdeen Royal Infirmary, Forestrhill, Aberdeen AB9 2ZB, UK). Brit J Radiol 1996;69:594–600