Enhancing the Kaiser score for lesion characterization in unenhanced breast MRI.

PURPOSE: To adapt the methodology of the Kaiser score, a clinical decision rule for lesion characterization in breast MRI, for unenhanced protocols. METHOD: In this retrospective IRB-approved cross-sectional study, we included 93 consecutive patients who underwent breast MRI between 2021 and 2023 for further work-up of BI-RADS 0, 3-5 in conventional imaging or for staging purposes (BI-RADS 6). All patients underwent biopsy for histologic verification or were followed for a minimum of 12 months. MRI scans were conducted using 1.5 T or 3 T scanners using dedicated breast coils and a protocol in line with international recommendations including DWI and ADC. Lesion characterization relied solely on T2w and DWI/ADC-derived features (such as lesion type, margins, shape, internal signal, surrounding tissue findings, ADC value). Statistical analysis was done using decision tree analysis aiming to distinguish benign (histology/follow-up) from malignant outcomes. RESULTS: We analyzed a total of 161 lesions (81 of them non-mass) with a malignancy rate of 40%. Lesion margins (spiculated, irregular, or circumscribed) were identified as the most important criterion within the decision tree, followed by the ADC value as second most important criterion. The resulting score demonstrated a strong diagnostic performance with an AUC of 0.840, providing both rule-in and rule-out criteria. In an independent test set of 65 lesions the diagnostic performance was verified by two readers (AUC 0.77 and 0.87, kappa: 0.62). CONCLUSIONS: We developed a clinical decision rule for unenhanced breast MRI including lesion margins and ADC value as the most important criteria, achieving high diagnostic accuracy.

Contrast-enhanced breast imaging: Current status and future challenges.

BACKGROUND: Contrast-enhanced breast MRI and recently also contrast-enhanced mammography (CEM) are available for breast imaging. The aim of the current overview is to explore existing evidence and ongoing challenges of contrast-enhanced breast imaging. METHODS: This narrative provides an introduction to the contrast-enhanced breast imaging modalities breast MRI and CEM. Underlying principle, techniques and BI-RADS reporting of both techniques are described and compared, and the following indications and ongoing challenges are discussed: problem-solving, high-risk screening, supplemental screening in women with extremely dense breast tissue, breast implants, neoadjuvant systemic therapy (NST) response monitoring, MRI-guided and CEM- guided biopsy. RESULTS: Technique and reporting for breast MRI are standardised, for the newer CEM standardisation is in progress. Similarly, compared to other modalities, breast MRI is well established as superior for problem-solving, screening women at high risk, screening women with extremely dense breast tissue or with implants; and for monitoring response to NST. Furthermore, MRI-guided biopsy is a reliable technique with low long-term false negative rates. For CEM, data is as yet either absent or limited, but existing results in these settings are promising. CONCLUSION: Contrast-enhanced breast imaging achieves highest diagnostic performance and should be considered essential. Of the two contrast-enhanced modalities, evidence of breast MRI superiority is ample, and preliminary results on CEM are promising, yet CEM warrants further study.

Using the Kaiser Score as a clinical decision rule for breast lesion classification: Does computer-assisted curve type analysis improve diagnosis?

PURPOSE: We aimed to investigate the effect of using visual or automatic enhancement curve type assessment on the diagnostic performance of the Kaiser Score (KS), a clinical decision rule for breast MRI. METHOD: This IRB-approved retrospective study analyzed consecutive conventional BI-RADS 0, 4 or 5 patients who underwent biopsy after 1.5T breast MRI according to EUSOBI recommendations between 2013 and 2015. The KS includes five criteria (spiculations; signal intensity (SI)-time curve type; margins of the lesion; internal enhancement; and presence of edema) resulting in scores from 1 (=lowest) to 11 (=highest risk of breast cancer). Enhancement curve types (Persistent, Plateau or Wash-out) were assessed by two radiologists independently visually and using a pixel-wise color-coded computed parametric map of curve types. KS diagnostic performance differences between readings were compared by ROC analysis. RESULTS: In total 220 lesions (147 benign, 73 malignant) including mass (n = 148) and non-mass lesions (n = 72) were analyzed. KS reading performance in distinguishing benign from malignant lesions did not differ between visual analysis and parametric map (P = 0.119; visual: AUC 0.875, sensitivity 95 %, specificity 63 %; and map: AUC 0.901, sensitivity 97 %, specificity 65 %). Additionally, analyzing mass and non-mass lesions separately, showed no difference between parametric map based and visual curve type-based KS analysis as well (P = 0.130 and P = 0.787). CONCLUSIONS: The performance of the Kaiser Score is largely independent of the curve type assessment methodology, confirming its robustness as a clinical decision rule for breast MRI in any type of breast lesion in clinical routine.

Estimation of the biomechanical mammographic deformation of the breast using machine learning models.

BACKGROUND: A typical problem in the registration of MRI and X-ray mammography is the nonlinear deformation applied to the breast during mammography. We have developed a method for virtual deformation of the breast using a biomechanical model automatically constructed from MRI. The virtual deformation is applied in two steps: unloaded state estimation and compression simulation. The finite element method is used to solve the deformation process. However, the extensive computational cost prevents its usage in clinical routine. METHODS: We propose three machine learning models to overcome this problem: an extremely randomized tree (first model), extreme gradient boosting (second model), and deep learning-based bidirectional long short-term memory with an attention layer (third model) to predict the deformation of a biomechanical model. We evaluated our methods with 516 breasts with realistic compression ratios up to 76%. FINDINGS: We first applied one-fold validation, in which the second and third models performed better than the first model. We then applied ten-fold validation. For the unloaded state estimation, the median RMSE for the second and third models is 0.8 mm and 1.2 mm, respectively. For the compression, the median RMSE is 3.4 mm for both models. We evaluated correlations between model accuracy and characteristics of the clinical datasets such as compression ratio, breast volume, and tissue types. INTERPRETATION: Using the proposed models, we achieved accurate results comparable to the finite element model, with a speedup of factor 240 using the extreme gradient boosting model. These proposed models can replace the finite element model simulation, enabling clinically relevant real-time application.

How much can abbreviated protocols for breast MRI increase patient throughput? a multi-centric evaluation.

PURPOSE: To assess the impact of abbreviated breast MRI protocols on patient throughput considering non-scanning time and differences between in- and out-of-hospital settings. MATERIALS & METHODS: A total of 143 breast MRI exams from four study sites (hospital, three radiology centers) were included in this retrospective study. Total exam time (TET), Table Time (TT), Scan Time (ST), Table Switch Time (TST) and Planning Time (PT) were determined from consecutive breast MRI examinations. Possible number of scans and exams per hour were calculated. Four scan protocols were compared: full diagnostic protocol (n = 34, hospital), split dynamic protocol (n = 109, all sites) and two abbreviated protocols (n = 109, calculated, all sites). Data were described as median and interquartile range (IQR) and compared by Mann-Whitney-U-Test. RESULTS: Non-scanning time increased from 50% to 74% of the TET with a TST of 46% and a PT of 28% in the shortest abbreviated protocol. Number of possible scans per hour increased from 4.7 to 18.8 while number of possible exams per hour only increased from 2.3 to 5.1. Absolute TST (4.7 vs. 5.7 min, p = 0.46) and TET (18 min each, p = 0.35) did not differ significantly between in- and out-of-hospital exams. Absolute (4.4 vs. 2.8 min, p < 0.001) and relative (23 vs. 13%, p < 0.001) PT and TT (13.3 vs. 11.5 min, p = 0.004) was longer and relative TST (27% vs. 34%, p = 0.047) was shorter in hospital. CONCLUSION: TST and PT significantly contribute to TET and challenge the effectiveness of abbreviated protocols for increasing patient throughput. These findings show only low setting-dependent differences.

Impact of PI-QUAL on PI-RADS and cancer yield in an MRI-TRUS fusion biopsy population.

PURPOSE: To test the inter-reader agreement of the Prostate Imaging Quality (PI-QUAL) score for multiparametric prostate MRI and its impact on diagnostic performance in an MRI-ultrasound fusion biopsy population. PATIENTS AND METHODS: Pre-biopsy multiparametric (T2-weighted, DWI, and DCE) prostate MRIs (mpMRI) of 50 patients undergoing transrectal ultrasound-guided MRI-fusion (MRI-TRUS) biopsy were included. Two radiologists independently assigned a PI-QUAL score to each patient and assessed the diagnostic quality of individual sequences. PI-RADS categories were assigned to six regions per prostate (left and right: base/mid-glandular/apex). Inter-reader agreement was calculated using Cohen's kappa and diagnostic performance was compared by the area under the receiver operating characteristics curve (AUC). RESULTS: In 274 diagnostic areas, the malignancy rate was 62.7% (22.5% clinically significant prostate cancer, ISUP ≥ 2). Inter-reader agreement for the diagnostic quality was poor for T2w (kappa 0.19), fair for DWI and DCE (kappa 0.23 and 0.29) and moderate for PI-QUAL (kappa 0.51). For PI-RADS category assignments, inter-reader agreement was very good (kappa 0.86). Overall diagnostic performance did not differ between studies with a PI-QUAL score > 3 compared to a score ≤ 3 (p = 0.552; AUC 0.805 and 0.839). However, the prevalence of prostate cancer was significantly lower when the PI-QUAL score was ≤ 3 (16.7% vs. 30.2%, p = 0.008). CONCLUSION: PI-QUAL has only a limited impact on PI-RADS diagnostic performance in patients scheduled for MRI-TRUS fusion biopsy. However, the lower cancer prevalence in the lower PI-QUAL categories points out a risk of false-positive referrals and unnecessary biopsies if prostate imaging quality is low.

AI-enhanced simultaneous multiparametric 18F-FDG PET/MRI for accurate breast cancer diagnosis.

PURPOSE: To assess whether a radiomics and machine learning (ML) model combining quantitative parameters and radiomics features extracted from simultaneous multiparametric 18F-FDG PET/MRI can discriminate between benign and malignant breast lesions. METHODS: A population of 102 patients with 120 breast lesions (101 malignant and 19 benign) detected on ultrasound and/or mammography was prospectively enrolled. All patients underwent hybrid 18F-FDG PET/MRI for diagnostic purposes. Quantitative parameters were extracted from DCE (MTT, VD, PF), DW (mean ADC of breast lesions and contralateral breast parenchyma), PET (SUVmax, SUVmean, and SUVminimum of breast lesions, as well as SUVmean of the contralateral breast parenchyma), and T2-weighted images. Radiomics features were extracted from DCE, T2-weighted, ADC, and PET images. Different diagnostic models were developed using a fine Gaussian support vector machine algorithm which explored different combinations of quantitative parameters and radiomics features to obtain the highest accuracy in discriminating between benign and malignant breast lesions using fivefold cross-validation. The performance of the best radiomics and ML model was compared with that of expert reader review using McNemar's test. RESULTS: Eight radiomics models were developed. The integrated model combining MTT and ADC with radiomics features extracted from PET and ADC images obtained the highest accuracy for breast cancer diagnosis (AUC 0.983), although its accuracy was not significantly higher than that of expert reader review (AUC 0.868) (p = 0.508). CONCLUSION: A radiomics and ML model combining quantitative parameters and radiomics features extracted from simultaneous multiparametric 18F-FDG PET/MRI images can accurately discriminate between benign and malignant breast lesions.

Multiparametric ultrasound examination for response assessment in breast cancer patients undergoing neoadjuvant therapy.

To investigate the performance of multiparametric ultrasound for the evaluation of treatment response in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). The IRB approved this prospective study. Breast cancer patients who were scheduled to undergo NAC were invited to participate in this study. Changes in tumour echogenicity, stiffness, maximum diameter, vascularity and integrated backscatter coefficient (IBC) were assessed prior to treatment and 7 days after four consecutive NAC cycles. Residual malignant cell (RMC) measurement at surgery was considered as standard of reference. RMC < 30% was considered a good response and > 70% a poor response. The correlation coefficients of these parameters were compared with RMC from post-operative histology. Linear Discriminant Analysis (LDA), cross-validation and Receiver Operating Characteristic curve (ROC) analysis were performed. Thirty patients (mean age 56.4 year) with 42 lesions were included. There was a significant correlation between RMC and echogenicity and tumour diameter after the 3rd course of NAC and average stiffness after the 2nd course. The correlation coefficient for IBC and echogenicity calculated after the first four doses of NAC were 0.27, 0.35, 0.41 and 0.30, respectively. Multivariate analysis of the echogenicity and stiffness after the third NAC revealed a sensitivity of 82%, specificity of 90%, PPV = 75%, NPV = 93%, accuracy = 88% and AUC of 0.88 for non-responding tumours (RMC > 70%). High tumour stiffness and persistent hypoechogenicity after the third NAC course allowed to accurately predict a group of non-responding tumours. A correlation between echogenicity and IBC was demonstrated as well.

Combined texture analysis and machine learning in suspicious calcifications detected by mammography: Potential to avoid unnecessary stereotactical biopsies.

OBJECTIVES: To investigate whether combined texture analysis and machine learning can distinguish malignant from benign suspicious mammographic calcifications, to find an exploratory rule-out criterion to potentially avoid unnecessary benign biopsies. METHODS: Magnification views of 235 patients which underwent vacuum-assisted biopsy of suspicious calcifications (BI-RADS 4) during a two-year period were retrospectively analyzed using the texture analysis tool MaZda (Version 4.6). Microcalcifications were manually segmented and analyzed by two readers, resulting in 249 image features from gray-value histogram, gray-level co-occurrence and run-length matrices. After feature reduction with principal component analysis (PCA), a multilayer perceptron (MLP) artificial neural network was trained using histological results as the reference standard. For training and testing of this model, the dataset was split into 70 % and 30 %. ROC analysis was used to calculate diagnostic performance indices. RESULTS: 226 patients (150 benign, 76 malignant) were included in the final analysis due to missing data in 9 cases. Feature selection yielded nine image features for MLP training. Area under the ROC-curve in the testing dataset (n = 54) was 0.82 (95 %-CI: 0.70-0.94) and 0.832 (95 %-CI 0.72-0.94) for both readers, respectively. A high sensitivity threshold criterion was identified in the training dataset and successfully applied to the testing dataset, demonstrating the potential to avoid 37.1-45.7 % of unnecessary biopsies at the cost of one false-negative for each reader. CONCLUSION: Combined texture analysis and machine learning could be used for risk stratification in suspicious mammographic calcifications. At low costs in terms of false-negatives, unnecessary biopsies could be avoided.

Impact of the Kaiser score on clinical decision-making in BI-RADS 4 mammographic calcifications examined with breast MRI.

OBJECTIVES: To investigate whether the application of the Kaiser score for breast magnetic resonance imaging (MRI) might downgrade breast lesions that present as mammographic calcifications and avoid unnecessary breast biopsies METHODS: This IRB-approved, retrospective, cross-sectional, single-center study included 167 consecutive patients with suspicious mammographic calcifications and histopathologically verified results. These patients underwent a pre-interventional breast MRI exam for further diagnostic assessment before vacuum-assisted stereotactic-guided biopsy (95 malignant and 72 benign lesions). Two breast radiologists with different levels of experience independently read all examinations using the Kaiser score, a machine learning-derived clinical decision-making tool that provides probabilities of malignancy by a formalized combination of diagnostic criteria. Diagnostic performance was assessed by receiver operating characteristics (ROC) analysis and inter-reader agreement by the calculation of Cohen's kappa coefficients. RESULTS: Application of the Kaiser score revealed a large area under the ROC curve (0.859-0.889). Rule-out criteria, with high sensitivity, were applied to mass and non-mass lesions alike. The rate of potentially avoidable breast biopsies ranged between 58.3 and 65.3%, with the lowest rate observed with the least experienced reader. CONCLUSIONS: Applying the Kaiser score to breast MRI allows stratifying the risk of breast cancer in lesions that present as suspicious calcifications on mammography and may thus avoid unnecessary breast biopsies. KEY POINTS: • The Kaiser score is a helpful clinical decision tool for distinguishing malignant from benign breast lesions that present as calcifications on mammography. • Application of the Kaiser score may obviate 58.3-65.3% of unnecessary stereotactic biopsies of suspicious calcifications. • High Kaiser scores predict breast cancer with high specificity, aiding clinical decision-making with regard to re-biopsy in case of negative results.

Can the addition of clinical information improve the accuracy of PI-RADS version 2 for the diagnosis of clinically significant prostate cancer in positive MRI?

AIM: To report prostate cancer (PCa) prevalence in Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) categories and investigate the potential to avoid unnecessary, magnetic resonance imaging (MRI)-guided in-bore biopsies by adding clinical and biochemical patient characteristics. MATERIALS AND METHODS: The present institutional review board-approved, prospective study on 137 consecutive men with 178 suspicious lesions on 3 T MRI was performed. Routine data collected for each patient included patient characteristics (age, prostate volume), clinical background information (prostate-specific antigen [PSA] levels, PSA density), and PI-RADS v2 scores assigned in a double-reading approach. RESULTS: Histopathological evaluation revealed a total of 93/178 PCa (52.2%). The mean age was 66.3 years and PSA density was 0.24 ng/ml2 (range, 0.04-0.89 ng/ml). Clinically significant PCa (csPCa, Gleason score >6) was confirmed in 50/93 (53.8%) lesions and was significantly associated with higher PI-RADS v2 scores (p=0.0044). On logistic regression analyses, age, PSA density, and PI-RADS v2 scores contributed independently to the diagnosis of csPCa (p=7.9×10-7, p=0.097, and p=0.024, respectively). The resulting area under the receiver operating characteristic curve (AUC) to predict csPCa was 0.76 for PI-RADS v2, 0.59 for age, and 0.67 for PSA density. The combined regression model yielded an AUC of 0.84 for the diagnosis of csPCa and was significantly superior to each single parameter (p≤0.0009, respectively). Unnecessary biopsies could have been avoided in 50% (64/128) while only 4% (2/50) of csPCa lesions would have been missed. CONCLUSIONS: Adding age and PSA density to PI-RADS v2 scores improves the diagnostic accuracy for csPCa. A combination of these variables with PI-RADS v2 can help to avoid unnecessary in-bore biopsies while still detecting the majority of csPCa.

[Contrast agent-free breast MRI : Advantages and potential disadvantages]. / Kontrastmittelfreie Mamma-MRT : Vorteile und potenzielle Nachteile.

BACKGROUND: Contrast-enhanced breast magnetic resonance imaging (MRI) is the most sensitive method for detection of breast cancer. The further spread of breast MRI is limited by the complicated examination procedure and the need for intravenously administered contrast media. OBJECTIVES: Can diffusion-weighted imaging (DWI) replace contrast-enhanced sequences to achieve an unenhanced breast MRI examination? MATERIALS AND METHODS: Narrative review and meta-analytic assessment of previously published studies. RESULTS: DWI can visualize breast lesions and distinguish benign from malignant findings. It is thus a valid alternative to contrast-enhanced sequences. As an additional technique, the use of DWI can reduce the numbers of unnecessary breast biopsies. The lack of robustness leading to variable sensitivity that is currently lower than that of contrast-enhanced breast MRI is a disadvantage of DWI. CONCLUSIONS: Presently, DWI can be recommended as an integral part of clinical breast MRI protocols. The application as a stand-alone technique within unenhanced protocols is still under evaluation.

Digital breast tomosynthesis as an adjunct to digital mammography for detecting and characterising invasive lobular cancers: a multi-reader study.

AIM: To examine the interpretive performance of digital breast tomosynthesis (DBT) as an adjunct to digital mammography (DM) compared to DM alone in a series of invasive lobular carcinomas (ILCs) and to assess whether DBT can be used to characterise ILC. MATERIALS AND METHODS: A retrospective, multi-reader study was conducted of 83 mammographic examinations of women with 107 newly diagnosed ILCs ascertained at histology. Consenting women underwent both DM and DBT acquisitions. Twelve radiologists, with varying mammography experience, interpreted DM images alone, reporting lesion location, mammographic features, and malignancy probability using the Breast Imaging-Reporting and Data System (BI-RADS) categories 1-5; they then reviewed DBT images in addition to DM, and reported the same parameters. Statistical analyses compared sensitivity, false-positive rates (FPR), and interpretive performance using the receiver operating characteristics (ROC) curve and the area under the curve (AUC), for reading with DM versus DM plus DBT. RESULTS: Multi-reader pooled ROC analysis for DM plus DBT yielded AUC=0.89 (95% confidence interval [CI]: 0.88-0.91), which was significantly higher (p<0.0001) than DM alone with AUC=0.84 (95% CI: 0.82-0.86). DBT plus DM significantly increased pooled sensitivity (85%) compared to DM alone (70%; p<0.0001). FPR did not vary significantly with the addition of DBT to DM. Interpreting with DBT (compared to DM alone) increased the correct identification of ILCs depicted as architectural distortions (84% versus 65%, respectively) or as masses (89% versus 70%), increasing interpretive performance for both experienced and less-experienced readers; larger gains in AUC were shown for less-experienced radiologists. Multifocal and/or multicentric and bilateral disease was more frequently identified on DM with DBT. CONCLUSION: Adding DBT to DM significantly improved the accuracy of mammographic interpretation for ILCs and contributed to characterising disease extent.

Inter- and intra-observer agreement of BI-RADS-based subjective visual estimation of amount of fibroglandular breast tissue with magnetic resonance imaging: comparison to automated quantitative assessment.

PURPOSE: To evaluate the inter-/intra-observer agreement of BI-RADS-based subjective visual estimation of the amount of fibroglandular tissue (FGT) with magnetic resonance imaging (MRI), and to investigate whether FGT assessment benefits from an automated, observer-independent, quantitative MRI measurement by comparing both approaches. MATERIALS AND METHODS: Eighty women with no imaging abnormalities (BI-RADS 1 and 2) were included in this institutional review board (IRB)-approved prospective study. All women underwent un-enhanced breast MRI. Four radiologists independently assessed FGT with MRI by subjective visual estimation according to BI-RADS. Automated observer-independent quantitative measurement of FGT with MRI was performed using a previously described measurement system. Inter-/intra-observer agreements of qualitative and quantitative FGT measurements were assessed using Cohen's kappa (k). RESULTS: Inexperienced readers achieved moderate inter-/intra-observer agreement and experienced readers a substantial inter- and perfect intra-observer agreement for subjective visual estimation of FGT. Practice and experience reduced observer-dependency. Automated observer-independent quantitative measurement of FGT was successfully performed and revealed only fair to moderate agreement (k = 0.209-0.497) with subjective visual estimations of FGT. CONCLUSION: Subjective visual estimation of FGT with MRI shows moderate intra-/inter-observer agreement, which can be improved by practice and experience. Automated observer-independent quantitative measurements of FGT are necessary to allow a standardized risk evaluation. KEY POINTS: • Subjective FGT estimation with MRI shows moderate intra-/inter-observer agreement in inexperienced readers. • Inter-observer agreement can be improved by practice and experience. • Automated observer-independent quantitative measurements can provide reliable and standardized assessment of FGT with MRI.

Fat saturation in dynamic breast MRI at 3 Tesla: is the Dixon technique superior to spectral fat saturation? A visual grading characteristics study.

PURPOSE: To intra-individually compare the diagnostic image quality of Dixon and spectral fat suppression at 3 T. METHODS: Fifty consecutive patients (mean age 55.1 years) undergoing 3 T breast MRI were recruited for this prospective study. The image protocol included pre-contrast and delayed post-contrast spectral and Dixon fat-suppressed T1w series. Two independent blinded readers compared spectral and Dixon fat-suppressed series by evaluating six ordinal (1 worst to 5 best) image quality criteria (image quality, delineation of anatomical structures, fat suppression in the breast and axilla, lesion delineation and internal enhancement). Breast density and size were assessed. Data analysis included Spearman's rank correlation coefficient and visual grading characteristics (VGC) analysis. RESULTS: Four examinations were excluded; 48 examinations in 46 patients were evaluated. In VGC analysis, the Dixon technique was superior regarding image quality criteria analysed (P < 0.01). Smaller breast size and lower breast density were significantly (P < 0.01) correlated with impaired spectral fat suppression quality. No such correlation was identified for the Dixon technique, which showed reconstruction-based water-fat mixups leading to insufficient image quality in 20.8%. CONCLUSIONS: The Dixon technique outperformed spectral fat suppression in all evaluated criteria (P < 0.01). Non-diagnostic examinations can be avoided by fat and water image reconstruction. The superior image quality of the Dixon technique can improve breast MRI interpretation. KEY POINTS: Optimal fat suppression quality is necessary for optimal image interpretation. Superior fat suppression quality is achieved using the Dixon technique. Lesion margin and internal enhancement evaluation improves using the Dixon technique. Superior image quality of the Dixon technique improves breast MRI interpretation.

Assessment with potential mapping of the cardiac protective effect of a drug. Example of trimetazidine.

SATAPEC is a computerized system built in the Laboratory for recording over 256 multiplexed channels and for automatic processing of cardiac electrical potentials. The results are printed out in the form of maps (either in black and white or in color) showing potential distributions, depolarization, repolarization, duration of activation, or various other analog-digital data. The cardioprotective ability of a drug may be assessed with SATAPEC. As an example, the effect of trimetazidine (TMZ) is examined using 2 groups of 12 rabbits (one group serving as a control and the second group pretreated with TMZ). An elastomer mesh with 240 regularly spaced chlorided silver wire electrode is placed around the ventricles following thoracotomy. A ligature is made starting from the anterior interventricular artery (AIV). Recordings are taken from the 240 unipolar epicardial electrograms (reference potential taken at Wilson terminal) 1 min before ligation and then every min for 8 min following ligation. Once the electrograms are plotted and any aberrant tracings eliminated, ST variation is calculated automatically. Files containing ST variations at different instants are stored in the computer memory and the mean sigma ST/240 curves of the two groups of rabbits are plotted versus time. Mean electric potential maps, obtained by aligning all of the individual maps, are then printed. With these maps the location and extent of the epicardial injured area can be visualized. Pretreatment with TMZ (2.5 mg/kg) has shown a beneficial effect on ischemia injury.

Evolution of free radical formation during low-flow ischemia and reperfusion in isolated rat heart.

Free radicals have been implicated in several aspects of cellular injury, both during ischemia and reperfusion of the myocardium. In this study, formation of free radicals in the isolated rat heart was measured a) directly using electron paramagnetic resonance (EPR) spectroscopy and b) indirectly using the generation of thiobarbituric acid reactants as an index of lipid peroxidation. EPR spectra of frozen heart powder recorded at 100 degrees K show several lines and consist of different components separated by temperature studies: signal C disappears after warming the sample 1 minute at 190 degrees K and is suggestive of a triplet signal g = 2.001, aN = 25 Gauss; signal B g parallel = 2.034, g perpendicular = 2.007, disappears after 1 min at 240 degrees K, and is similar to those previously reported for oxygen alkylperoxyl free radical; the remaining signal, signal A with g = 2.004 is identical to that of a carbon-centered ubiquinone free radical. The total free radical concentration in isolated rat heart perfused at a constant flow rate of 12 ml/min was increased by 44% compared with control (p less than 0.05) after 10 minutes of normothermic global ischemia with a 10% residual flow, and by only 31% compared with control after 20 seconds of reflow with oxygenated perfusate (p less than 0.05). Compared with the reperfused group, trimetazidine 10(-5) M administered 15 minutes before the ischemic period decreased the free radical concentration (-20%). However, this free radical generation in heart was not associated with a concomitant increase of lipid peroxides.