[Dynamic 3D MR mammography using a rapid gradient-echo sequence]

High grade and non-high grade ductal carcinoma in situ on dynamic MR mammography: characteristic findings for signal increase and morphological pattern of enhancement

The objective of this review is to describe characteristic MR mammographic findings for signal increase and morphological patterns of enhancement in pure ductal carcinoma in situ (DCIS) and to differentiate between high grade and non-high grade lesions. The dynamic MR examination (1.5 T unit, contrast enhanced T(1) weighted two dimensional fast field echo, 96 ms repetition time, 5.0 ms echo time, 80 degrees flip angle) of 39 consecutive patients with pure DCIS was evaluated retrospectively. Categories were defined for signal increase (C1=normal, C2=slow, continuous, C3=strong initial and slow further increase, C4=strong initial increase followed by a plateau phenomenon, and C5=strong initial increase followed by a washout phenomenon) and morphological patterns (M0=no pattern observed, M1=linear or linear-branched, M2=segmental dotted or granular, M3=segmental homogeneous, and M4=focal spot-like). Time-intensity curves showing a C4 and C5 signal increase were considered suspicious for malignancy. All cases were correlated with histology. 62% of all tumours had a plateau or washout (C4, C5), 77% showed a strong initial signal increase (C3-C5). On evaluation of time-intensity curves alone MR mammography (MRM) findings were suspicious for malignancy in 62% of all DCIS cases. A segmental enhancement was found in 82% of all enhancing tumors and the M2 pattern in 73%. In a combined analysis of signal increase and morphology, 70% of non-high grade and 92% of high grade DCISs were correctly described as suspicious. The difference between non-high grade and high grade DCIS was not significant (p=0.148), while significant differences were found between G1 and G3 DCISs and between G1 and G2 DCISs (p<0.05). All G2 and G3 DCISs showed noticeable signal enhancement. The mean histological tumour size of non-high grade DCISs was smaller than that for high grade DCIS (p<0.05). The hallmark of DCIS on dynamic MRM was unilateral segmental enhancement, most commonly with a granular dotted morphology (M2). Hormone effects need to be considered as the main differential diagnosis. Signal enhancement kinetics similar to invasive carcinoma were seen in the majority of cases. A combined analysis of morphological pattern and signal enhancement considerably improved rate of detection. G2 and G3 DCISs were correctly diagnosed with a significantly higher rate of detection (92%) than G1 DCIS (53%) (p<0.05). Different average size of G1, G2 and G3 DCIS on pathology cannot be excluded as a reason for differences found. Normal MRM seems to exclude high grade DCIS.

Understanding why contrast enhancement in dynamic MRI is not reproducible: illustration with a simple phantom

The goal of this work was to verify in a phantom study the necessity of a calibration method for comparison in dynamic contrast-enhanced magnetic resonance imaging (MRI) examinations. A perspex phantom with a dilution series of Gd-DTPA was used to measure the dynamic signal enhancement of a sequence. With nine MRI scanners from Bruker (0.23, 0.5, and 2 Tesla), Philips [0.5 and 1.5 Tesla (ACS-NT and S15)], and Siemens (0.2, 1.0, and 1.5 Tesla) one 2D FLASH and two 3D FLASH experiments were performed under identical measurement conditions. Under different measurement conditions (2D and 3D FLASH, TR, TE, FA) different characteristics in signal enhancement exist on a scanner. The same measurement conditions at different scanners (same magnetic field strength) also result in different signal enhancement. Dynamic contrast enhanced MRI examinations from different measurement conditions or scanners cannot be compared. To solve this problem a calibration is needed.

MR dynamic enhancement of breast lesions: high temporal resolution during the first-minute versus eight-minute study

PURPOSE

To investigate the value of the early phase of MR enhancement of breast lesions.

METHOD

To study 63 breast lesions (size 5-45 mm in diameter) in 56 patients, whole-breast and lesion-targeted precontrast T1 -weighted gradient-echo 2D sequences were acquired. After intravenous injection of Gd-DTPA (0.1 mmol/Kg), four targeted scans, each every 15 seconds during the first minute (1-m), and seven whole-breast scans, each every minute up to 8 minutes (8-m), were performed. The subtraction technique was used, and percent enhancement curves were obtained. The final diagnosis was obtained by histology for 36 lesions, including 28 malignancies, and by fine-needle aspiration cytology and at least 1-year negative follow-up for the remaining 27 benign lesions.

RESULTS

Significant differences in enhancement between malignant and benign lesions were found using both techniques (p<0.0001). However the ratio between the median enhancement of malignant lesions and that of benign lesions was 6.7 (15 s), 4.8 (30 s), 4.6 (45 s), and 3.8 (60 s), descending from 4.3 to 2.5 from the second to the eighth minute. The overlap between the malignant and benign curves was 9% of the malignant range with the 1-m technique, and 50% with the 8-m technique. Three blinded observers obtained a 100% sensitivity with both techniques and a specificity of 94-97% with the 1-m technique and 83-89% with the 8-m technique.

CONCLUSION

The first minute of Gd-enhancement allows a more prominent differentiation between malignant and benign breast lesions than the following times.

Dynamic 3D-MR mammography: is there a benefit of sophisticated evaluation of enhancement curves for clinical routine?

The purpose of the study was to compare standard analysis with pharmacokinetic analysis of time-intensity curves in dynamic three-dimensional (3D) MR mammography (MRM) for their capability of differentiating benign from malignant disease. Dynamic MRM of the whole breast was performed at 1.0 T using an axial fast low-angle shot (FLASH) 3D sequence. For the standard evaluation, the enhancement of the first minute (E1) and the slope of enhancement from minute 2 to 10 (SE2-10) were calculated. For pharmacokinetic analysis, the amplitude of enhancement (A), distribution time (t21), and elimination time (tel) were computed. Sixty-two histologically verified lesions were evaluated. The standard evaluation methods yielded a highly significant difference between benign and malignant disease for E1 (P = .0008) and SE2-10 (P = .0001). The pharmacokinetic parameters gained similarly significant P values (A, P = .0014; t21, P = .0024; tel, P = .0001). Both standard and pharmacokinetic analysis concordantly discriminated between benign and malignant lesions in discriminant analysis. Compared with standard analysis, a pharmacokinetic analysis of time-intensity curves is not beneficial for routine clinical diagnosis.

Recent developments in breast imaging

A review of breast imaging has already appeared in 1982 in this journal. Consequently, the present article concentrates on a discussion of only those developments of a more recent nature. Although the emphasis is placed on the physical aspects of the different imaging methods concerned, the essential factors relating to the clinical background and the associated radiation risk are also outlined. The completeness of detail depends on the present clinical importance of the method under discussion. X-ray mammography, which is still the most important breast imaging technique and has proved to be an effective method for breast cancer screening, is therefore treated in greater detail. Since the early 1980s, ultrasound B-mode scanning has evolved to an indispensable adjunct to x-ray mammography. For Doppler sonography, diaphanography, contrast-enhanced MRI, CT and DSA, the visualization of a tumour depends essentially on the enhanced vascularity of the lesion. Whether this will prove to be a reliable indicator for malignancy remains to be shown in controlled clinical studies. Common to all imaging systems is the increasing use of digital methods for signal processing, which also offers the possibility of computer-aided diagnosis by texture analysis and pattern recognition.