MR Imaging—Detected Breast Lesions: Histopathologic Correlation of  Lesion Characteristics and Signal Intensity Data

Siegmann, K. C.; Müller-Schimpfle, Markus; Schick, Fritz; Remy, Christopher T.; Fersis, N.; Ruck, Peter; Gorriz, Corinna; Claussen, Claus D.

doi:10.2214/ajr.178.6.1781403

Cited by 59 publications

(33 citation statements)

References 31 publications

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“…A malignant tumour may well enhance with type I and type II shapes but heterogeneous nature of enhancement and variety of curve shapes in different anatomical areas is strongly suggestive of malignancy [8,16], reflecting a polymorphous cell population and tumour necrosis. Therefore a heterogeneous lesion must be ROI-averaged in order to gather information that is representative of the whole lesion.…”

Section: Discussionmentioning

confidence: 99%

“…The vascularisation of the malignant lesions resulting from neo-vessels, that are the basis of exponential tumour growth, is one of the major reasons that dynamic features of MRI have played a crucial role in breast cancer for a decade [7][8][9][10][11][12][13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

“…Kinetic curve analysis can be performed qualitatively (visual inspection of the curve shape), semi-quantitatively (by means of empirical parameters of signal intensity changes as gradient of the upslope of enhancement curves, maximum signal intensity and wash-out gradient) or quantitatively through pharmacokinetic modelling techniques [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

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Can semi-quantitative evaluation of uncertain (type II) time-intensity curves improve diagnosis in breast DCE-MRI?

Fusco¹,

Filice²,

Granata³

et al. 2013

JBiSE

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Objective/Background: Qualitative assessment of uncertain (type II) time-intensity curves (TICs) in breast DCE-MRI is problematic and operator dependent. The aim of this work is to evaluate if a semi-quantitative assessment of uncertain TICs could improve overall diagnostic performance. Methods: In this study 49 lesions from 44 patients were retrospectively analysed. Per each lesion one region-of-interest (ROI)-averaged TIC was qualitatively evaluated by two radiologists in consensus: all the ROIs resulted in type II (uncertain) TIC. The same TICs were semi-quantitatively re-classified on the basis of the difference between the signal intensities of the last-time-point and of the peak: this difference was classified according to two different cut-off ranges (±5% and ±3%). All patients were cytological or histological biopsy proven. Fisher test and McNemar test were performed to evaluate if results were statistically significant (p < 0.05). Results: Using ±5% cut-off 16 TICs were reclassified as type III and 12 as type I while 21 were reclassified again as type II. Using ±3% 22 TICs were reclassified as type III and 16 as type I while 11 were reclassified again as type II. The semi-quantitative classification was compared to the histologicalcytological results: the sensitivity, specificity, positive and negative predictive values obtained with ±3% were 77%, 91%, 91% and 78% respectively while using ±5% were 58%, 96%, 94% and 68% respectively. Using the ±5% cut-off 26/28 (93%) TICs were correctly reclassified while using the ±3% cut-off 34/38 (90%) TICs were correctly reclassified (p < 0.05). Conclusions: Semi-quantitative methods in kinetic curve assessment on DCE-MRI could improve classification of qualitatively uncertain TICs, leading to a more accurate classification of suspicious breast lesions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Can semi-quantitative evaluation of uncertain (type II) time-intensity curves improve diagnosis in breast DCE-MRI?

Fusco¹,

Filice²,

Granata³

et al. 2013

JBiSE

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“…The first to apply Gd -DTPA as a contrast agent in breast MRI was Heywang et al in 1985. Following that in 1989 Kaiser et al first reported dynamic breast MRI, as a modality designed to track rapid changes in signal intensity (7,14,24). Changes in the post-contrast signal intensity helped to distinguish lesions according to characteristic enhanced accumulation of contrast agent could then be related to higher tissue microvascularity (1,7,12,13,15,17,18).…”

Section: Dynamic Contrast Enhanced Mri (Dce Mri)mentioning

confidence: 99%

“…Whereas it is still not standardized the method for generating kinetic curves is accepted as both inter-and intraobserver variability (7,8,10,11,20,21). In general, though, DCE MRI has excellent sensitivity despite its variable specificity for breast cancer detection (10,14,15,22,24).…”

Section: Dynamic Contrast Enhanced Mri (Dce Mri)mentioning

confidence: 99%

Nuclear Magnetic Resonance as a Diagnostic Tool in Breast Cancer

Hnilicová¹,

Dobrota²

2012

Acta Medica Martiniana

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A b s t r a c tThe early detection and treatment of breast cancer is of direct benefit to patients. Magnetic resonance imaging (MRI) is a promising modality for detection, diagnosis, and staging of breast cancer. MRI enables two methods: the diffusion-weighted MRI (DW MRI) and the dynamic contrast enhanced MRI (DCE MRI). DW MRI reflects the diffusion of water molecules in the extracellular fluid space and allows the estimation of cellularity and tissue structure. The value of the diffusion of water in tissue is called the apparent diffusion coefficient (ADC). ADC values in malignant lesions are smaller than in benign tissue. DCE MRI yields appropriate pharmacokinetic data of physiological parameters that relate to tissue perfusion, microvascular vessel wall permeability and extracellular volume fraction. Gadolinium based contrast agent is usually used in breast DCE MRI diagnostics. Changes in the post-contrast signal intensity help to distinguish lesions according to characteristically enhanced accumulation of contrast agent. Malignant lesions are characterized by a faster and stronger signal enhancement than benign lesions which relate to their neoangiogenesis. Over the last few years, there has been appreciable interest in the use of magnetic resonance spectroscopy (MRS) for the non-invasive analysis of breast tisue metabolites. One of the spectroscopic hallmarks of the neoplastic process appears to be the presence of total choline signal in the in vivo spectrum. Despite the fact that MRI and MRS achieve excellent results, they are still not so frequently used in comparison to mammography and breast ultrasound.

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Probably benign lesions at breast magnetic resonance imaging

Liberman

Morris

Benton

et al. 2003

Cancer

100

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The performance of limestone‐derived CaO during many (>1000 in some cases) calcination and carbonation cycles is reported. After 150 cycles, the calcium utilization during carbonation reached a minimum value between 4 and 17%, with the asymptotic level depending strongly on the carbonation time. With the aid of mechanistic studies including investigations on sorbent surface topology by SEM and mercury intrusion, a mechanism for pore evolution during the cyclic capture is proposed consistent with the experimental observations. © 2008 American Institute of Chemical Engineers AIChE J, 2008

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MR Imaging—Detected Breast Lesions: Histopathologic Correlation of Lesion Characteristics and Signal Intensity Data

Cited by 59 publications

References 31 publications

Can semi-quantitative evaluation of uncertain (type II) time-intensity curves improve diagnosis in breast DCE-MRI?

Can semi-quantitative evaluation of uncertain (type II) time-intensity curves improve diagnosis in breast DCE-MRI?

Nuclear Magnetic Resonance as a Diagnostic Tool in Breast Cancer

Probably benign lesions at breast magnetic resonance imaging

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