Meme manyetik rezonans görüntülemede malign ve benign lezyonların ayrımında histogram analizi: ön çalışma

Amaç: Bu çalışma, yağ baskısız T1 ağırlıklı ve yağ baskılı T2 ağırlıklı meme manyetik rezonans (MR) görüntülerinin histogram analizi ile malign ve benign lezyonların ayırt edilip edilemeyeceğini incelemeyi amaçladı. Gereç ve Yöntem: 20 malign, 20 benign hastanın MR görüntüleri retrospektif tarandı. Görüntülerin histogram analizi için Osirix V.4.9 yazılımı kullanıldı. İlgi alanları (ROI) elle lezyonun tamamına yakınını kapsayacak şekilde çizildi. ROI değerlerinden gri seviye yoğunluğu, ortalama, standart sapma, entropi, tekdüzelik, çarpıklık, basıklık, boyut % alt, boyut % üst, boyut % ortalama hesaplandı. Tüm görüntü analizi MATLAB’da kurum içi program kullanılarak sağlandı. Bulgular: Yağ baskısız T1 ağırlıklı görüntülerde, Minimum, %1, %3, %5, %10 ve %25’inci değerleri; malign lezyonlarda benign lezyonlara göre istatistiksel anlamlı olarak daha düşük izlendi. Minimum değer için sensitivite %70, spesifite %63.2 olarak saptandı. Yağ baskılı T2 ağırlıklı görüntülerde Skewness değeri malign lezyonlarda benign lezyonlara göre istatistiksel anlamlı olarak daha yüksek, Uniformity değeri; malign lezyonlarda benign lezyonlara göre istatistiksel anlamlı olarak daha düşük izlendi. Skewness değer için sensitivite %68.4, spesifite %60 olarak saptandı. Uniformity değer için sensitivite %65, spesifite %68.4 olarak saptandı. Sonuç: Bu çalışma, yağ baskısız T1 ağırlıklı ve yağ baskılı T2 ağırlıklı görüntülerin histogram analizinin meme MR görüntülemede malign ve benign lezyonları ayırt etmek için kullanılabileceğini göstermektedir.

Histogram analysis for the differentiation of malignant and benign lesions in breast magnetic resonance imaging: preliminary study

Purpose: The present study assesses whether malignant and benign lesions can be distinguished through histogram analysis of non-fat-suppressed T1-weighted and fat-suppressed T2-weighted breast magnetic resonance images (MRIs). Materials and Methods: MRIs of 20 malignant and 20 benign breast lesions were reviewed retrospectively by histogram analysis performed using Osirix V.4.9 software. The regions of interest (ROIs) were drawn manually to include almost the entire lesion, and values from these ROIs were used to calculate gray-level intensity mean, standard deviation, entropy, uniformity, skewness, kurtosis, and percentile values. Results: In non-fat-suppressed T1-weighted images, the minimum, 1st, 3rd, 5th, 10th and 25th percentile values were significantly lower in the malignant lesions than in the benign lesions. The minimum value had sensitivity of 70% and specificity of 63.2%. On the fat-suppressed T2-weighted images, skewness was significantly higher while uniformity was significantly lower in malignant lesions than benign lesions. Skewness had 68.4% sensitivity and 60% specificity, and uniformity had 65% sensitivity and 68.4% specificity. Conclusion: The results of this study demonstrated that histogram analysis of non-fat-suppressed T1-weighted and fat-suppressed T2-weighted images can be used to differentiate malignant and benign lesions in breast MRI.

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