ULTRASONIC NAKAGAMI IMAGING: A STRATEGY TO VISUALIZE THE SCATTERER PROPERTIES OF BENIGN AND MALIGNANT BREAST TUMORS

被引:60
作者
Tsui, Po-Hsiang [1 ]
Yeh, Chih-Kuang [2 ]
Liao, Yin-Yin [2 ]
Chang, Chien-Cheng [1 ,3 ]
Kuo, Wen-Hung [4 ,5 ]
Chang, King-Jen [4 ,5 ]
Chen, Chiung-Nien [4 ,5 ]
机构
[1] Acad Sinica, Div Mech, Res Ctr Appl Sci, Taipei 115, Taiwan
[2] Natl Tsing Hua Univ, Dept Biomed Engn & Environm Sci, Hsinchu, Taiwan
[3] Natl Taiwan Univ, Inst Appl Mech, Taipei, Taiwan
[4] Natl Taiwan Univ Hosp, Dept Surg, Taipei 100, Taiwan
[5] Natl Taiwan Univ, Coll Med, Taipei 10764, Taiwan
关键词
Ultrasound image; Nakagami distribution; Breast tumor; B-MODE IMAGES; COMPUTER-AIDED CLASSIFICATION; NEURAL-NETWORKS; DIAGNOSIS; MASSES; LESIONS; CANCER; SONOGRAPHY; NODULES; SCANS;
D O I
10.1016/j.ultrasmedbio.2009.10.006
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Previous studies have demonstrated the usefulness of the Nakagami parameter in characterizing breast tumors by ultrasound. However, physicians or radiologists may need imaging tools in a clinical setting to visually identify the properties of breast tumors. This study proposed the ultrasonic Nakagami image to visualize the scatterer properties of breast tumors and then explored its clinical performance in classifying benign and malignant tumors. Raw data of ultrasonic backscattered signals were collected from 100 patients (50 benign and 50 malignant cases) using a commercial ultrasound scanner with a 7.5 MHz linear array transducer. The backscattered signals were used to form the B-scan and the Nakagami images of breast tumors. For each tumor, the average Nakagami parameter was calculated from the pixel values in the region-of-interest in the Nakagami image. The receiver operating characteristic (ROC) curve was used to evaluate the clinical performance of the Nakagami image. The results showed that the Nakagami image shadings in benign tumors were different from those in malignant cases. The average Nakagami parameters for benign and malignant tumors were 0.69 +/- 0.12 and 0.55 +/- 0.12, respectively. This means that the backscattered signals received from malignant tumors tend to be more pre-Rayleigh distributed than those from benign tumors, corresponding to a more complex scatterer arrangement or composition. The ROC analysis showed that the area under the ROC curve was 0.81 +/- 0.04 and the diagnostic accuracy was 82%, sensitivity was 92% and specificity was 72%. The results showed that the Nakagami image is useful to distinguishing between benign and malignant breast tumors. (E-mail: mechang@iam.ntu.edu.tw, or mechang@gate.sinica.edu.tw (C.-C. C.)) (C) 2010 World Federation for Ultrasound in Medicine & Biology.
引用
收藏
页码:209 / 217
页数:9
相关论文
共 54 条
  • [1] [Anonymous], 2005, J MED BIOL ENG
  • [2] Does texture analysis improve breast ultrasound precision?
    Bader, W
    Böhmer, S
    Van Leeuwen, P
    Hackmann, J
    Westhof, G
    Hatzmann, W
    [J]. ULTRASOUND IN OBSTETRICS & GYNECOLOGY, 2000, 15 (04) : 311 - 316
  • [3] DIFFERENCES IN MICROCALCIFICATION IN BREAST-TUMORS
    BUSING, CM
    KEPPLER, U
    MENGES, V
    [J]. VIRCHOWS ARCHIV A-PATHOLOGICAL ANATOMY AND HISTOPATHOLOGY, 1981, 393 (03) : 307 - 313
  • [4] Automatic ultrasound segmentation and morphology based diagnosis of solid breast tumors
    Chang, RF
    Wu, WJ
    Moon, WK
    Chen, DR
    [J]. BREAST CANCER RESEARCH AND TREATMENT, 2005, 89 (02) : 179 - 185
  • [5] Breast tumor vascularity identified by contrast enhanced ultrasound and pathology: initial results
    Chaudhari, MH
    Forsberg, F
    Voodarla, A
    Saikali, FN
    Goonewardene, S
    Needleman, L
    Finkel, GC
    Goldberg, BB
    [J]. ULTRASONICS, 2000, 38 (1-8) : 105 - 109
  • [6] Classification of breast ultrasound images using fractal feature
    Chen, DR
    Chang, RF
    Chen, CJ
    Ho, MF
    Kuo, SJ
    Chen, ST
    Hung, SJ
    Moon, WK
    [J]. CLINICAL IMAGING, 2005, 29 (04) : 235 - 245
  • [7] Diagnosis of breast tumors with sonographic texture analysis using wavelet transform and neural networks
    Chen, DR
    Chang, RF
    Kuo, WJ
    Chen, MC
    Huang, YL
    [J]. ULTRASOUND IN MEDICINE AND BIOLOGY, 2002, 28 (10) : 1301 - 1310
  • [8] 3-D ultrasound texture classification using run difference matrix
    Chen, WM
    Chang, RF
    Kuo, SJ
    Chang, CS
    Moon, WK
    Chen, ST
    Chen, DR
    [J]. ULTRASOUND IN MEDICINE AND BIOLOGY, 2005, 31 (06) : 763 - 770
  • [9] Stepwise logistic regression analysis of tumor contour features for breast ultrasound diagnosis
    Chou, YH
    Tiu, CM
    Hung, GS
    Wu, SC
    Chang, TY
    Chiang, HK
    [J]. ULTRASOUND IN MEDICINE AND BIOLOGY, 2001, 27 (11) : 1493 - 1498
  • [10] Cotran RamziS., 1998, ROBBINS PATHOLOGIC B