Ovarian malignant tumor detected by objective ultrasound glhw tissue characterization

*Kazuo Maeda
Obstetrics And Gynecology, Tottori University Medical School, Japan
Paul E Kihaile
Obstetrics And Gynecology, Tottori University Medical School, Japan

*Corresponding Author:

Kazuo Maeda
Obstetrics And Gynecology, Tottori University Medical School

Published on: 2017-03-08


Aims: To try to detect malignancy of ovarian masses using ultrasound tissue characterization gray level histogram width (GLHW).

Methods: The GLHW is the width of gray level histogram divided by full gray level length of gray level histogram of common ultrasound B-mode image device. Mean and Coefficient of Variation ( SD/ mean; CV) and mean of ultrasound GLHW in benign ovarian masses calculated in five connected regions of interest (ROI) were compared to those of pathologic tumors pathologically diagnosed after the surgeries to remove ovarian masses.

Results: CV of GLHW was larger in benign than malignant masses, while mean GLHW was larger in malignant than benign masses.

Conclusion: The pathologic malignancy of ovarian masses was diagnosed by the analysis of GLHW ultrasound tissue characterization.


Ovarian masses, Malignancy, Ultrasound tissue characterization, GLHW


The presence of ovarian masses were diagnosed by vaginal examination in old time, and clearly detected by the ultrasound B-mode imaging with abdominal and transvaginal scans. Its histological nature was suspected by 6 cystic or solid patterns1 before their histological studies, however, the pattern study was subjective and difficult to be classified into benign or malignant. Therefore, Kihaile2 compared the GLHW ultrasound tissue characterization to the postoperative histopathological diagnosis.


The GLHW was standardized among various ultrasound B-mode devices and a 3D ultrasound machine using RMI412A ultrasound phantom (Radiation Measurement Inc. Middleton, Wisconsin) by the author3 ,where GLHW value was unchanged if image gain changed, but image contrast should be the lowest, because GLHW value increased if the image contrast increased. Aloka ultrasound B-mode imaging devices (Tokyo Japan) detected ovarian masses, where five connecting ROIs were set at ovarian mass images, and obtained five gray level histograms and five GLHW values in a ovarian tumor. The masses were pathologically studied after surgical resection then the tumors were classified into benign and malignant groups, where coefficient of variation (SD/mean, CV) and mean values of GLHW were compared between benign and malignant groups (Figure 1).

Results and Discussion

Coefficient of variation (CV) of GLHW values
The CV of GLHW was significantly large in benign masses than malignant tumors (Figure 2).

Mean value of GLHW
The mean of GLHW was 51 ± 11% and significantly larger in malignant group than the mean GLHW of benign group which was 18 ± 10% (Figure 2). In summary, mean GLHW was larger and CV was smaller in malignant ovarian tumors than benign tumors.

In other studies, mean GLHW was 42.7 ± 5.0% in normal endometrium, while it was 58.2 ± 11.2% in endometrial cancer, thus, endometrial cancer will be diagnosed using GLHW4,5. Maeda found that the GLHW of an uterine cervical cancer was higher than 50%. Thus, a malignant tissue will be diagnosed, if its GLHW is 50 or more%.

Recently, Nam, et al.6 reported differentiation of malignant and benign thyroid nodules using histogram analysis of gray scale sonograms. Ultrasonic B-mode histogram diagnosis of malignancy was supported also by the report.

Maeda studied adult healthy liver tissue GLHW, and found the GLHW of healthy liver was not influenced by the age, or gender3, therefore, the GLHW will be useful to study adult liver diseases.


Medical ultrasound is useful to detect malignancy, if the GLHW tissue characterization is studied on subject tissue.


  1. New Medical Ultrasound. Obstetrics & Gynecology, Japan Society of Ultrasonic in Medicine, Igakushoin. (2000).
  2. Kihaile PE. Ultrasonic tissue characterization of ovarian tumors by the scanning of grey-level histograms. Yonago Acta Medica. (1989) 31: 75-82.
  3. Maeda K, Utsu M, Kihaile PE. Quantification of sonographic echogenicity with grey-level histogram width; A clinical tissue characterization. Ultrasound Med & Biol (1998) 24: 225-234.
  4. Maeda K, Utsu M, Yamamoto N, et al. Clinical tissue characterization with gray level histogram width in obstetrics and gynecology. Ultrasound Rev Obstet Gynecol. (2002) 2: 124-128.
  5. Ito T. Diagnosis of endometrial cancer with GLHW tissue characterization. Personal communication. (2007).
  6. Nam SJ, Yoo J, Lee HS, et al. Quantitative evaluation for differentiating malignant and benign thyroid nodules using histogram analysis of grayscale sonograms. J Ultrasound Med (2016) 35: 775-782.

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