Miharu Sasaki

Quantitative histopathology in the prognostic evaluation of patients with transitional cell carcinoma of the urinary bladder

Background. Morphologic grading of malignancy is considered to be of prognostic value in patients with transitional cell carcinomas of the urinary bladder (TCC). This qualitative approach is, however, associated with low reproducibility. Grading of malignancy can be carried out on a reproducible, quantitative scale.

ROLE OF VOLUME WEIGHTED MEAN NUCLEAR VOLUME FOR PREDICTING DISEASE OUTCOME IN PATIENTS WITH RENAL CELL CARCINOMA

PURPOSE Histological grading of malignancy in renal cell carcinoma is based on qualitative, morphological examination and suffers from poor reproducibility. On the other hand, estimate of volume weighted mean nuclear volume, which was developed based on a stereological technique, is an easy method to perform with high reproducibility. Furthermore, it has been reported that mean nuclear volume is remarkably correlated with prognosis of bladder and prostate cancer. We compared mean nuclear volume to a histological grading method and TNM classification in determining the prognosis of renal cell carcinoma using a Cox proportional hazards model. MATERIALS AND METHODS A retrospective, prognostic study was done of 65 patients with renal cell carcinoma diagnosed by radical nephrectomy or needle punch biopsy between January 1978 and November 1995. Unbiased estimates of mean nuclear volume were compared to TNM classification and histological grading to determine prognostic value. RESULTS Univariate analysis indicated that all TNM classifications, histological grades and estimates of mean nuclear volume were significantly correlated with prognosis of renal cell carcinoma. However, multivariate analysis revealed that estimates of mean nuclear volume and metastasis at diagnosis were the 2 most powerful independent predictors of disease specific survival. CONCLUSIONS Our results indicate that estimates of mean nuclear volume are prognostically superior to morphological grading of renal cell carcinoma. We recommend mean nuclear volume estimates as an adjunct to subjective histological grading in patients with this disease.

Nuclear morphometry for improved prediction of the prognosis of human bladder carcinoma

Background. Histologic grade and clinical stage generally are used for estimating the prognosis of bladder carcinoma. However, both methods have been reported to have a rather low reproducibility and to be unsatisfactory for predicting the recurrence and progression of superficial bladder carcinoma. Recently, nuclear morphometry was used to quantitate the malignant potential of cancer cells in a more objective and reproducible manner. The authors quantitatively analyzed the malignant potential of bladder carcinoma at initial presentation using a combination of several nuclear morphometric variables.

Prognostic Criteria in Patients with Prostate Cancer: Correlation with Volume Weighted Mean Nuclear Volume

PURPOSE Grading of malignancy in prostate cancer is based on qualitative, morphological examination and suffers from poor reproducibility. On the other hand, estimating the volume weighted mean nuclear volume, which was developed by Gunderson and Jensen based on a stereological technique, is a simple method with high reproducibility. Furthermore, it has been reported that mean nuclear volume is remarkably correlated with prognosis of bladder cancer. We compared mean nuclear volume to 2 histological grading methods and clinical stage to determine the prognosis of prostate cancer using a Cox proportional hazards model. MATERIALS AND METHODS A retrospective, prognostic study of 52 patients with prostate cancer diagnosed by transurethral resection of the prostate or needle punch biopsy between January 1983 and July 1994 was performed. Unbiased estimates of mean nuclear volume were compared to patient age at diagnosis, clinical stage, histological grading according to the World Health Organization (WHO) classification and Gleason score of the prognostic value. RESULTS Univariate analysis revealed that estimates of mean nuclear volume (p = 0.0011), clinical stage (p = 0.0014) and WHO classification (p = 0.0010) correlated significantly with progression-free survival, and that clinical stage (p = 0.0005) and estimates of mean nuclear volume (p = 0.0049) correlated significantly with disease-specific survival of patients with prostate cancer. However, multivariate analysis revealed that only estimates of mean nuclear volume and clinical stage were the 2 most powerful independent prognosticators in progression-free and disease-specific survival. CONCLUSIONS Our results indicate that estimates of mean nuclear volume are prognostically superior to morphological grading of malignancy, such as Gleason score and WHO classification, in prostate cancer.

Predicting disease outcome of non-invasive transitional cell carcinoma of the urinary bladder using an artificial neural network model: results of patient follow-up for 15 years or longer.

Background: Patients with non‐invasive (Ta/T1) transitional cell carcinoma (TCC) of the urinary bladder are often observed without progression in the long‐term follow‐up period, although many of them experience recurrence of disease. It is difficult to accurately predict the disease outcome of each patient with Ta/T1 TCC using conventional prognostic criteria. In this study, we examined the usefulness of artificial neural networks (ANNs) to predict the long‐term disease outcome of patients with TCC of the urinary bladder.

Bilateral Renal Cell Carcinoma in a Patient with Tuberous Sclerosis

A case of pure bilateral renal tell carcinoma (RCC) in a 21‐year‐old female diagnosed as having tuberous selerosis is reported. She underwent a left nephrectomv because of her loss of appetite possibly caused by the tumor compressing her intestines. The preoperalive CI scan showed the presence of adipose tissue in bilateral renal tumors, which is highly suggestive of angiomvolipoma (AML). Histological examination, however, revealed no area or component ot the tumor with features characteristic of AML.

Combining volume-weighted mean nuclear volume with Gleason score and clinical stage to predict more reliably disease outcome of patients with prostate cancer

Various criteria for patients with prostate cancer have been reported to be of prognostic value, and we have reported that estimates of volume‐weighted mean nuclear volume (MNV), developed by Gundersen and Jensen based on a stereological technique, accurately predict the prognosis of prostate cancer. However, all of these studies were conducted on cases in a single institution, and it has remained unclear whether MNV calculations obtained at one institution apply to cases at another institution. In attempting to solve this problem, we made a prognostic index (P.I.) based on data from one hospital, and tested whether these data could be used to predict the prognosis of patients at another hospital.

Prognostic criteria in patients with stage D2 prostate cancer. Correlation with mean nuclear volume

Background. Histologic grading, especially the Gleason score (GS), is considered to be of value in determining the prognosis of patients with prostate cancer. However, subjective histologic grading is characterized by low reproducibility. Conversely, estimates of mean nuclear volume (MNV), developed by Gunderson and Jensen based on a stereologic technique, is a method with high reproducibility. Furthermore, it has been reported that MNV provides an accurate prognosis of bladder cancer. In this study MNV was compared with two histologic grading methods in determining the prognosis of Stage D2 prostate cancer.

Histologic Characteristics of Renal Cell Carcinomas with Lymph Node Metastasis

Background:

The role of volume weighted mean nuclear volume in predicting the prognosis of patients with primary transitional cell carcinoma of the upper urinary tract : A report of 102 new cases

PURPOSE We compare estimates of volume weighted mean nuclear volume (MNV) with histological grading to determine the prognosis of primary transitional cell carcinoma of the upper urinary tract using a Cox proportional hazards model. MATERIALS AND METHODS We retrospectively reviewed 102 patients who underwent nephroureterectomy for primary transitional cell carcinoma of the upper urinary tract at our hospital between April 1981 and March 1997. Traditional prognostic factors, such as patient age, sex, stage and grade, multiplicity and unbiased estimates of MNV were analyzed with respect to disease recurrence and survival. RESULTS Estimates of mean nuclear volume were significantly larger for patients with than without lymph node metastasis (p = 0.0031). No prognostic factor significantly correlated with recurrence of transitional cell carcinoma of the bladder. For pTxN0M0 cases univariate analysis revealed that histological grade (p = 0.0018), pathological T stage (p = 0.0030) and estimates of MNV (p = 0.0001) correlated significantly with disease specific survival, and multivariate stepwise regression analysis revealed that estimate of MNV was the only powerful predictor of prognosis (p = 0.0007). CONCLUSIONS Our results indicate that estimate of MNV is an important predictor of prognosis for transitional cell carcinoma of the upper urinary tract. We recommend MNV estimate as a supportive method for subjective histological grading.