Intraductal Adenocarcinoma of the Prostate With Cribriform or Papillary Ductal Morphology: Rare Biopsy Cases Lacking Associated Invasive High-grade Carcinoma

Prostatic duct adenocarcinoma, characterized by pseudostratified columnar epithelium, has historically been considered invasive carcinoma, although it may commonly have an intraductal component. Usual (acinar) intraductal carcinoma of the prostate (IDC-P) is a noninvasive high-risk lesion typically associated with high-grade, high-stage prostate cancer. Whereas there have been rare biopsy studies of pure acinar IDC-P or IDC-P associated with only low-grade carcinoma, there have been no analogous series of IDC-P with cribriform or papillary ductal morphology on biopsy unassociated with invasive high-grade carcinoma. We identified 14 patients with biopsies showing IDC-P with ductal morphology, defined as prostatic duct adenocarcinoma confined to glands/ducts with immunohistochemically proven retention of basal cells. Our series includes 12 patients with pure IDC-P and 2 patients with concurrent low-volume Grade Group 1 invasive cancer in unassociated cores. Three patients underwent radical prostatectomy: 2/3 had high-grade cancer in their resection specimen (Grade Group 3, Grade Group 5), including 1 with advanced stage and nodal metastases; 1/3 had Grade Group 1 organ-confined carcinoma and spatially distinct IDC-P with ductal morphology. Five men had only follow-up biopsies: 2/5 had cancer (Grade Group 2, Grade Group 4); 1/5 had IDC-P (on 2 repeat biopsies); and 2/5 had benign transurethral resection of the prostate. In all 5 cases with invasive cancer, the invasive portion was comprised purely of acinar morphology; no invasive ductal component was identified. Five patients did not have follow-up biopsies and were treated with radiation therapy±androgen deprivation. One patient had no follow-up information. In an analogous situation to acinar IDC-P, we propose that rarely there is a precursor form of ductal adenocarcinoma that can exist without concurrent invasive high-grade carcinoma and propose the term "IDC-P with ductal morphology," consistent with the terminology for acinar prostate adenocarcinoma. Until more evidence is accumulated, we recommend reporting and treating patients with IDC-P with ductal morphology in a manner analogous to those with acinar IDC-P. As with pure IDC-P with acinar morphology, we would also recommend not grading pure IDC-P with ductal morphology. Finally, we propose a new addition to the diagnostic criteria of IDC-P to include intraductal lesions with ductal morphology consisting of papillary fronds or cribriform lesions lined by cytologically atypical pseudostratified epithelium.

DCE-MRI Pharmacokinetic-Based Phenotyping of Invasive Ductal Carcinoma: A Radiomic Study for Prediction of Histological Outcomes

Breast cancer is a disease affecting an increasing number of women worldwide. Several efforts have been made in the last years to identify imaging biomarker and to develop noninvasive diagnostic tools for breast tumor characterization and monitoring, which could help in patients' stratification, outcome prediction, and treatment personalization. In particular, radiomic approaches have paved the way to the study of the cancer imaging phenotypes. In this work, a group of 49 patients with diagnosis of invasive ductal carcinoma was studied. The purpose of this study was to select radiomic features extracted from a DCE-MRI pharmacokinetic protocol, including quantitative maps of ktrans, kep, ve, iAUC, and R1 and to construct predictive models for the discrimination of molecular receptor status (ER+/ER-, PR+/PR-, and HER2+/HER2-), triple negative (TN)/non-triple negative (NTN), ki67 levels, and tumor grade. A total of 163 features were obtained and, after feature set reduction step, followed by feature selection and prediction performance estimations, the predictive model coefficients were computed for each classification task. The AUC values obtained were 0.826 ± 0.006 for ER+/ER-, 0.875 ± 0.009 for PR+/PR-, 0.838 ± 0.006 for HER2+/HER2-, 0.876 ± 0.007 for TN/NTN, 0.811 ± 0.005 for ki67+/ki67-, and 0.895 ± 0.006 for lowGrade/highGrade. In conclusion, DCE-MRI pharmacokinetic-based phenotyping shows promising for discrimination of the histological outcomes.

Clinical impact of margin status on survival and recurrence pattern after curative-intent surgery for pancreatic cancer

BACKGROUND/OBJECTIVE

The definition of R0 resection for invasive pancreatic ductal carcinoma (IPDC) is important. However, there are different definitions among several countries in the world.

METHODS

From 2001 to 2015, 100 consecutive patients with IPDC who underwent pancreatic resection in our hospital were enrolled. We compared survival and recurrence patterns between the R0 group and R1 group based on the UICC (Union for International Cancer Control) classification (current-R0 vs. current-R1) and based on our revised classification, which defines R0 as a surgical margin of >1 mm (revised-R0 vs. revised-R1).

RESULTS

The 100 patients comprised 58 males and 42 females, and their median age was 70 [32-87]. There were 84 patients in the current-R0 group and 43 in the revised-R0 group. There was no difference in overall survival (OS) or recurrence-free survival (RFS) between the current-R0 group and current-R1 group. However, there was a tendency toward a higher OS rate in the revised-R0 than revised-R1 group (log-rank p = 0.065), and RFS was significantly better in the revised-R0 than revised-R1 group (log-rank p = 0.002). There was no significant difference in the recurrence patterns between the current-R0 and current-R1 groups. In contrast, the local recurrence rate was significantly lower in the revised-R0 than revised-R1 group (21% vs. 42%, respectively; p = 0.026).

CONCLUSION

The revised classification of surgical resection may be more useful than the current UICC classification for prediction of prognosis and local recurrence of IPDC.

Influence of age on PPV of sonographic BI-RADS categories 3, 4, and 5

PURPOSE

The purpose of this retrospective study was to calculate the positive predictive value (PPV) of sonographic Breast Imaging Reporting and Data System (BI-RADS) categories 3, 4, and 5 in different age groups to investigate whether age influences the PPV of the BI-RADS category in breast ultrasound.

MATERIALS AND METHODS

From our sonography-guided core biopsy database of breasts between 2006 and 2008, we identified 2817 BI-RADS category 3, 4, and 5 lesions with known pathological diagnosis in 2587 women, all of whom underwent the earlier breast assessment via ultrasound with a sonographic BI-RADS lexicon and later sonography-guided core biopsy. All lesions were classified into three age groups (< 45, 45 - 59, and > 59 years). The age-related PPVs of each BI-RADS category among three age groups were calculated on the basis of pathological diagnoses and were compared using a χ(2)-test.

RESULTS

The overall PPV of each BI-RADS category was 2.2 % in category 3, 6.5 % in category 4a, 35.2 % in category 4b, 79.6 % in category 4c, and 99.6 % in category 5. The age-related PPVs of category 3 varied significantly among the three age groups (0.9 % versus 3.9 % versus 2.0 % p = 0.048), and notably, the age-related PPV in group 2 was higher than the others. Additionally, there was a significant positive association between the age-related PPVs and increasing age in categories 4a and 4b (4a, p < 0.0001 and 4b, p = 0.0139), but not in categories 4c and 5 (4c, p = 0.1853 and 5, p = 0.2871).

CONCLUSION

The incidence of female breast cancer differs not only in different sonographic BI-RADS categories, but also in different age groups. Therefore, more attention should be paid to the special age group that we found for sonographic BI-RADS categories 3, 4a, and 4b.

Update on the Gleason grading system for prostate cancer: results of an international consensus conference of urologic pathologists

The Gleason system for prostate cancer was based on a study of 270 patients from the Minneapolis Veterans Administration Hospital in 1966-1967. In 1974, Gleason and the Veterans Administrative Cooperative Urological Research Group expanded this study to 1032 men. These studies formed the basis of the Gleason grading system, which is now endorsed as the primary grading system for prostate cancer by the World Health Organization, the Armed Forces Institute of Pathology Fascicle on prostate cancer, the Association of Directors of Anatomic and Surgical Pathology, and the College of American Pathologists. In the nearly 40 years since its inception, several aspects about prostate cancer and its management have changed, most notably serum prostate-specific antigen, transrectal ultrasonography, 18-gauge needle biopsy sampling, immunohistochemistry for the diagnosis of cancer, and radical prostatectomy and radiation therapy as primary treatment modalities. Several aspects of the disease, and consequently the reporting needs, have changed such as reporting cancer on multiple cases in needle biopsies, multiple nodules in prostatectomy, tertiary patterns, variants and variations in prostate cancer. The application of the Gleason system, therefore, has varied considerably in contemporary surgical pathology practice. An International Consensus Conference attended by 80 urologic pathologists from 20 countries was convened to discuss clarifications and modifications to the Gleason system. This article serves as a brief overview and summary of the proceedings that have been published in detail in recent literature.

Time-domain optical mammography SoftScan: initial results

RATIONALE AND OBJECTIVES

Near-infrared (NIR) technology appears promising as a noninvasive technique for breast cancer screening and diagnosis. The technology capitalizes on the relative transparency of human tissue in this spectral range and its sensitivity to the main components of the breast: water, lipid, and hemoglobin. In this study, the authors report quantitative measurements of these components and the functional contrast between healthy and diseased tissue.

MATERIALS AND METHODS

A four-wavelength time domain optical imaging system was used to perform noninvasive NIR measurements in the breast of 49 women both pre- and postmenopausal, ages 24-80. Algorithms based on a diffusive model of light transport provided absolute bulk and local values of breast constituent concentrations.

RESULTS

Important variations in the functional and structural NIR properties of the breast were observed. Demographics trend were noticed in accordance with breast physiology. In the 23 cases imaged with suspicious masses, the optical images were consistent with the mammographic findings. Substantial contrast between masses and adjacent tissue is observed. Moreover, consistent differences between malign and benign cases are found with optical imaging.

CONCLUSION

The results of this pilot study illustrate the sensitivity of optical techniques to the composition of the breast. In addition, preliminary data suggest that benign and malignant tumors can potentially be noninvasively differentiated with optical imaging. Moreover, statistically significant discrimination based on deoxy-hemoglobin content between malign and benign cases was found with optical imaging (P = .0184, one-tailed t test).

Characterization of pure high-grade DCIS on magnetic resonance imaging using the evolving breast MR lexicon terminology: can it be differentiated from pure invasive disease?

Magnetic resonance imaging (MRI) is now a recognized method of imaging the breast. Unfortunately, there is lack of standardization in the MRI terminology used to characterize the appearance of breast lesions. Moreover, cases of mixed histologies are often imaged. We retrospectively identified cases of pure high-grade ductal carcinoma in situ (DCIS) using the recently introduced breast MRI lexicon and characterized the lesions in order to try and identify features that might distinguish high-grade DCIS from invasive disease. Five-year review of our institution's database revealed 637 patients underwent gadolinium-enhanced breast MRI examination. Twenty patients had histologically proven pure high-grade DCIS. After excluding patients with previous chemotherapy or inadequate MRI examination, 13 patients were analyzed and compared to the 13 most recent cases of pure invasive breast carcinoma. The morphological and dynamic features were then compared. High-grade DCIS cases were significantly more likely to show focal branching pattern (P=.03) and to have an irregular contour (P=.03), compared with invasive disease. Although of marginal statistical significance, DCIS lesions are more likely to have a lower morphological score than invasive carcinoma (P=.06), whilst the latter is more likely to show ring enhancement (P=.07). Use of breast MRI for staging at our institution shows that pure DCIS and pure invasive cancers are both rare entities. Despite the relatively limited numbers, we identified features that would help to differentiate high-grade DCIS from invasive carcinoma on MRI.

Bootstrap methods for statistical inference from stereological estimates of volume fraction

We suggest the use of bootstrap methods for inference from stereological estimates of volume fraction. An informal introduction to stereological estimation of volume fraction and to principles of bootstrap techniques is given. The bootstrap method is a robust computer-intensive resampling technique, based on independent random sampling from a data set with replacement. Bootstrap methods were used to estimate confidence intervals for volume fractions, and to test for a significant difference between estimated volume fractions from two samples. Two sampling designs are considered: independent replicated samples (visual fields) from a single object, and estimates of volume fraction from multiple independent objects. The methods are presented as worked examples on real data sets obtained from tumour pathology (mammary cancer, pancreatic cancer). The volume fraction of glandular lumina per total volume of the epithelial phase was chosen as target parameter. It indicates the degree of glandular differentiation in adenocarcinomas and is estimated as a ratio-of-means statistic with variable denominator within cases. The confidence intervals of the volume fraction estimated by the bootstrap method were slightly narrower than the parametrically calculated confidence intervals for all data sets. The outcomes of significance tests based on the bootstrap technique were unchanged as compared with classical tests based on the assumptions of normality and homoscedasticity of the data. Special attention was paid to the reproducibility of the bootstrap technique in replicated trials on the same data.

Robinson cytologic grading of invasive ductal breast carcinoma: correlation with histologic grading and regional lymph node metastasis

OBJECTIVE

To evaluate the importance of cytologic grading of breast carcinoma and its association with histologic grading and the existence of axillary lymph node metastasis.

STUDY DESIGN

Aspirates and surgical samples from 100 patients with invasive ductal breast carcinoma not otherwise specified were studied. In 50 patients, > or = 1 metastatic nodes were identified. The cytologic grade was evaluated using the Robinson method and the histologic grade using the Elston modification of the Bloom-Richardson method. A study was undertaken to establish the association between histologic and cytologic grades and to compare the various parameters used to evaluate cytologic grade with the presence of axillary node metastasis.

RESULTS

A statistically significant association was observed between cytologic and histologic grades (p < 0.0005) and between cytologic grade and presence of axillary metastasis (p < 0.0005). Similarly, cell dissociation (p < 0.0005), cell uniformity (p = 0.0010) and the appearance of nuclear margins (p < 0.0005) all displayed a positive correlation with regional metastasis.

CONCLUSION

Cytologic grade may provide relevant information on the aggressiveness of invasive ductal breast carcinoma and could be a useful parameter to take into consideration when selecting neoadjuvant therapy.

Soft copy versus hard copy reading in digital mammography

The objective of this study was to compare soft copy reading at a mammography work station with hard copy reading of full-field digital mammographic images. Mammograms of 60 patients ( n = 29 malignant, n = 31 benign) performed with full-field digital mammography (Senographe 2000D, GE, Buc, France) were evaluated. Reading was performed based on hard copy prints (Scopix, Agfa, Leverkusen, Germany) and on 2 k x 2.5 k high-resolution monitors (Sun Ultra 60, Sun Microsystems, Palo Alto, California, USA). Four readers with different levels of experience in mammography categorized the mammograms according to the BI-RADS classification. The comparative study was performed by four readers, and at least 2 months elapsed between the reading sessions. Postprocessing, of course, was available only at the work station (windowing and leveling, zooming, inversion). Sensitivity, specificity, and positive predictive value were evaluated. Diagnostic accuracy of the evaluation was determined. Sensitivity for malignant lesions in hard copy versus soft copy reading was 97% vs 90%, 97% vs 97%, 93% vs 97%, and 76% vs 76% for the four readers, respectively. Specificity was 52% vs 68%, 58% vs 74%, 65% vs 48%, and 61% vs 68%. Accuracy for the classification of malignant lesions according to the BI-RADS categories showed no difference between hard copy and soft copy reading. Soft copy reading is possible with the available system and enables radiologists to use the advantages of a digital system.

Classification of Fourier transform infrared microscopic imaging data of human breast cells by cluster analysis and artificial neural networks

Cluster analysis and artificial neural networks (ANNs) are applied to the automated assessment of disease state in Fourier transform infrared microscopic imaging measurements of normal and carcinomatous immortalized human breast cell lines. K-means clustering is used to implement an automated algorithm for the assignment of pixels in the image to cell and non-cell categories. Cell pixels are subsequently classified into carcinoma and normal categories through the use of a feed-forward ANN computed with the Broyden-Fletcher-Goldfarb-Shanno training algorithm. Inputs to the ANN consist of principal component scores computed from Fourier filtered absorbance data. A grid search optimization procedure is used to identify the optimal network architecture and filter frequency response. Data from three images corresponding to normal cells, carcinoma cells, and a mixture of normal and carcinoma cells are used to build and test the classification methodology. A successful classifier is developed through this work, although differences in the spectral backgrounds between the three images are observed to complicate the classification problem. The robustness of the final classifier is improved through the use of a rejection threshold procedure to prevent classification of outlying pixels.