Open Access

Histopathological grading of breast ductal carcinoma In Situ: validation of a web-based survey through intra-observer reproducibility analysis

  • Fernando Schuh1, 2Email author,
  • Jorge Villanova Biazús2,
  • Erika Resetkova3,
  • Camila Zanella Benfica1,
  • Alessandra de Freitas Ventura4,
  • Diego Uchoa5,
  • Márcia Graudenz1, 5 and
  • Maria Isabel Albano Edelweiss1, 5
Diagnostic Pathology201510:93

https://doi.org/10.1186/s13000-015-0320-2

Received: 18 November 2014

Accepted: 10 June 2015

Published: 10 July 2015

Abstract

Background

Histopathological grading diagnosis of ductal carcinoma in situ (DCIS) of the breast may be very difficult even for experts, and it is important for therapeutic decisions. The challenge may be due to the inaccurate and/or subjective application of the diagnosis criteria. The aim of this study was to investigate the intra-observer agreement between a traditional method and a developed web-based questionnaire for scoring breast DCIS.

Methods

A cross-sectional study was carried out to evaluate the diagnostic agreement of an electronic questionnaire and its point scoring system with the subjective reading of digital images for 3 different DCIS grading systems: Holland, Van Nuys and modified Black nuclear grade system. Three pathologists analyzed the same set of digitized images from 43 DCIS cases using two different web-based programs. In the first phase, they accessed a website with a newly created questionnaire and scoring system developed to allow the determination of the histological grade of the cases. After at least 6 months, the pathologists read again the same images, but without the help of the questionnaire, indicating subjectively the diagnoses. The intra-observer agreement analysis was employed to validate this innovative web-based survey.

Results

Overall, diagnostic reproducibility was similar for all histologic grading classification systems, with kappa values of 0.57 ± 0.10, 0.67 ± 0.09 and 0.67 ± 0.09 for Holland, Van Nuys classification and modified Black nuclear grade system respectively. Only two 2-step diagnostic disagreements were found, one for Holland and another for Van Nuys. Both cases were superestimated by the web-based survey.

Conclusion

The diagnostic agreement between the web-based questionnaire and a traditional method, both using digital images, is moderate to good for Holland, Van Nuys and modified Black nuclear grade system. The use of a scoring point system does not appear to pose a major risk of presenting large (2-step) diagnostic disagreements. These findings indicate that the use of this point scoring system in this web-based survey to grade objectively DCIS lesions is a useful diagnostic tool.

Keywords

ClassificationDuctal carcinoma in situ Scoring systemIntra-observer reproducibility

Background

Ductal carcinoma in situ (DCIS) of the breast consists in lesions with different cytological and architectural characteristics. DCIS lesions are originated in the terminal ductolobular unit and are associated with a variable risk of invasive carcinoma development [14].

From a practical perspective, the precise definition of the histological grade as a predictor of biological behavior is very important, especially in regard to DCIS, because of its association with the risk of developing invasive carcinoma [5].

It is very important to establish reproducible diagnosis that can help the choice of the best treatment for each patient. Therefore, the degree of tumor differentiation is a biological variable which can be used as a prognostic factor [6]. Therapeutic decisions are made based on the histological classification, associated with other factors such as histopathological grading, size of lesion, state of margins, age of patient, mammographic correlation, and other biological markers of tumor aggressiveness assessed by molecular techniques [710].

Since treatment of DCIS may vary according to the potential of evolution and recurrence of the lesion, it is necessary to have clearly defined criteria to classify these lesions [11]. Considering that surgical treatment may vary from an isolated segmental resection, through a segmental resection with radiation therapy, up to a mastectomy, and given the irreversibility of therapeutic action, it is essential that the diagnosis is based on objective criteria that can be easily reproduced in daily practice [12]. Several studies have looked at the issue of diagnostic reliability and intra-observer reproducibility according to the classification studied [1321].

Although several classification systems for DCIS have been proposed, there is only a regular level of diagnostic agreement between pathologists [14]. Many reasons may be suggested to explain this condition. Prior studies differ in how DCIS cases are presented, with variations of the origin and characteristics of the samples, core biopsy or excisional biopsies, association with invasive carcinoma, convenience or random sampling, cases with difficult grade diagnosis or representative cases. Also, there is great variation of professionals included to perform the diagnosis: some are specialists in breast pathology, while others are surgical pathologists directly involved in the diagnosis routine, not exclusively in the interpretation of breast tumors. Furthermore, instruments to gather data differ in the studies conducted so far, which contribute to the difficulty of comparing them, as well as affect the quality of reported information.

Classifications that take into account only parameters related to nuclear morphology have been proposed. These classifications have higher correlation with breast cancer biological behavior than those that take into consideration cytoarchitectural features. Therefore, they provide important clinical information with prognostic value [22].

Telepathology has been studied extensively as a mean of diagnosis and consultation in surgical pathology [2330]. Eusebi et al. [31] have studied the telepathology diagnostic accuracy of pathologists in cases with difficult diagnosis and shown the accuracy of telepathology to be high (agreement of 75.0 %) [31]. However, before telepathology can be used confidently, thorough evaluation of its true diagnostic reproducibility is needed.

For all these reasons, this study intends to validate an electronic questionnaire available on Internet, which through a scoring point system generates the diagnosis of pathological grading of DCIS lesions in different grading systems. This study aims to assess the ability of the created questionnaire and its scoring system to reproduce the diagnosis of the pathologists in their work routine for Hollland and Van Nuys classification systems and Black modified nuclear grade.

Methods

A cross-sectional study was carried out to evaluate the diagnostic agreement of an electronic questionnaire and its point scoring system with the subjective reading of digital images for 3 different DCIS of the breast grading systems. This project was approved by the Ethics and Research Committee at Hospital de Clínicas de Porto Alegre - number 10-247.

Cases in the study

Slides of 43 breast DCIS cases diagnosed at Hospital de Clínicas de Porto Alegre (HCPA) and at MD Anderson Cancer Center were chosen by convenience sampling. Typical examples of DCIS were considered to select these cases. The slides selected were reviewed by two experienced pathologists (MIE and ER) without knowledge of the clinical and demographic characteristics of the patients. Cases in which there was evident invasive ductal carcinoma associated or divergence between the original anatomopathological diagnosis and the review performed at selection were excluded. The case slides were prepared from surgical specimens fixed in buffered formalin and placed in paraffin blocks, using 4 μm thick sections stained with hematoxylin–eosin.

The reviewing pathologists (MIE and ER) obtained several colored digital photomicrographs of the selected DCIS cases. The website provides images of the same field in three different magnifications (100, 200, and 400×). During analysis, the pathologist could enlarge each image provided. Each case had at least 5 images stored in JPEG format, which the observers could access freely with or without magnification.

Participating pathologists

Three pathologists (E.R., M.G., D.U.) experts in breast pathology were invited to participate in this study. Each pathologist had specific experience with one of the study classification systems: Holland, Van Nuys and modified Black nuclear grade. They were invited to participate performing diagnoses with their preferred classification system.

Classification systems assessed

A series of cytonuclear, cytoarchitectural characteristics and patterns of necrosis was used to compose the classification systems (Table 1).
Table 1

Summary of the criteria to determine the nuclear grade for the DCIS classifications studied

Holland

 

High grade

Intermediate grade

Low grade

Nuclei

Pleomorphic nuclei, anisonucleosis, irregular location, usually but not always large

Slight pleomorphism, nuclei showing some variation in size, outline and spacing

Monomorphic nuclei of uniform size, regular outline and spacing, usually small

Chromatin

Vesicular

Fine to coarse

Uniform, fine

Nucleoli

1 or more

Infrequent

No nucleoli

Mitoses

Often present

Occasionally present

Rare

Van Nuys

 

High grade

Intermediate grade

Low grade

Nuclei diameter

>2 RBC

1.5–2 RBC

1–1.5 RBC

Chromatin

Vesicular

Fine to coarse

Uniform, fine

Nucleoli

1 or more

Infrequent

No nucleoli

Comedo-necrosis

Present or absent

Present

Absent

Black Modified Nuclear Grade

 

High grade

Intermediate grade

Low grade

Nuclei

Pleomorphic nuclei, anisonucleosis, irregular location, usually but not always large

Slight pleomorphism, nuclei showing some variation in size, outline and spacing

Monomorphic nuclei of uniform size, regular outline and spacing, usually small

Nuclei diameter

Up to 3 times the diameter of normal nuclei

Up to 2 times the diameter of normal nuclei

Same as normal nuclei

Chromatin

Vesicular

Fine to coarse

Uniform, fine

Nucleoli

1 or more

Infrequent

No nucleoli

Mitoses

Often present

Occasionally present

Rare

The modified Black nuclear grade, used mainly by American pathologists in the evaluation of both invasive and intraductal breast cancer, evaluates the nuclear characteristics of breast cancers. Black and colleagues [32, 33] proposed a nuclear grading system with five grades. Contrary to common practice, grade 0 and 1 were used to designate the most poorly differentiated, or anaplastic neoplasms, whereas grade 4 reflected the well-differentiated tumors. This reversal of the numerical order remained a disturbing aspect of this nuclear grading system and contributed to a lack of wide support for its application. The nuclear-grading system of Black and colleagues has been found to be useful in predicting prognosis [34]. Fischer and coworkers devised a grading method and modified the Black nuclear grading system by reducing it from five to three grades after combining grades 0 and 1 into one group, and grades 3 and 4 into another. Furthermore, they inverted the numerical order so that grade 1 corresponds to the well differentiated carcinomas, and grade 3 reflects the most poorly differentiated tumors. In this study, the participant patologist classified cytonuclear differentiation (nuclear grade) according to criteria published [34].

Holland’s classification, used by the European Pathologists Working Group, primarily emphasizes cytonuclear differentiation and secondarily architectural differentiation (cellular polarization). This system classifies DCIS in three groups: poorly, moderately (intermediately) and well differentiated. The term ‘comedonecrosis’ is not used as a diagnostic criterion [35]. In this study, the participant assessed the criteria to compose the degree of cytonuclear differentiation (nuclear grade), as well as the cellular polarization, according to the criteria published.

The Van Nuys scale values the nuclear grade and the presence or absence of comedo-type necrosis. The presence of any high nuclear grade (with or without comedo-type necrosis) is defined as Group 3. Among the remaining non-high nuclear grade lesions, those with comedo-type necrosis are defined as Group 2, and those without comedo-type necrosis are defined as Group 1. Special types of DCIS are included in this classification [9]. The participant of this study identified both presence and absence of comedo-type necrosis and also the remaining criteria necessary to compose the nuclear grade, according to the literature published.

Web-based model

Partially, the methodology of this study was already published in a previous paper, Schuh et al. [17]. We created two computer software programs which can be accessed through Internet, in website format. Every participant pathologist received a username and password to access the site. Both sites can be accessed by visitors using the login ‘patholdiagn’ and the password ‘123456’.

The three participant pathologists had accessed to the first software through the address http://www.mayer.art.br/cainsitu/site3. This program offers the digitized microscopy images of the 43 DCIS cases in study and a questionnaire containing the characteristics used to compose the three DCIS classification systems (Fig. 1). A scoring system was developed to allow the determination of the histological grade of the cases (Table 2). This electronic questionnaire and the diagnostic scoring point system compose the web-based survey that is proposed to be validated in this study. Based on the evaluation of the data obtained at the end of each case, the program itself accesses the histological grade for the three classification systems.
Fig. 1

Screenshot from the website that provides the newly created questionnaire and scoring system

Table 2

Score for each histological finding for the generation of histological grade for the DCIS classification systems: Holland, Van Nuys and modified Black nuclear grade system

Holland

Van Nuys

Modified black nuclear grade system

G1 if final score <6

G1 if final score <50

G1 if final score <6

(1) monomorphic nuclei of uniform size, regular outline and spacing

(10) Nuclei 1.5 -2 RBC diameter or nuclear size in relation to normal duct: 2 fold variation in nuclear diameter

(1) monomorphic nuclei of uniform size, regular outline and spacing

 

or

 

(1) uniform, fine chromatin

(1) Nuclei 1-1.5 RBC diameter or nuclear size in relation to normal duct: similar, minimal enlargement

(1) Nuclei 1-1.5 RBC diameter or nuclear size in relation to normal duct: similar, minimal enlargement

(1) no nucleoli

(10) fine to coarse chromatin

(1) uniform, fine chromatin

 

or

 

(1) no mitoses

(1) uniform, fine chromatin

(1) no nucleoli

(1) all the cells have a well-defined apex and show polarization

(2) nucleoli insignificant

(1) no mitoses

 

or

 

(1) no nucleoli

(10) any confluent necrosis

or

(1) no necrosis

G2 if final score >5 and <90

G2 if final score >1000 and <1030

G2 if final score >5 and <90 or >13 and <16 if no mitoses

(10) nuclei showing some variation in nuclear size, outline and spacing

(10) Nuclei 1.5 -2 RBC diameter or nuclear size in relation to normal duct: 2 fold variation in nuclear diameter

(10) nuclei showing some variation in nuclear size, outline and spacing

or

or

or

(1) monomorphic nuclei of uniform size, regular outline and spacing

(1) Nuclei 1-1.5 RBC diameter or nuclear size in relation to normal duct: similar, minimal enlargement

(1) monomorphic nuclei of uniform size, regular outline and spacing

(10) fine to coarse chromatin

(10) fine to coarse chromatin

(10) nuclei 1.5 -2 RBC diameter or nuclear size in relation to normal duct: 2 fold variation in nuclear diameter

or

or

or

(1) uniform, fine chromatin

(1) uniform, fine chromatin

(1) nuclei 1-1.5 RBC diameter or nuclear size in relation to normal duct: similar, minimal enlargement

(2) nucleoli insignificant)

(2) nucleoli insignificant

(10) fine to coarse chromatin

or

or

or

(1) no nucleoli

(1) no nucleoli

(1) uniform, fine chromatin

(10) mitoses present

(1000) proeminent central necrosis - comedonecrosis

(2) nucleoli insignificant

or

 

or

(1) absent

 

(1) no nucleoli

(10) polarization present but not pronouced

 

(1) no mitoses

or

  

(1) all the cells have a well-defined apex and show polarization

G3 if final score >95

G3 if final score >100 and <320 or >1100

G3 if final score >95 or >13 and <16 if mitoses are present

(100) pleomorphic nuclei, anisonucleosis, usually but not always large

(100) nuclei >2 RBC diameter or nuclear size in relation to normal duc: 3 fold variation in nuclear diameter

(100) pleomorphic nuclei, anisonucleosis, usually but not always large

or

or

or

(10) nuclei showing some variation in nuclear size, outline and spacing

(10) nuclei 1.5 -2 RBC diameter or nuclear size in relation to normal duct: 2 fold variation in nuclear diameter

(10) nuclei showing some variation in nuclear size, outline and spacing

or

or

or

(1) monomorphic nuclei of uniform size, regular outline and spacing

(1) nuclei 1-1.5 RBC diameter or nuclear size in relation to normal duct: similar, minimal enlargement

(1) monomorphic nuclei of uniform size, regular outline and spacing

(100) coarse, clumped chromatin

(100) coarse, clumped chromatin

(100) nuclei >2 RBC diameter or nuclear size in relation to normal duc: 3 fold variation in nuclear diameter

or

or

or

(10) fine to coarse chromatin

(10) fine to coarse chromatin

(10) nuclei 1.5 -2 RBC diameter or nuclear size in relation to normal duct: 2 fold variation in nuclear diameter

or

or

or

(1) uniform, fine chromatin

(1) uniform, fine chromatin

(1) nuclei 1-1.5 RBC diameter or nuclear size in relation to normal duct: similar, minimal enlargement

(10) evident nucleoli

(10) evident nucleoli

(100) coarse, clumped chromatin

or

or

or

(2) nucleoli insignificant

(2) nucleoli insignificant

(10) fine to coarse chromatin

or

or

or

(1) no nucleoli

(1) no nucleoli

(1) uniform, fine chromatin

(10) mitoses present

(1000) proeminent central necrosis - comedonecrosis

(10) evident nucleoli

or

or

or

(1) mitoses absent

(10) any confluent necrosis

(2) nucleoli insignificant

 

or

or

(100) no true polarization of the cells with orientation toward a lumen

(1) no necrosis

(1) no nucleoli

or

  

(10) polarization present but not pronouced

 

(10) present mitoses

or

 

or

(1) all the cells have a well-defined apex and show polarization

 

(1) absent

After at least six months, the same three pathologists were again assigned to classify the same cases of DCIS. In this phase, the pathologists accessed the second website, http://www.mayer.art.br/cainsitu/site2 (Fig. 2). In this moment, however, the final diagnosis was given by the pathologist without the aid of the questionnaire containing the criteria and scoring system for diagnosis. Each pathologist was responsible for a particular classification system.
Fig. 2

Screenshot from the website that allows subjective diagnosis, without help of the questionnaire

Statistical analysis

The Kappa statistical method was used to access the diagnosis agreement of each classification system by comparing the scoring point system and the subjective reading of the digital images on a web-based survey. Intra-observer reproducibility was calculated using Cohen’s κ statistics. Intra-observer reproducibility between the two methods (scoring point system and subjective analysis) using digital images was calculated for each pathologist [36, 37].

For each classification, the proportion of the different histologic grades found for all cases by the scoring point system and the subjective reading was also estimated.

The histological grading diagnoses were considered semi quantitative variables and were aggregated into 3 categories, with each diagnosis corresponding to a step from well differentiated to undifferentiated. The ordering of these 3 diagnostic categories was low, moderated and high grade. Any difference in diagnostic category between the two methods using digitized images was considered a diagnostic disagreement by 1 or 2 steps. Therefore, diagnoses that fell into the same category were considered concordant.

Program SPSS v.14.0 and PEPI (programs for epidemiologists) v.4.0 were used for statistical analysis of the data.

According to the sample calculation, for a 0.7 Kappa, 95 % confidence interval and 15 % margin of error, at least 43 different cases of DCIS would be needed.

Results

Table 3 shows the proportion of cases found in each histological grade in the three classification systems studied, obtained by the diagnostic scoring system and by the subjective reading of the digital images of DCIS.
Table 3

Proportion of cases found in each histological grade in the three classification systems studied

Systems

Nuclear grade

Diagnostic scoring system

Subjective reading

n (%)

n (%)

Black

Grade 1

12 (27.9)

11 (25.6)

 

Grade 2

10 (23.3)

13 (30.2)

 

Grade 3

21 (48.8)

19 (44.2)

Holland

Grade 1

2 (4.7)

8 (18.6)

 

Grade 2

19 (44.2)

15 (34.9)

 

Grade 3

22 (51.2)

20 (46.5)

Van Nuys

Group 1

17 (39.5)

17 (39.5)

 

Group 2

5 (11.6)

9 (20.9)

 

Group 3

21 (48.8)

17 (39.5)

The intraobserver κ values comparing the scoring point system and the subjective reading of digital images of DCIS for each of the three grading systems are shown in Table 4. A κ value of 1 reflects perfect agreement among all observers. When agreement is only by chance, the κ value is 0, and with κ <0 the observers generally disagree. Although there are no formal criteria to qualitatively describe κ values, many observers consider that κ >0.81 indicate excellent reproducibility, κ from 0.61 to 0.80 good reproducibility, κ from 0.41 to 0.60 moderate reproducibility, κ from 0.21 to 0.40 accetable reproducibility, and κ from 0 to 0.20 poor or weak reproducibility [36]. By these criteria, our results show fair to good intraobserver diagnostic reproducibility. There was no statistically significant difference between kappa values of Holland classification if compared to others (p = 0.317).
Table 4

Intraobserver reproducibility between the scoring point system and the subjective reading for the three different DCIS grading classifications studied

DCIS classification systems

Kappa values (κ ± EP)

Holland

0.57 ± 0.10

Van Nuys

0.67 ± 0.09

Black modificado

0.67 ± 0.09

Table 5 shows the degree of disagreement found in this study between the web-based survey and the subjective reading of the digital images of DCIS, for each classifcation system studied.
Table 5

Degree of disagreements between the web-based survey and the subjective reading in the three classification systems studied

 

1-step disagreement

2-step disagreement

Super-estimateda

Sub-estimateda

Total

Super-estimateda

Sub-estimateda

Total

n (%)

n (%)

n (%)

n (%)

n (%)

n (%)

Holland

8 (18.6)

2 (4.6)

10 (23.2)

1 (2.3)

0 (0.0)

1 (2.3)

Van Nuys

5 (11.6)

3 (7.0)

8 (18.6)

1 (2.3)

0 (0.0)

1 (2.3)

Black

5 (11.6)

4 (9.3)

9 (20.9)

0 (0.0)

0 (0.0)

0 (0.0)

aSuperestimated and Subestimated by the web-based survey vs the subjective reading

Only two 2-step diagnostic disagreements were found, one for Holland and another for Van Nuys. Both cases were superestimated by the web-based survey (Grade 1 subjectively and grade 3 objectively). The case of Holland got grade 3 by the scoring point system because of nuclear grade 1 with absence of polarization. The Van Nuys case scored 3 because the nucleolus was marked as very evident.

1-step diagnostic disagreements were seen in 9 cases of modified Black grade system, 10 cases of Holland classification and 8 Van Nuys classification cases. These 1-step situations mostly have occurred by the scoring point system super estimation.

Discussion

Two different methodological approaches have been advocated for telepathologic diagnosis. In dynamic systems, images are viewed live and in real time as the receiving viewer directly controls specimen orientation, field selection and fine focus of the microscope via robotic controls [38]. In static systems, images are captured in a digital format on an image frame grabber board and then transmitted individually as still images to the receiving viewer. The receiving viewer usually has little or no direct control over microscope functions [10, 25, 27, 28]. Although dynamic imaging is unquestionably the most powerful technological approach, the substantial lower cost favors the use of static imaging methods for review of histological slides [27], as used in this study.

When evaluating the reproducibility of diagnosis made through two or more different method diagnosis modalities, the overall percentage or proportional agreement appears to be a simple and intuitively correct measure of reproducibility. Given the limited number of diagnostic possibilities, it is important to correct for chance agreement. Agreement is the overall or proportional number of cases given the same diagnosis between or within observers, including that part of the agreement which may be attributable to chance. Reproducibility, part of the agreement that may not be explained purely by chance, is appropriately measured by the κ statistic [20]. Reproducibility can be evaluated at the level of 2 or more observers examining the same specimen (inter-observer reproducibility) or at the level of the same observer examining a specimen via 2 or more modalities or in 2 or more occasions (intra-observer reproducibility) [20].

We found that the intra-observer diagnostic reproducibility for digital images using a web-based survey was moderate to good, with κ values ranging from 0.57 ± 0,10 to 0.67 ± 0,09 for intra-observer reproducibility. Factors such as initial selection of slide fields for imaging and transmission, technical factors (digitization, transmission and display), viewer expertise and comfort when viewing and interpreting computer images seem to play a great role in determining intra-pathologist disagreements in the final diagnosis. As instrumentation improves and pathologists gain more experience in sending, receiving and interpreting digital images, the diagnostic reproducibility of digital images is likely to improve [24, 25, 27, 28]. In this study, however, what was confronted was a diagnostic scoring system with a subjective reading just using the static telepathology with the same set of digitized microscopy images of the DCIS cases.

A number of prior studies have addressed the issue of inter-observer and intra-observer reproducibility in the diagnosis of proliferative breast lesions [9, 1317, 19, 29]. In a study examining the diagnostic accuracy of conventional examination of DCIS section slides, Douglas-Jones et al. [14] found an interobserver κ of 0,57 to 0,58 for Van Nuys classification. In that study, 19 participating pathologists reviewed all 60 cases studied [14]. Although in our study we used intraobserver concordance to compare diagnoses by the scoring system and the conventional reading of digital images, the kappa values were very similar to that study.

The diagnostic categories used in this study are semiquantitative in nature, limited to three categories: low, moderated and high grade. For quality assurance purpose, a minor discrepancy is often defined as a 1-step difference between the original and the observer diagnoses and a major discrepancy as a 2-step difference. It is a relevant aspect to be considered because differences of more than one step may be expected to result in significantly different follow-up/treatment approaches. However in this study only two 2-step diagnostic disagreements occurred, one for Holland and another for Van Nuys.

One conclusion that can be drawn from this study is that its results demonstrate for the first time that histological grading of DCIS, evaluated by three different systems, can be applied with a high degree of consistency using the available scoring point system on this innovative web-based survey. In fact, the level of observer agreement we obtained in this study was higher than that seen in prior studies of observer agreement in proliferative breast lesions [9, 1317, 19, 29].

There are a number of potential limitations to this study. First, it could be argued that our results may not be representative of the level of agreement attainable in general pathology practice, because all pathologists participating in this study have a particular interest in breast pathology. Second, the pathologists in this study were asked to render their diagnoses following examination of selected digital images rather than following examination of whole histological sections under the microscope, as done in routine clinical practice. However, given that the goal of this study was to assess observer variability in the classification of specific lesions, we believe that the use of digital images could be viewed as a strength of the study, as it required the participants to base their diagnoses only in the microscopic features of the lesions in question, without the aid of surrounding histological clues.

Conclusions

In summary, the intra-observer diagnostic reproducibility of DCIS with the use of digital images in a web-based survey comparing subjective analysis with the use of a point scoring system is fair to good for Holland, Van Nuys and modified Black nuclear grade system. The use of scoring point system does not appear to pose a major risk of presenting large (2-step) diagnostic disagreements. These findings indicate that the use of this point scoring system in this web-based survey to objectively grade DCIS lesions is a promising and useful diagnostic tool.

Declarations

Acknowledgements

This research was funded by "Hospital de Clínicas de Porto Alegre - Fundo de Incentivo à Pesquisa e Eventos (HCPA - FIPE)".

Authors’ Affiliations

(1)
Universidade Federal do Rio Grande do Sul (UFRGS)
(2)
Breast surgeon, Hospital de Clínicas de Porto Alegre (HCPA)
(3)
Department of Pathology, MD Anderson Cancer Center
(4)
Breast surgeon, Hospital São Cristóvão
(5)
Department of Pathology, Hospital de Clínicas de Porto Alegre (HCPA)

References

  1. Burstein HJ, Polyak K, Wong JS, et al. Ductal carcinoma in situ of the breast. N Engl J Med. 2004;350:1430–41.PubMedView ArticleGoogle Scholar
  2. Harris JR, Lippman ME, Morrow M, Osborne CK. Diseases of the breast. Lippincott Williams e Wilkins; 2004Google Scholar
  3. Rosen PP, Oberman H. Tumors of the mammary gland. Armed Forces Institute of Pathology; 1993Google Scholar
  4. Tavassoli FA, Devilee P. World Health Organization Classification of Tumours. Pathology and genetics of tumours of the breast and female genital organs. Lyon: IARC Press; 2003. p. 60–81.Google Scholar
  5. Goldhirsch A, Glick JH, Gelber AS, et al. Meeting highlights: international expert consensus on the primary therapy of early breast cancer 2005. Ann Oncol. 2005;16:1569–83.PubMedView ArticleGoogle Scholar
  6. Consensus conference on the classification of ductal carcinoma in situ. Hum Pathol. 1997;28:1221–25.Google Scholar
  7. Lagios MD, Margolin FR, Westdahl PR, et al. Mammographically detected duct carcinoma in situ. Frequency of local recurrence following tylectomy and prognostic effect of nuclear grade on local recurrence. Cancer. 1989;63:618–24.PubMedView ArticleGoogle Scholar
  8. Ponzone R, Dominguez A, Marra V, et al. Pathological classification of ductal carcinoma in situ of the breast correlates with surgical treatment and may be predicted by mammography. Breast. 2007;16:495–502.PubMedView ArticleGoogle Scholar
  9. Silverstein MJ, Lagios MD, Craig PH, et al. A prognostic index for ductal carcinoma in situ of the breast. Cancer. 1996;77:2226–74.View ArticleGoogle Scholar
  10. Van de Vijner MJ. Biologic variables and prognosis of DCIS. Breast. 2005;14:509–19.View ArticleGoogle Scholar
  11. Badve S, A’Hern RP, Ward AM, et al. Prediction of local recurrence of ductal carcinoma in situ of the breast using five histological classifications: a comparative study with long follow-up. Hum Pathol. 1998;29:915–23.PubMedView ArticleGoogle Scholar
  12. Douglas-Jones AG, Gupta SK, Attanoos RL, et al. A critical appraisal of six modern classifications of ductal carcinoma in situ of the breast (DCIS): correlation with grade of associate invasive carcinoma. Histopathology. 1996;29:397–409.PubMedView ArticleGoogle Scholar
  13. Bethwaite P, Smith N, Delahunt B, et al. Reproducibility of a new classification schemes for pathology of ductal carcinoma in situ of the breast. J Clin Pathol. 1998;51:450–4.PubMed CentralPubMedView ArticleGoogle Scholar
  14. Douglas-Jones AG, Morgan JM, Appleton MA, et al. Consistency in the observation of feature used to classify duct carcinoma in situ (DCIS) of the breast. J Clin Pathol. 2000;53:596–602.PubMed CentralPubMedView ArticleGoogle Scholar
  15. Salles MA, Mattos MA, Resende IM, et al. Análise interobservador no diagnóstico histopatológico do carcinoma ductal in situ da mama. Rev Brasil Ginecol Obstet. 2005;27:1–6.View ArticleGoogle Scholar
  16. Schnitt SJ, Connolly JL, Tavassoli FA, et al. Interobserver reproducibility in the diagnosis of ductal proliferative breast lesions using standardized criteria. Am J Surg Pathol. 1992;16:1133–43.PubMedView ArticleGoogle Scholar
  17. Schuh F, Biazús JV, Resetkova E, et al. Reproducibility of three classification systems of ductal carcinoma in situ of the breast using a web-based survey. Pathol Res and Pract. 2010;206:705–11.View ArticleGoogle Scholar
  18. Scott MA, Lagios MD, Axelsson K, et al. Ductal Carcinoma in situ of the breast: reproducibility of histological subtype analysis. Hum Pathol. 1997;28:967–73.PubMedView ArticleGoogle Scholar
  19. Sloane JP, Amendoeira I, Apostolikas N, et al. Consistency achieved by 23 European pathologists in categorizing ductal carcinoma in situ of the breast using five classifications. Hum Pathol. 1998;10:1056–62.Google Scholar
  20. Sneige N, Lagios MD, Schwarting R, et al. Interobserver reproducubility of the Lagios nuclear grading system for ductal carcinoma in situ. Hum Pathol. 1999;30:257–62.PubMedView ArticleGoogle Scholar
  21. Wells WA, Carney PA, Eliassen MS, et al. Pathologists’ agreement with experts and reproducibility of breast ductal carcinoma in situ classification schemes. Am J Surg Pathol. 2000;24:651–9.PubMedView ArticleGoogle Scholar
  22. Pinder SE. Ductal carcinoma in situ (DCIS): pathological features, differential diagnosis, prognostic factors and specimen evaluation. Mod Pathol. 2010;23:8–13.View ArticleGoogle Scholar
  23. Halliday BE, Bhattacharyya AK, Graham AR, et al. Diagnostic accuracy of an international static-imaging telepathology consultation service. Hum Pathol. 1997;28:17–21.PubMedView ArticleGoogle Scholar
  24. Kayser K. Telepathology in Europe. Its practical use. Arch Anat Cyto Pathol. 1995;43:196–9.Google Scholar
  25. Weinberg DS, Allaert FA, Dusserre P, et al. Telepathology diagnosis by means of digital still images: an international validation study. Hum Pathol. 1996;27:111–8.PubMedView ArticleGoogle Scholar
  26. Weinstein LJ, Epstein JI, Edlow D, et al. Static image analysis of skin specimens: the application of telepathology to frozen section evaluation. Hum Pathol. 1997;28:22–9.PubMedView ArticleGoogle Scholar
  27. Weinstein RS, Bhattacharyya AK, Graham AR, et al. Telepathology: a ten year progress report. Hum Pathol. 1997;28:1–7.PubMedView ArticleGoogle Scholar
  28. Weinstein RS, Bloom KJ, Rozek LS. Telepathology: long-distance diagnosis. Am J Clin Pathol. 1989;91:39–42.Google Scholar
  29. Weinstein RS, Graham AR, Lynne C, et al. Overview of telepathology, virtual microscopy, and whole slide imaging: prospects for the future. Hum Pathol. 2009;40:1057–69.PubMedView ArticleGoogle Scholar
  30. Piccolo D1, Soyer HP, Burgdorf W, et al. Concordance between telepathologic diagnosis and conventional histopathologic diagnosis: a multiobserver store-and-forward study on 20 skin specimens. Arch Dermatol. 2002;138(1):53–8.PubMedView ArticleGoogle Scholar
  31. Eusebi V, Foschini L, Erde S, et al. Transcontinental consults in surgical pathology via the internet. Hum Pathol. 1997;28:13–6.PubMedView ArticleGoogle Scholar
  32. Black MM, Barclay TH, Hankey BF, et al. Prognosis in breast cancer utilizing histologic characteristics of the primary tumor. Cancer. 1975;36:2048–55.PubMedView ArticleGoogle Scholar
  33. Black MM, Opler SR, Speer FD. Survival in breast cancer cases in relation to the structure of the primary tumor and regional lymph nodes. Sur Gyn Obst. 1995;100:543–51.Google Scholar
  34. Fisher ER, Redmond C, Fisher B. Histologic grading of breast cancer. Pathol Annu. 1980;15:239–51.PubMedGoogle Scholar
  35. Holland R, Peterse JL, Millis RR, et al. Ductal carcinoma in situ: a proposal for a new classification. Semin Diagn Pathol. 1994;11:167–70.PubMedGoogle Scholar
  36. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–74.PubMedView ArticleGoogle Scholar
  37. Svanholm H, Staklint H, Gundersen HJG, et al. Reproducibility of histomorphologic diagnosis with special reference to the kappa statistic. APMIS. 1989;97:689–98.PubMedView ArticleGoogle Scholar
  38. Mun SK, Esayed AM, Tohme WG, et al. Teleradiology/telepathology requirements and implementation. J Med Sys. 1995;19:153–64.View ArticleGoogle Scholar

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© Schuh et al. 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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