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Keywords:

  • oral carcinoma;
  • cytology;
  • DNA cytometry;
  • AgNOR analysis;
  • sensitivity;
  • specificity;
  • argyrophilic nucleolar organizer regions;
  • brush biopsy;
  • multinodal cell analysis

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Conflict of Interest Disclosures
  7. References

BACKGROUND:

This report describes what to the authors' knowledge is the first clinical application of semiautomated multimodal cell analysis (MMCA), a novel technique for the early detection of cancer for cases with a limited number of suspicious cells. In this clinical study, MMCA was applied to oral cancer diagnostics on brush biopsies. The MMCA approach was based on the sequential application of multiple stainings of identical, slide-based cells and repeated relocalizations and measurements of their diagnostic features, resulting in multiparametric features of individual cells. Data integration of the variously stained cells increased diagnostic accuracy. The implementation of MMCA also enabled fully automatic, adaptive image preprocessing, including registration of multimodal images and segmentation of cell nuclei.

METHODS:

In a preliminary clinical trial, 47 slides from brush biopsies of suspicious oral lesions were analyzed. The final histologic diagnoses included 20 squamous cell carcinomas, 7 hyperkeratotic leukoplakias, and 20 lichen planus mucosae.

RESULTS:

The stepwise application of 2 additional approaches (morphology, DNA content, argyrophilic nucleolar organizer region counts) increased the specificity of conventional cytologic diagnosis from 92.6% to 100%. This feasibility study provided a proof of concept, demonstrating efficiency, robustness, and diagnostic accuracy on slide-based cytologic specimens.

CONCLUSIONS:

The authors concluded that MMCA may become a sensitive and highly specific, objective, and reproducible adjuvant diagnostic tool for the identification of neoplastic changes in oral smears that contain only a few abnormal cells. Cancer (Cancer Cytopathol) 2009. © 2009 American Cancer Society.

Squamous cell carcinomas of the oral cavity are among the 10 most common cancers in the world and account for approximately 3% to 5% of all malignancies.1, 2 In the last 10 years in Germany, approximately 3100 new cases in men and 1000 new cases in women were encountered annually.3, 4 Despite extensive surgical, chemotherapeutic, and radiotherapeutic efforts, the 5-year survival rate has not improved for these patients and remains at <50%.5-7 Early diagnosis and treatment of malignancies usually optimizes long-term cure and survival.8 Successful screening depends on the widespread application of minimally invasive diagnostic tests.

Until recently, an initial suspicion of head and neck cancer usually was investigated by routine inspection of the oral cavity using imaging modalities such as X-rays, computed tomography (CT) scanning, magnetic resonance imaging (MRI), and sonography for cancer staging. Tumors detected this way already may have grown to considerable size. A histologic investigation, which involves inconvenient or even painful scalpel biopsy, may yield a negative result in up to 23.9% of patients, depending on the underlying lesion.9 In contrast, a cytologic investigation requires only noninvasive smears or brushings.9, 10

Ideally, a diagnostic procedure should be neither time-consuming nor elaborate and, in addition to high sensitivity, should have the potential for automation. High specificity also avoids patient anxiety, additional investigations, and even unnecessary treatment.

Cytology meets all of these requirements optimally, particularly when it is supplemented by an adequate image-analysis method. Morphologic interpretation alone is not sufficient to meet the requirements of sensitivity and specificity; however, both are close to 100% when supplemented.11

The objective of the current clinical study was to apply a novel approach to improving diagnostic accuracy by sequential analysis of cellular characteristics in the same smear using multimodal cell analysis (MMCA).12, 13 We applied the MMCA process to smears from oral brush biopsies, combining conventional cytology with the more quantifiable DNA content, followed by a count of argyrophilic nucleolar organizing regions (AgNORs) to identify early malignant transformation.14-20 Recent studies have demonstrated that the number and/or size of AgNORs correlate with the ribosomal gene activity and, therefore, with cellular proliferation and consequent malignant potential.21-24

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Conflict of Interest Disclosures
  7. References

Each of the 47 patients was examined by an experienced member (T.W.R.) of the Department of Oral and Maxillofacial Surgery. After a thorough intraoral examination, at least 4 cytologic smears were obtained from suspicious lesions using a brush-based cell collector. It was rolled 4 times on the glass slide, followed immediately by fixation with a propanol-containing spray. If clinically indicated (ie, in suspected malignant or equivocal cases), the collection of smears were followed directly by scalpel biopsy.

Papanicolaou Staining and Diagnostic Categories

The slides were stained routinely according to Papanicolaou. The specimens were evaluated according to generally accepted diagnostic criteria by an experienced cytopathologist (A.B.). The following categories of cytologic diagnoses were applied: 1) “insufficient” for specimens without any or with exclusively autolytic cells; 2) “tumor cell negative” for unsuspicious, reactive, or inflammatory cellular images; 3) “atypical” in cases with atypical cellular changes (eg, with mild or moderate dysplasia); 4) “suspicious for tumor cells” if only sparse abnormal or severe dysplastic squamous cells were observed or if the diagnostic criteria for malignancy were only vague; and 5) “tumor cell positive” for smears that contained unequivocal malignant cells.27

Feulgen Staining

Papanicolaou-prestained slides were uncovered in xylene and subsequently destained and restained in a temperature-controlled staining machine with Schiff reagent.28 After rehydration in decreasing ethanol concentrations and refixation in buffered 10% formalin, 5 N HCl for acid hydrolysis was applied at 27°C for 1 hour, followed by staining in Schiff reagent (Merck, Darmstadt, Germany) for another hour, followed by rinsing in SO2-water and dehydration at increasing ethanol concentrations.29, 30 The slides were then covered with Entellan (Merck) and stored in the dark.

DNA Measurements

The normal 2c reference value was established by measuring 30 cytologically normal squamous epithelial cells in each slide as an internal reference (mean value of integrated optical densities). Coefficients of variation (CVs) of reference cells generally were below 5%. No correction factor was applied. If present, 300 abnormal or atypical epithelial or carcinoma cells per specimen were measured interactively at random. All cases were measured using at least 300 analysis cells. The performance of our system, which is based on a Leica DMLA automated microscope (Leica, Wetzlar, Germany), meets the standards of the European Society for Analytical Cellular Pathology task force on the standardization of diagnostic DNA image cytometry.20, 31-33

We assumed DNA aneuploidy if 1) the DNA index of the stemline was <0.90/>1.10, or <1.80/>2.20, or <3.60/>4.40; or 2) if cells >9c occurred (9c-exceeding events). A DNA stemline was defined as a frequency peak in a histogram accompanied by values at its 2-fold DNA content. It was defined interactively when the DNA histograms were displayed on the screen by marking its minimum and maximum. Details of software algorithms for precise scene matching, relocalization, and registration have been described in detail elsewhere.12, 34

AgNOR Analysis

Silver staining for AgNOR analysis was performed according to the 1-step method described by Ploton et al,37 Crocker et al,36 and Ruschoff22 with some modifications. Slides that contained smears were uncovered in xylene, fixed in absolute ethanol for 5 minutes, followed by a mixture of 100 mL 96% ethanol with 5 drops acetic acid for an additional 5 minutes, then progressively rehydrated. AgNOR staining was performed using a solution consisting of 1 volume of 2% gelatin in 1% aqueous formic acid and 2 volumes of 50% silver nitrate. The slides were incubated at room temperature for 20 minutes in the dark. After staining, the slides were placed in a dark container, washed 3 times in deinoized distilled water, and submerged in 10% thiosulfate for 10 minutes. The smears were then washed for 5 minutes in tap water, dehydrated in xylene, and mounted in a synthetic medium. The, slides were then stored in the dark.

Manual AgNOR counting was performed on 100 normal cells and abnormal squamous cells for each cytologic smear. These were examined under ×1000 magnification (Achroplan, ×100/1.25 oil; numerical aperture, 0.17; W-PL, ×10/23) in oil immersion. To standardize counting, we followed the method described by Crocker et al.36 First, all silver-stained structures were counted both lying in groups (clusters) and as individual dots39 outside the clusters. The mean number of AgNORs per nucleus as clusters, as satellites, as clusters and satellites together, and all AgNORs lying together in clusters and as satellites were calculated for each case.21

Multimodal Cell Analysis

Through application of the novel MMCA technology, individual cells are tracked while different stains are applied successively. The cells are fixed sufficiently to the microscope slides so that they adhere to their positions even after removal of the coverslips and 2 restainings. Identical cells are shown after Papanicolaou staining, Feulgen staining, and silver nitrate staining (Fig. 1). Thus, the integration of features obtained by adjuvant diagnostic methods can be correlated to individually identified, suspicious cells and evaluated across the board over the entire slide. Instead of isolated values, the fusion provides a data vector for each investigated cell. In turn, diagnostic sensitivity, specificity, and typing accuracy may be improved.

thumbnail image

Figure 1. Triplets of identical atypical (a and b) and suspicious (c) oral squamous epithelial cells. Left to right: Papanicolaou stain, Feulgen stain, silver nitrate stain, and respective DNA histograms. Mean colloidal silver counts per nucleus were (a) 3.7, (b) 5.4, and (c) 5.4. (a) Negative follow-up. (b and c) Biopsy-proven squamous cell carcinoma.

Download figure to PowerPoint

The application of MMCA requires a standard microscope equipped with a digital camera and a motor-driven stage. A digital workstation equipped with a suitable camera interface runs the software needed for microscope control, image management, and analysis. The integrative workstation software facilitates the recognition of individual cells and cell clusters in subsequent stains, aligns the slide movement to an approximate match with previously obtained images of the same region, and, finally, registers individual cells to subpixel accuracy (approximately 0.1 μm). Another software feature is the database-based organization of all functions, ie, images, coordinates of the measured cells, slide identifiers, data resulting from image analysis, and annotations. These data always can be traced back to their origin and correlated with each other as desired.

For MMCA, the operator selects representative regions on the stained slides that contain atypical or abnormal cells. Images are digitized immediately and stored together with their coordinates. Then, the slides are destained and restained by using the Feulgen method (Fig. 1). The newly stained and covered slides then are placed back onto the microscope stage, where the previously recorded coordinates (stored in the database) automatically reposition the slide to the regions of interest that were digitized previously. The accuracy of the mechanic alignment, however, was limited to several micrometers. Without further correction, a significant fraction of nuclei would be lost for a multimodal analysis, because as they lie outside the field of view of the camera. Therefore, the unique constellation of the nuclei, determined by presegmentation, is compared between the previously recorded image and the live image of the newly stained cells to correct the field of view capture.34 The residual displacement is still mostly too large for a morphologic fit, because subcellular structures of interest are only some tenths of a microgram in size. Therefore, the alignment is refined by digital registration.12

Finally, all slides received a third stain with silver nitrate (Fig. 1c) to demonstrate AgNOR dots. A digital registration, as described above, was performed on the digitized regions of interest. The results were appended to the feature set of the individual cells.

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Conflict of Interest Disclosures
  7. References

The study population was comprised of 47 patients (mean age, 61 years; range, 27-84 years; standard deviation, 12 years) who had been referred for examination and treatment of oral lesions to the Department of Oral, Maxillofacial, and Facial Plastic Surgery at the University of Leipzig (Leipzig Germany). The “gold standard” for the establishment of diagnostic accuracy in all cases was the (repeated) scalpel biopsy-based histology, which was validated by clinical follow-up. The final diagnoses included 20 histologically proven squamous cell carcinomas, 7 leukoplakias (according to World Health Organization criteria25, 26), and 20 lichen planus mucosae. There were 17 squamous cell carcinomas, 1 large cell keratinizing carcinoma, 1 adenoid squamous cell carcinoma, and 1 mucoepidermoid carcinoma. Tumor (T) classification revealed that 2 patients had pathologic T1 (pT1) disease, 11 patients had pT2 disease, 3 patients had pT3 disease, and 1 patient had pT4 disease or oral cancer. Lymph node (N) status revealed that 6 patients had pathologically negative lymph nodes (pN0), 6 patients had pN1 disease, and 3 patients had pN2b disease.

In 25 cases, the brushings from suspicious oral lesions were diagnosed cytologically as nonmalignant (tumor cell negative). Four cases were “atypical,” 5 cases were diagnosed as “suspicious for tumor cells,” and 13 specimens were diagnosed as “positive for tumor cells.” The medical reports indicated that, in all 18 specimens that were diagnosed as “suspicious” or “tumor cell positive” and in 2 of 4 specimens that were diagnosed as “atypical,” squamous cell carcinomas were verified by subsequent histopathologic diagnosis (correctly positive). For 27 cases without carcinomas in the clinical follow-up, cytology alone had correctly reported ”negative for tumor cells” in 25 (Table 1). We assessed only “tumor cell negative” cytologic diagnoses as negative and “atypical,” “suspicious,” and “tumor cell positive,” as positive and compared the results with the reference method of histology combined with clinical follow-up. We considered the results of patients' clinical follow-up in 3-month to 6-month intervals for a period of at least 1 year.

Table 1. Diagnoses of 3 Different Methods Applied to 47 Oral Smears Compared With Histology Response to Clinical Follow-up
 Applied Methods
Histology/Follow-upPositiveNegativeTotal
  1. AgNOR indicates argyrophilic nucleolar organizing regions.

 Conventional cytology
 Positive20020
 Negative22527
 DNA image cytometry
 Positive18220
 Negative02727
 AgNOR analysis
 Positive20020
 Negative02727

Therefore, the sensitivity of our cytologic diagnosis in oral smears for the detection of cancer cells was 100% (95% confidence interval [95% CI], 83%-100%), but the specificity for the detection of non-neoplastic cells was 93% (95% CI, 76%-99%), the positive predictive value was 91% (95% CI, 71%-99%), and the negative predictive value was 100% (95% CI, 86%-100%) (Table 2).

Table 2. Diagnostic Accuracy of 3 Different Methods of Multimodal Cell Analysis of Oral Smears
VariableCytology, %DNA ICM, %AgNOR Analysis, %
  1. ICM indicates image cytometry; AgNOR, argyrophilic nucleolar organizing region; PPV, positive predictive value; NPV, negative predictive value.

Sensitivity10090100
Specificity92.6100100
PPV90.9100100
NPV10093.1100

Twelve of 13 cytologically diagnosed tumor cell-positive specimens had DNA aneuploidy. One of our 4 cytologically “atypical” cases was DNA aneuploid, and the other 3 specimens were DNA euploid. Scalpel biopsy revealed squamous cell carcinoma in 2 of those 4 specimens, with 1 that was DNA aneuploid (correct positive) and 1 that was DNA euploid (false-negative). All 5 specimens that were diagnosed cytologically as “suspicious for tumor cells” were DNA aneuploid, and squamous cell carcinoma was identified histologically in all of them. All 25 cytologically tumor-negative specimens were DNA noneuploid (Table 1). Four of 20 squamous cell carcinomas revealed an atypical DNA stemline alone, 5 of 20 had abnormal cells >9c alone, and 9 of 20 had both aspects of DNA aneuploidy.

Therefore, the sensitivity of DNA aneuploidy on oral smears for the detection of cancer cells was 90% (95% CI, 68%-99%), the specificity for the detection of non-neoplastic cells was 100% (95% CI, 87%-100%), the positive predictive value was 100% (95% CI, 82%-100%), and the negative predictive value was 93% (95% CI, 77%-99%) (Table 2).

AgNOR analysis reached a sensitivity of 100% for the diagnosis of malignant cells (95% CI, 83% to 100%) and a specificity of 100% for benign cells (95% CI, 87%-100%), whereas the cutoff level was determined by 5.09 AgNORs per nucleus, as described previously.21 The negative predictive value reached 100% (95% CI, 83%-100%), and the positive predictive value also reached 100% (95% CI, 87%-100%) (Table 2).

DNA image cytometry (DNA-ICM) identified 2 of the cytologically atypical cases as euploid (ie, most likely benign) and all of the suspicious cases as aneuploid (ie, prospectively malignant). Instead, AgNOR analysis clearly could distinguish between nonmalignant and malignant in all 9 atypical and suspicious cases. The sequential application of different methods (eg, DNA cytometry, AgNOR analysis) increased the sensitivity and specificity of our cytologic diagnosis from 90% to 100%.

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Conflict of Interest Disclosures
  7. References

Cytopathologic diagnostics of cancer have major advantages against alternative, more invasive diagnostic procedures. The most striking advantages are the early detection of malignancy before invasion, higher compliance, low costs, and applicability to outpatients, particularly for screening. However, to our knowledge to date, routine application has been hampered by limited diagnostic accuracy. In particular, no single method alone, other than AgNOR analysis,21 has achieved sufficiently high levels of diagnostic sensitivity and specificity.

All information that is gathered from different stains and evaluated by different methods of analysis contributes to the identification and characterization of cancerous or even precancerous cells, each adding a new facet to a complex picture. In the case of doubtful or suspicious cytopathologic findings, further adjuvant methods are necessary to finally reach a definitive diagnosis. These methods may include complementary stains, which may yield additional information. In our current study, the application of Feulgen staining, DNA image cytometry, and finally silver-nitrate staining for AgNOR analysis were used.

The main benefit of the technique presented here is to improve the specificity of cytologic screening without compromising sensitivity. In this way, false-positive results can be decreased, unnecessary histologic biopsies can be avoided, and, hopefully, no cancers will be missed. This improvement in the screening test narrows the “band of uncertainty.”

Cytopathology possesses a repository of many different methods for the evaluation of cells and their components. However, most of these methods rarely are exploited in routine diagnostics, because they need special equipment or specific training, or they are excessively elaborate. It is the merit of the approach presented in this study on oral cancer to combine an appropriate number of different evaluation methods and, thus, to compile a wealth of diagnostic information on few suspicious cells on the same slide. This novel type of MMCA can be implemented only with the support of digital image processing.

MMCA involves a sequential process that includes an initial conventional morphologic evaluation supplemented by the evaluation of diagnostically relevant molecular and subcellular characteristics. An automatic, reliable classification of cell types using morphologic features is a precondition for automatic DNA-ICM. The image-data fusion may lead to an improved diagnostic interpretation of AgNOR configurations: Augmented by the segmentation of nucleoli within the Feulgen stain, AgNOR clusters (unsuspicious aggregations located within nucleoli but sometimes appearing as large satellites) are distinguished reliably from real satellites. A considerable improvement in the diagnostic performance of AgNOR analysis is expected from a novel, automatic AgNOR segmentation process, which not only counts but also will yield area measurements of AgNORs. This new procedure makes use of high-dynamic-range images.23

In this feasibility study, all specimens ran through all stages (including DNA cytometry and AgNOR analysis) of MMCA, which is not necessary in routine application. Because of the hierarchical or cascaded approach of MMCA, a measurement of uncertain specimens is terminated at that stage, when a clear cancer diagnosis is confirmed through additional information (eg, the presence of DNA aneuploidy).

The stepwise, refined MMCA decision process will relieve us from the considerations of an ethics versus economics tradeoff. An uncertainty band is defined between “negative” and “positive” decisions that corresponds to the common definition of microscopic uncertainty or dysplasia. The distinctive feature of the MMCA approach is the stepwise narrowing of the uncertainty band. This allows us to set the thresholds between “negative” and “uncertain” and between “uncertain” and “positive,” such that the probabilities of false-negative and false-positive decisions are reduced; in particular the expense and time incurred when cases with uncertain diagnoses must undergo follow-up staining to append further meaningful features. In this automated procedure, a stepwise reduction of uncertain diagnoses can be repeated until the repertoire of adjuvant cytodiagnostic methods has been fully exploited.

According to our results, MMCA on oral smears may be useful if only few atypical, abnormal, or otherwise suspicious cells are encountered on a single slide that would not be enough to apply ancillary tests, such as DNA-ICM or AgNOR analysis on separate cells on additional slides. In these cases, the cheaper, faster, and more robust method of DNA-ICM would be applied first. Only if this will not yield an unequivocal diagnosis (eg, aneuploidy) would AgNOR analysis be applied on the identical cells.

We were able to demonstrate that DNA-ICM could correctly identify cancer cells in 2 of 4 cytologically atypical cases and in 5 of 5 suspicious cases, but AgNOR analysis identified all of them as abnormal (Table 1). Because the MMCA procedure still is time consuming, we recommend its application only for those cases in which few cytologically suspicious cells are available on a single slide.

This feasibility study demonstrated the efficiency, robustness, and high diagnostic accuracy of MMCA on slide-based smears from oral brushings. Brush biopsies of visible lesions are an easily practicable, cheap, noninvasive, painless, and safe screening method for the detection of oral precancerous lesions and squamous cell carcinomas in all stages. We conclude that MMCA may become a sensitive and highly specific, objective, and reproducible adjuvant tool for the identification of neoplastic cells in smears from oral brush biopsies that contain only a few abnormal cells.

Conflict of Interest Disclosures

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Conflict of Interest Disclosures
  7. References

The MMCA project is supported by the Viktor and Mirka Pollak Fund for Biomedical Engineering and the Innovation Fund of the University Hospital Leipzig.

References

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Conflict of Interest Disclosures
  7. References
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