Convoluted Cerebriform Pattern Research Articles

Predictive Value of Magnetic Resonance Imaging Multi-parametric Analysis for Malignant Transformation of Sinonasal Inverted Papilloma: A Comprehensive Prediction Model.

Accurate preoperative prediction of sinonasal inverted papilloma (SNIP) malignant transformation is essential and challenging. In this study, 3.0T magnetic resonance was used for qualitative, quantitative, and multi-parametric analysis to evaluate the predictive value of magnetic resonance imaging (MRI) in malignant transformation. The data of patients with SNIP (n=83) or SNIP-transformed squamous cell carcinoma (SNIP-SCC) (n=21) were analysed retrospectively. Univariate analysis and multivariate logistic regression were used to establish models to predict the risk factors for the malignant transformation of SNIP. Receiver operating characteristic (ROC) curves were used to evaluate the ability of independent risk factors and related combination models to predict the malignant transformation of SNIP. Convoluted cerebriform pattern (CCP) mutation, apparent diffusion coefficient ratio (ADCr), and wash-in index (WII) 2 and 3 were independent risk factors for predicting malignant transformation of SNIP, with area under the ROC curve (AUC) values of 0.845, 0.862, 0.727, and 0.704, respectively. The AUC of the quantitative parameter model combined with ADCr and WII 2 and 3 was 0.910 for diagnosing malignant transformation. The AUC of the comprehensive model comprising all independent risk factors was 0.937, with a sensitivity, specificity, and accuracy of 90.48%, 90.36%, and 92.31%, respectively. Compared with assessing independent risk factors of CCP mutation, ADCr and WII, and the quantitative parameter model, the comprehensive model could improve the differential diagnosis ability of SNIP and SNIP-SCC, which provides an important imaging basis for the possible accurate preoperative evaluation of the malignant transformation of SNIP.

Development and validation of apparent diffusion coefficient histogram-based nomogram for predicting malignant transformation of sinonasal inverted papilloma.

To develop and validate a nomogram based on whole-tumour histograms of apparent diffusion coefficient (ADC) maps for predicting malignant transformation (MT) in sinonasal inverted papilloma (IP). This retrospective study included 209 sinonasal IPs with and without MT, which were assigned into a primary cohort (n = 140) and a validation cohort (n = 69). Eight ADC histogram features were extracted from the whole-tumour region of interest. Morphological MRI features and ADC histogram parameters were compared between the two groups (with and without MT). Stepwise logistic regression was used to identify independent predictors and to construct models. The predictive performances of variables and models were assessed using the area under the curve (AUC). The optimal model was presented as a nomogram, and its calibration was assessed. Four morphological features and seven ADC histogram parameters showed significant differences between the two groups in both cohorts (all p < 0.05). Maximum diameter, loss of convoluted cerebriform pattern, ADC10th and ADCSkewness were identified as independent predictors to construct the nomogram. The nomogram showed significantly better performance than the morphological model in both the primary (AUC, 0.96 vs 0.88; p = 0.006) and validation (AUC, 0.96 vs 0.88; p = 0.015) cohorts. The nomogram showed good calibration in both cohorts. Decision curve analysis demonstrated that the nomogram is clinically useful. The developed nomogram, which incorporates morphological MRI features and ADC histogram parameters, can be conveniently used to facilitate the pre-operative prediction of MT in IPs.

MRI radiomics-based machine learning model integrated with clinic-radiological features for preoperative differentiation of sinonasal inverted papilloma and malignant sinonasal tumors.

ObjectiveTo explore the best MRI radiomics-based machine learning model for differentiation of sinonasal inverted papilloma (SNIP) and malignant sinonasal tumor (MST), and investigate whether the combination of radiomics features and clinic–radiological features can produce a superior diagnostic performance.MethodsThe database of 247 patients with SNIP (n=106) or MST (n=141) were analyzed. Dataset from scanner A were randomly divided into training set (n=135) and test set 1 (n=58) in a ratio of 7:3, and dataset from scanner B and C were used as an additional independent test set 2 (n=54). Fourteen clinic-radiological features were analyzed by using univariate analysis, and those with significant differences were applied to construct clinical model. Based on the radiomics features extracted from single sequence (T2WI or CE-T1WI) and combined sequence, four commonly used classifiers (logistic regression (LR), support vector machine (SVM), decision tree (DT) and k-nearest neighbor (KNN)) were employed to constitute twelve different machine learning models, and the best-performing one was confirmed as the optimal radiomics model. Furthermore, a combined model incorporated best radiomics feature subsets and clinic-radiological features was developed. The diagnostic performances of these models were assessed by the area under the receiver operating characteristic (ROC) curve (AUC) and the calibration curves.ResultsFive clinic-radiological features (age, convoluted cerebriform pattern sign, heterogeneity, adjacent bone involvement and infiltration of surrounding tissue) were considered to be significantly different between the tumor groups (P < 0.05). Among the twelve machine learning models, the T2WI-SVM model exhibited optimal predictive efficacy for classification tasks on the two test sets, with the AUC of 0.878 and 0.914, respectively. For three types of diagnostic models, the combined model achieved highest AUC of 0.912 (95%CI: 0.807-0.970) and 0.927 (95%CI: 0.823-0.980) for differentiation of SNIP and MST in test 1 and test 2 sets, which performed prominently better than clinical model (P=0.011, 0.005), but not significantly different from the optimal radiomics model (P=0.100, 0.452).ConclusionThe machine learning model based on T2WI sequence and SVM classifier achieved best performance in differentiation of SNIP and MST, and the combination of radiomics features and clinic-radiological features significantly improved the diagnostic capability of the model.

Sinonasal Inverted Papilloma Showing a Misleading Finding on Magnetic Resonance Imaging.

Sinonasal inverted papilloma (IP) is the most common benign tumor in sinonasal cavities. Treatment involves excising the whole tumor, so it is essential to evaluate the extent of the tumor by preoperative radiographic findings. Magnetic resonance imaging (MRI) is superior to computed tomography (CT) for determining a tumor's location as MRI can discern the difference between mucus and IP. We herein report a 51-year-old man with sinonasal IP treated with endoscopic sinus surgery (ESS). Preoperative MRI showed findings resembling a convoluted cerebriform pattern on T2-weighted imaging, but this site was not enhanced by intravenous gadolinium at all. We preoperatively suspected that this site was not part of the tumor but rather the accumulation of mucus, and indeed, we found no tumor at this site when we performed the surgery. This patient is a valuable example of misleading findings of IP on T2-weighted imaging and underscores the importance of contrast-enhanced T1-weighted imaging to determine the extent of IP.

Risk factors of malignant transformation of sinonasal inverted papilloma

Objective:To explore the risk factors of malignant transformation of sinonasal inverted papilloma （SNIP）, and to improve the accuracy of preoperative diagnosis of tumor. Methods:The clinical data of 89 patients with sinonasal inverted papilloma （SNIP group, n=60） and malignant transformation of sinonasal inverted papilloma （IP-SCC, n=29） were analyzed retrospectively. Clinical symptoms, medical history, endoscopic examination, characteristic of sinonasal CT scan and MR imaging were collected and compared between two groups. Then the indicators with significant differences between the two groups were used for binary logistic regression analysis. The logistic regression model was established to predict the malignant transformation risk factors of inverted papilloma and the prediction ability of the regression model was estimated. Results:The significant differences between the two groups were: symptoms, including nasal obstruction, purulent mucus, blood in the nasal discharge; long-term smoking history; tumor attached with purulent mucus; CT scan showing bone destruction of the orbital wall and skull base; MR Imaging showing convoluted cerebriform pattern （CCP） sign, intraorbital involvement, and dural enhancement of the skull base. The results of logistic regression analysis showed that the risk factors of malignant transformation of SNIP were blood in the nasal discharge, long-term smoking history, tumor with purulent discharge, orbital wall destruction on CT scan, disappearance of CCP and orbital involvement on MRI. The accuracy rate of regression model for predicting malignant transformation of IP is 75.0%, and the accuracy rate for benign inverted papilloma is 96.7%, and the overall accuracy of the model is 89.8%. Conclusion:The risk factors for predicting malignant transformation of SNIP are blood in the nasal discharge, long-term smoking history, tumor with purulent discharge, orbital wall destruction on CT scan, and disappearance of CCP sign and orbital involvement on MRI. It's necessary to analyze all of clinical factors in order to improve the accuracy of preoperative diagnosis of sinonasal inverted papilloma.

MRI Predictors of Malignant Transformation in Patients with Inverted Papilloma: A Decision Tree Analysis Using Conventional Imaging Features and Histogram Analysis of Apparent Diffusion Coefficients

ObjectivePreoperative differentiation between inverted papilloma (IP) and its malignant transformation to squamous cell carcinoma (IP-SCC) is critical for patient management. We aimed to determine the diagnostic accuracy of conventional imaging features and histogram parameters obtained from whole tumor apparent diffusion coefficient (ADC) values to predict IP-SCC in patients with IP, using decision tree analysis.Materials and MethodsIn this retrospective study, we analyzed data generated from the records of 180 consecutive patients with histopathologically diagnosed IP or IP-SCC who underwent head and neck magnetic resonance imaging, including diffusion-weighted imaging and 62 patients were included in the study. To obtain whole tumor ADC values, the region of interest was placed to cover the entire volume of the tumor. Classification and regression tree analyses were performed to determine the most significant predictors of IP-SCC among multiple covariates. The final tree was selected by cross-validation pruning based on minimal error.ResultsOf 62 patients with IP, 21 (34%) had IP-SCC. The decision tree analysis revealed that the loss of convoluted cerebriform pattern and the 20th percentile cutoff of ADC were the most significant predictors of IP-SCC. With these decision trees, the sensitivity, specificity, accuracy, and C-statistics were 86% (18 out of 21; 95% confidence interval [CI], 65–95%), 100% (41 out of 41; 95% CI, 91–100%), 95% (59 out of 61; 95% CI, 87–98%), and 0.966 (95% CI, 0.912–1.000), respectively.ConclusionDecision tree analysis using conventional imaging features and histogram analysis of whole volume ADC could predict IP-SCC in patients with IP with high diagnostic accuracy.

Dermatoscopic and morphological features of some clinical variants of seborrheic keratosis

Objective — to determine medical tactics, trace the relationship and supplement the correlation information between clinical manifestations, dermatoscopic patterns and histological picture of typical and flat variants of seborrheic keratosis (SK).Materials and methods. The studies were conducted in Zaporizhzhya Regional Dermatovenerological Clinical Hospital of Zaporizhzhya Regional Council. 20 persons with seborrheic keratosis were monitored — 14 (70 %) women and 6 (30 %) men aged 41 to 87. The screening included a general, dermatoscopic and pathomorphological examination of the patient.Results and discussion. More often, lesions were localized on the skin of the body — in 10 persons, on face and scalp — in 5, on lateral neck — in 3, less often on upper limbs — in 2 patients. Fitzpatrick’s І phototype was detected in 3 (15 %) persons, ІІ phototype — in 13 (65 %), ІІІ phototype — in 4, which equals to 20 %. Histologically, the acanthotic type of seborrheic keratosis was identified in 14 (70 %), papillomatous and reticular in — 5 and 1 patients, respectively. The dermatoscopic picture of the acanthotic variant is represented by the following criteria: milia­like cysts— in 10 cases, comedo­like openings— in 4, «convoluted cerebriform pattern» — in 5, «moth­eaten» border — in 2, verrucous surface — in 1, papillomatous SK with verrucous, papillary surface — in 1, keratoma with patterns of «finger print» type — in 3 cases. The reticular (adenoid) variant is represented by a symmetrical lesion of dark brown color and round shape up to 0.5 cm in diameter with moth-­eaten borders and milia­-like cysts around the periphery. Conclusions. The variability of the clinical, dermatoscopic, and pathomorphological manifestations of seborrheic keratosis needs further search for new algorithms of therapy and differential diagnosis of malignant skin tumors.

Clinical evidence based review and systematic scientific review in the identification of malignant transformation of inverted papilloma

BackgroundInverted papilloma (IP) is an unusual type of benign tumor that has high recurrence rates and the potential to transform into squamous cell carcinomas (SCC). The mechanism of the transformation process from IP to IP-SCC is uncertain and there is no consensus regarding the best practice for IP-SCC detection. The goal of this study is to identify the best clinical methods to detect for IP-SCC.MethodsAn evidence-based review was performed using Medline and Ovid to obtain all articles up to October 10th, 2019 pertaining to identification of IP malignant transformation. All manuscripts discussing clinical methods or biomarkers were included.ResultsBased on clinical research studies, convoluted cerebriform pattern and apparent diffusion coefficient values on Magnetic Resonance Imaging (MRI) can help differentiate benign IP from SCC and increased SUVmax on PET/CT is associated with higher probability of malignancy although not as specific. No consensus about the best biomarker for IP-SCC has been reached among researchers and continues to be exploratory.ConclusionEndoscopy with biopsy is the gold standard practice to identify IP-SCC; however, MRI is the preferred imaging modality to recognize malignant transformation in cases where biopsy is difficult. Multiple biomarkers have shown positive results, but no single indicator with clinical significance for monitoring malignant transformation process has been found.

Prediction of malignant sinonasal inverted papilloma transformation by preoperative computed tomography and magnetic resonance imaging.

Accurate preoperative prediction of the malignant transformation of sinonasal inverted papilloma (SNIP) is essential for radical resection of tumours and prevention of recurrence. We here explored the predictive value of preoperative computed tomography (CT) and magnetic resonance imaging (MRI). The study was performed on 268 patients with SNIP with (n = 78) or without (n = 190) coexistent malignant transformation. We used univariate and multivariate logistic regression analysis method to screen for independent risk factors, and established a nomogram model. Finally, using receiver operating characteristic curves, we assessed the diagnostic value of the independent risk factors for malignant transformation of SNIP. We identified bone erosion on CT, change in convoluted cerebriform pattern (CCP) on MRI, and washout-type time intensity curve (TIC) of dynamic contrast-enhanced (DCE)-MRI were independent predictors of malignant transformation of SNIP. The scores of these three independent risk factors from the nomogram model were 10, 7 and 8, respectively. The area under the receiver operating characteristic curve for predicting SNIP malignancy was 0.954 for the nomogram model, 0.826 for bone erosion, 0.776 for washout-type TIC, and 0.810 for CCP mutation. Of the independent risk factors and related combination identified, the nomogram model based on bone destruction on CT, CCP mutation on MRI, and washout-type TIC of DCE-MRI had the best predictive value for malignant transformation of SNIP.

Pathological changes from the originating to the peripheral sites of Sinonasal Inverted Papilloma are the underlying mechanisms of preoperative MRI-tumor origin prediction.

Our previous study showed that convoluted cerebriform pattern (CCP)-based reverse tracing method in preoperative magnetic resonance imaging (MRI) is a reliable tool in predicting originating site of sinonasal inverted papilloma (SNIP). This study aimed to determine the underlying pathological mechanism of the preoperative MRI-CCP reverse tracing method by assessing the histopathological changes from the origin to the peripheral sites of SNIP. The originating site of SNIP was predicted by preoperative MRI in 30 consecutive patients suspected to have primary SNIP. Samples of SNIP originating and peripheral sites were processed by pathological staining for evaluation of stroma score, micro-vessel density (MVD), and tight junction proteins (claudin-5, zonula occludens (ZO)-1 and occludin) expression. The originating site of SNIP was accurately predicted by preoperative MRI in all patients. Stroma scores, and MVD were significantly greater in the periphery of SNIP than in the originating site. In contrast, Claudin-5 expression in micro-vessels was greater at the originating site than the periphery. More edematous stroma and intensive micro-vessels with defective tight junction in periphery of SNIP result in more contrast agent diffusing and CCP that can only be observed at the periphery of SNIP on T2 and contrast-enhanced T1 weighted MR images, which may be the mechanisms underlying the CCP reverse tracing method.

Multiparametric MRI in differentiation between sinonasal inverted papilloma and malignant transformation of inverted papilloma

Objective To identify the value of multiparametric MR imaging features including diffusion weighted (DW) and dynamic contrast-enhanced (DCE) MR imaging features in differentiation between inverted papilloma and malignant transformation of inverted papilloma in the sinonasal region. Methods Seventy-seven patients were included in this study, including 12 malignant transformation of inverted papilloma and 65 inverted papillomas. Conventional MRI including nonenhanced and static contrast-enhanced imaging, DCE-and the DW-MRI were analyzed. Differences in conventional MRI features, ADCs and DCE-MRI parameters between the two entities were determined by Fisher exact test, independent samples t-test and Mann-Whitney U test, respectively. Results There were significant differences in convoluted cerebriform pattern (P=0.045), necrosis (P=0.003) and orbit involvement (P<0.01) between inverted papilloma and malignant transformation of inverted papilloma in the sinonasal region. The ADCs of inverted papilloma were significantly lower than those of malignant transformation of inverted papilloma (P<0.01). There were significant differences in time to peak enhancement (P<0.01), maximum contrast index (P=0.004) and time intensity curve types (P<0.01) between the two entities. Conclusions A multiparametric approach using conventional MR imaging with added ADCs and DCE-MRI parameters had the potential to improve the differentiation between inverted papilloma and malignant transformation of inverted papilloma in the sinonasal region. Key words: Nasal cavity; Sinus; Neoplasms; Multiparametric MR imaging

Prediction of the originating site of sinonasal inverted papilloma by preoperative magnetic resonance imaging and computed tomography.

Precise localization and excision of the originating site of a sinonasal inverted papilloma (SNIP) is essential for decreasing tumor recurrence. In this study we evaluated the use of preoperative computed tomography (CT) and magnetic resonance imaging (MRI) to pinpoint the attachment/originating sites of SNIPs in 143 patients. Osteitis signs in CTs and convoluted cerebriform pattern (CCP)-based reverse tracings from MRIs of 143 SNIP patients were analyzed preoperatively to predict the originating site of SNIPs. The predicted sites were compared with actual SNIP attachment sites determined by surgery, and patients were followed-up for evaluation of SNIP recurrence rates over a mean period of about 4 years. Osteitis signs in CT accurately predicted the actual tumor attachment site in 49.7% of all patients. In comparison, convoluted cerebriform pattern (CCP)-based reverse tracings in MRI and combination CT plus MRI accurately predicted the SNIP originating sites in 84.1% and 86% of the patients, respectively. Sensitivity and specificity in predicting the SNIP originating site were: CT, 54.6% and 69.2%; MRI, 93.1% and 76.9%; and CT+MRI, 94.6% and 92.3%, respectively. A single postoperative recurrence occurred in 4.2% of the patients. Preoperative combination of MRI and CT provides a better option to accurately predict the SNIP originating site, and thus may facilitate accurate and complete excision of the SNIP.

Multiparametric Magnetic Resonance Imaging and Texture Analysis to Distinguish Sinonasal Inverted Papilloma from Squamous Cell Carcinoma

Background: Inverted papilloma (IP) is an uncommon epithelial tumor that occurs in the sinonasal tract. Although benign, it can exhibit aggressive behavior including a propensity for invasion and recurrence. The association of IP with synchronous or metachronous squamous cell carcinoma (SCCA) is well documented, making the differentiation of these tumor types with imaging relevant. A convoluted cerebriform pattern is recognized on magnetic resonance imaging (MRI) as indicative of, but not entirely specific for, IP. Moreover, this represents a subjective finding that suffers from interobserver variability, particularly with smaller tumors.

Differentiation of squamous cell carcinoma and inverted papilloma using non-invasive MR perfusion imaging.

To investigate the diagnostic value of tumour blood flow (TBF) obtained with pseudocontinuous arterial spin labelling for the differentiation of squamous cell carcinoma (SCC) and inverted papilloma (IP) in the nasal or sinonasal cavity. We retrospectively analysed the cases of 33 patients with SCC and 8 patients with IP in the nasal or sinonasal cavity. Pseudocontinuous arterial spin labelling scanning was performed for all patients using a 3.0-T MR unit. Quantitative TBF values were measured by two neuroradiologists by respectively delineating the whole-tumour regions of interest, and the mean of them was determined as TBF value in each patient. Additionally, the presence of imaging findings of convoluted cerebriform pattern (CCP) on MR T2 weighted images was determined in all patients. As a subgroup analysis, patients with IP were divided into aggressive and non-aggressive IPs depending on their progression range. First, an intraclass correlation coefficient (ICC) of TBF values between two neuroradiologists was determined. Next, a statistical comparison of the TBF value by a Mann-Whitney U test between the patients with SCC and IP was performed. Additionally, the comparison by an ANOVA with a post hoc test of Tukey's method among the SCC, non-aggressive IP and aggressive IP groups was also performed. If significance was observed, the diagnostic accuracy to differentiate SCCs from IPs was calculated. Diagnostic accuracy by CCP findings alone and by the combination of CCP findings and TBF were also assessed. The ICC of TBF values between two neuroradiologists was 0.82. The mean TBF values in the patients with SCC, all patients with IP, those with aggressive IP and those with non-aggressive IP were 141.2 ± 33.1, 77.8 ± 31.5, 109.4 ± 16.7 and 58.8 ± 19.9 ml 100 g⁻¹ min⁻¹, respectively. A significant difference was observed between SCC and IP (p < 0.001), SCC and non-aggressive IP (p < 0.01) and non-aggressive IP and aggressive IP (p < 0.01). The diagnostic accuracy values obtained with receiver operating characteristic curve analysis for the differentiation of SCC from IP and for SCC from non-aggressive IP were 0.90 and 0.92, respectively. The diagnostic accuracy was elevated (0.95 from 0.88) by adding the TBF value to CCP findings. The pseudocontinuous arterial spin labelling technique can be a useful non-invasive diagnostic tool to differentiate SCC from IP in nasal or sinonasal cavity.

18F-FDG PET/CT findings of sinonasal inverted papilloma with or without coexistent malignancy: comparison with MR imaging findings in eight patients

Sinonasal inverted papilloma (IP) is known for high rate of associated malignancy. The purpose of this study was to identify (18)F-FDG PET/CT findings of sinonasal IPs. We also tried to compare the PET/CT findings with the MR imaging findings. We retrospectively reviewed PET/CT and MR images of eight patients with sinonasal IP with (n = 6) or without (n = 2) coexistent squamous cell carcinoma (SCC). Particular attention was paid to correlate the PET/CT findings with the MR imaging findings in terms of area distribution of standard uptake values (SUVs) and a convoluted cerebriform pattern (CCP). In two benign IPs, the maximum SUVs measured 8.2 and 7.8, respectively (mean, 8.0). In both tumors, MR images demonstrated a diffuse CCP. In six IPs with coexistent SCC, the maximum SUVs ranged from 13.3 to 31.9 (mean +/- SD, 20.2 +/- 6.6). In these tumors, MR images demonstrated a diffuse CCP in two, a partial CCP in three, and no CCP in one. A wide discrepancy was noted between MR imaging and PET/CT in terms of area distribution of a CCP and SUVs. In sinonasal lesions with MR imaging features of IP, (18)F-FDG PET/CT demonstrating avid FDG uptake does not necessarily imply the presence of coexistent malignancy. In our small series, although IPs containing foci of SCC had consistently higher SUVs than IPs without SCC, the limited literature on this subject suggests that PET cannot be used reliably to make the distinction.

Sinonasal Inverted Papilloma: Value of Convoluted Cerebriform Pattern on MR Imaging

A convoluted cerebriform pattern (CCP) has been reported as a valuable MR imaging feature of inverted papilloma (IP). The purpose of this study was to validate the usefulness of CCP for distinguishing IP from various malignant sinonasal tumors in a relatively large number of patients. We retrospectively reviewed MR images of 30 patients with IP and 128 patients with various malignant sinonasal tumors proved on histologic examination and compared the prevalence of a CCP between the 2 groups. In 8 patients with IP concomitant with squamous cell carcinoma, we also tried to find the MR features to help suggest coexistent malignancy. A CCP was demonstrated in all 30 (100%) of the IPs and 17 (13%) of the 128 malignant sinonasal tumors on MR imaging. There was a significant statistical difference in the prevalence of a CCP between IP and malignant sinonasal tumors with the overall sensitivity, specificity, positive predictive value, negative predictive value, and accuracy 100%, 87%, 64%, 100%, and 89%, respectively. Of 8 IPs concomitant with squamous cell carcinoma, a focal loss of a CCP was demonstrated in 4 tumors, 3 of which also showed aggressive bone destruction with extrasinonasal extension on MR images. Although a CCP is a reliable MR imaging feature of sinonasal IPs, it can also be seen in various malignant sinonasal tumors. A focal loss of a CCP might be a clue to the diagnosis of IPs concomitant with malignancy.

Potentially distinctive features of sinonasal inverted papilloma on MR imaging.

The objective of this study is to describe potentially distinctive MR features of sinonasal inverted papilloma and those of coexisting squamous cell carcinoma. A sinonasal mass with a convoluted cerebriform pattern on T2- or enhanced T1-weighted images suggests inverted papilloma as a histologic diagnosis. Necrosis in a mass with such an appearance strongly suggests coexistent carcinoma.