Phyllodes Tumors-The Predictors and Detection of Recurrence

Prognostic value of Ki67 in phyllodes tumor of the breast: A systematic review and meta‑analysis

Numerous clinicopathological features have been examined as predictive factors for adverse outcomes in patients with phyllodes tumor (PT) of the breast, but there are still no definitive predictive markers to guide management, despite the persistent risk of recurrence, even in benign disease. Whether Ki67 has prognostic value in PT remains uncertain. Therefore, a systematic review and meta-analysis were performed to examine whether Ki67 is associated with adverse clinical outcomes, particularly recurrence, in patients with PT. The PubMed/MEDLINE, Web of Science, Scopus, Embase and Cochrane Library databases were searched from inception to July 2024. Study characteristics and outcomes (recurrence and overall survival) according to Ki67 status were extracted from each eligible study, and pooled log odds ratios (OR) with 95% CI were derived using a random-effects model. A total of five studies comprising 280 cases were eligible for inclusion. The adverse outcome rate for the Ki67high (Ki67 >10 or >11.2%) population was 28.7% (95% CI, 20.1-38.6%), while the adverse outcome rate for the Ki67low population was 9.4% (95% CI, 5.4-13.5%). Ki67high was associated with an increased odds of an adverse outcome [log OR, 1.26 (95% CI, 0.38-2.15; P=0.005)] compared with a Ki67low status. All five studies scored 8 points on the Newcastle-Ottawa Scale, equivalent to 'good' quality according to Agency for Healthcare Research and Quality standards, and no significant publication bias was noted. This was the first meta-analysis of the predictive value of Ki67 in PT of the breast. A relatively high Ki67 index (>10%) is associated with recurrence. It is timely to re-evaluate the prognostic value of Ki67 in large retrospective cohorts with long follow-up to firmly establish whether it could contribute to identifying patients at risk of recurrence, particularly those with histologically benign disease. Doing so could impact clinical practice by refining follow-up recommendations based on quality evidence.

Deep learning-assisted distinguishing breast phyllodes tumours from fibroadenomas based on ultrasound images: a diagnostic study

OBJECTIVES

To evaluate the performance of ultrasound-based deep learning (DL) models in distinguishing breast phyllodes tumours (PTs) from fibroadenomas (FAs) and their clinical utility in assisting radiologists with varying diagnostic experiences.

METHODS

We retrospectively collected 1180 ultrasound images from 539 patients (247 PTs and 292 FAs). Five DL network models with different structures were trained and validated using nodule regions annotated by radiologists on breast ultrasound images. DL models were trained using the methods of transfer learning and 3-fold cross-validation. The model demonstrated the best evaluation index in the 3-fold cross-validation was selected for comparison with radiologists' diagnostic decisions. Two-round reader studies were conducted to investigate the value of DL model in assisting 6 radiologists with different levels of experience.

RESULTS

Upon testing, Xception model demonstrated the best diagnostic performance (area under the receiver-operating characteristic curve: 0.87; 95% CI, 0.81-0.92), outperforming all radiologists (all P < .05). Additionally, the DL model enhanced the diagnostic performance of radiologists. Accuracy demonstrated improvements of 4%, 4%, and 3% for senior, intermediate, and junior radiologists, respectively.

CONCLUSIONS

The DL models showed superior predictive abilities compared to experienced radiologists in distinguishing breast PTs from FAs. Utilizing the model led to improved efficiency and diagnostic performance for radiologists with different levels of experience (6-25 years of work).

ADVANCES IN KNOWLEDGE

We developed and validated a DL model based on the largest available dataset to assist in diagnosing PTs. This model has the potential to allow radiologists to discriminate 2 types of breast tumours which are challenging to identify with precision and accuracy, and subsequently to make more informed decisions about surgical plans.

Postoperative surgical margin results of the phyllodes tumors from a tertiary hospital

OBJECTIVE

Phyllodes tumors in the breast are exceptionally uncommon fibroepithelial tumors. In the literature, they are typically categorized as benign phyllodes tumor, borderline phyllodes tumor, and malignant phyllodes tumor. This study aims to assess and present the clinical and surgical outcomes of patients diagnosed with phyllodes tumor.

METHODS

The outcomes of patients aged 18 years and above diagnosed with phyllodes tumor between 2006 and 2023 were retrospectively reviewed. Patients were grouped as benign phyllodes tumor and borderline/malignant phyllodes tumor and compared by clinical and surgical results.

RESULTS

Of all 57 patients with phyllodes tumor, 64.9% (n=37) were benign phyllodes tumor and 35.1% (n=20) were borderline/malignant phyllodes tumor [22.8% (n=13) borderline phyllodes tumor and 12.3% (n=7) malignant phyllodes tumor]. When the patients were divided into two groups as benign phyllodes tumor and borderline/malignant phyllodes tumor and compared, our cumulative (total) recurrence rate was 14.0%, with final surgical margin width between groups [(0

CONCLUSION

Phyllodes tumors of the breast can be followed up with a narrow negative surgical margin (0 mm Collapse

Key Words

• breast
• phyllodes tumor
• neoplasm
• recurrence

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MESH Headings

• Humans
• Phyllodes Tumor/surgery
• Phyllodes Tumor/pathology
• Female
• Margins of Excision
• Breast Neoplasms/surgery
• Breast Neoplasms/pathology
• Adult
• Retrospective Studies
• Middle Aged
• Tertiary Care Centers
• Neoplasm Recurrence, Local/pathology
• Young Adult
• Treatment Outcome
• Postoperative Period
• Mastectomy/methods
• Aged
• Adolescent

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Affiliation(s)

Fatih Dal University of Health Sciences, Turkish Ministry of Health, İstanbul Training and Research Hospital, Department of General Surgery – İstanbul, Turkey
Semiha Battal Havare University of Health Sciences, Turkish Ministry of Health, İstanbul Training and Research Hospital, Department of Medical Pathology – İstanbul, Turkey

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Predicting Prognosis of Phyllodes Tumors Using a Mammography- and Magnetic Resonance Imaging-Based Radiomics Model: A Preliminary Study

PURPOSE

To investigate whether a radiomics model based on mammography (MG) and magnetic resonance imaging (MRI) can be used to predict disease-free survival (DFS) after phyllodes tumor (PT) surgery.

METHOD

About 131 PT patients who underwent MG and MRI before surgery between January 2010 and December 2020 were retrospectively enrolled, including 15 patients with recurrence and metastasis and 116 without recurrence. 884 and 3138 radiomic features were extracted from MG and MR images, respectively. Then, multiple radiomics models were established to predict the recurrence risk of the patients by applying a support vector machine classifier. The area under the ROC curve (AUC) was calculated to evaluate model performance. After dividing the patients into high- and low-risk groups based on the predicted radiomics scores, survival analysis was conducted to compare differences between the groups.

RESULTS

In total, 3 MG-related and 5 MRI-related radiomic models were established; the prediction performance of the T1WI feature fusion model was the best, with an AUC value of 0.93. After combining the features of MG and MRI, the AUC increased to 0.95. Furthermore, the MG, MRI and all-image radiomic models had statistically significant differences in survival between the high- and low-risk groups (P < .001). All-image radiomics model showed higher survival performance than the MG and MRI radiomics models alone.

CONCLUSIONS

Radiomics features based on preoperative MG and MR images can predict DFS after PT surgery, and the prediction score of the image radiomics model can be used as a potential indicator of recurrence risk.

Fibroepithelial Neoplasm with Hybrid Features of Benign Phyllodes Tumor, Juvenile Papillomatosis, and Juvenile Fibroadenoma: A Case Report

Phyllodes tumor is an uncommon breast fibroepithelial neoplasm mainly found in middle-aged patients, presenting a morphologic continuum from benign to malignant. Juvenile papillomatosis represents a rare benign proliferative breast tumor primarily affecting young individuals and carries a potential elevated risk of subsequent breast cancer development. Juvenile fibroadenoma is a well-circumscribed biphasic neoplasm that often occurs in adolescent girls, characterized by a pericanalicular growth pattern with usual-type epithelial hyperplasia and gynaecomastia-like micropapillary proliferation. Herein, we present an unusual example of a 26-year-old woman with a left breast outer lower quadrant palpable mass. Ultrasonography identified a 5.9 cm lobulated hypoechoic solid mass with scattered small cysts. The preoperative biopsy initially diagnosed a fibroepithelial lesion, considering giant cellular fibroadenoma and phyllodes tumor in the differential. Subsequent complete excision revealed areas of benign phyllodes tumor features closely admixed with distinctive elements such as prominent multiple cysts exhibiting apocrine and papillary apocrine metaplasia, duct papillomatosis, and duct stasis characteristic of juvenile papillomatosis, and hyperplastic ductal epithelium with micropapillary projections demonstrating a pericanalicular growth pattern indicative of juvenile fibroadenoma. The diagnosis was conclusively established as a fibroepithelial lesion with combined features of benign phyllodes tumor, juvenile papillomatosis, and juvenile fibroadenoma. Further investigation uncovered a family history of breast cancer. Molecular analysis revealed a pattern of unique and overlapping mutations within these distinct histopathological areas. This unusual presentation with hybrid features within a single tumor is described for the first time in the literature along with the molecular signature of the individual components.

Nipple-sparing mastectomy and immediate breast reconstruction by prepectoral implant for the management of giant phyllodes tumors: A case series

Phyllodes tumor is an uncommon breast neoplasm that is present in variable sizes. Giant phyllodes are those larger than 10 cm in diameter. Clinically, giant phyllodes tumors present as a visible, rapidly growing mass distorting the breast contour. Such tumors with large size and rapid growth rate suggest a phyllode diagnosis of fibroadenoma. Planning a standard treatment strategy for these tumors is quite challenging. While adequate surgical excision with tumor-free resection margins is the standard of care for most giant phyllodes cases, borderline and malignant giant phyllodes tumors might require wider resections given their high recurrence rates. Some authors described total mastectomy as the treatment option for giant borderline and malignant phyllodes to obtain wide, clear margins. Between March 2022 and September 2023, our surgical oncology department presented and operated on three cases of giant phyllodes. They underwent a nipple-sparing mastectomy and immediate breast reconstruction using pre-pectoral silicone implants. We think that with such a procedure, we can benefit from the wide, safe margins of mastectomy that have been proven to decrease local recurrence rates while considering the aesthetic outcome.

Metastatic and Malignant Phyllodes Tumors of the Breast: An Update for Current Management

Metastatic, malignant phyllodes tumor (PT) of the breast is a rare and aggressive neoplasm. Currently, there is no agreed upon consensus as to best management practices. A systematic review of literature was conducted investigating surgical, chemotherapeutic, and radiotherapeutic management for metastatic PT. Databases employed to identify articles included Embase, PubMed, and SAGE Journals. Diagnosis of metastatic PT has been of significant difficulty to radiologists as it is often confused with fibroadenomas. Surgically, metastatectomy has been correlated with increased overall survival (of 25.9 versus 9.9 months; P = .01). Radiotherapy has often been associated with palliation and pain control in metastatic, malignant neoplasia. However, one study showed that in malignant PT, radiation was associated with significantly lower rates of local recurrence (OR: 0.048 versus 0.209). Anthracycline containing chemotherapy regimens has been associated with improved overall survival (22.4 months versus 13.2 months; P = .040). Further research must be conducted into this rare malignancy to elucidate accurate diagnosis and care for patients with advanced metastatic or malignant phyllodes tumors.

The phyllodes menace-Variation in course, therapy, and appearance of phyllodes tumors in a case series of three patients

Key Clinical Message

Early and complete surgical resection is the most important therapeutic and diagnostic measure. Adjuvant radiation is suggested for malign phyllode tumors, phyllode tumors larger than 10 cm or those with a low distance to the resection margins.

Abstract

Phyllodes tumors are rare fibroepithelial tumors of the breast. Histologically, they are usually classified as benign, borderline or malignant, though these classifications do not necessarily reflect the clinical course of the disease. These tumors may stay undetected for years, or show sudden and rapid progression. There is currently no consistent therapy recommendation based upon histological findings, the localization of the tumor and/or whether it is recurrent. Using the examples of three patients, we show how courses and therapy may differ widely, and discuss this in the context of the current state of the literature.

Machine Learning-Based Ultrasound Texture Analysis in Differentiation of Benign Phyllodes Tumors from Borderline-Malignant Phyllodes Tumors

PURPOSE

 Phyllodes tumors (PTs) are uncommon fibroepithelial breast lesions that are classified as three different forms as benign phyllodes tumor (BPT), borderline phyllodes tumor (BoPT), and malignant phyllodes tumor (MPT). Conventional radiologic methods make only a limited contribution to exact diagnosis, and texture analysis data increase the diagnostic performance. In this study, we aimed to evaluate the contribution of texture analysis of US images (TAUI) of PTs in order to discriminate between BPTs and BoPTs-MPTs.

METHODS

 The number of patients was 63 (41 BPTs, 12 BoPTs, and 10 MPTs). Patients were divided into two groups (Group 1-BPT, Group 2-BoPT/MPT). TAUI with LIFEx software was performed retrospectively. An independent machine learning approach, MATLAB R2020a (Math- Works, Natick, Massachusetts) was used with the dataset with p < 0.004. Two machine learning approaches were used to build prediction models for differentiating between Group 1 and Group 2. Receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic performance of statistically significant texture data between phyllodes subgroups.

RESULTS

 In TAUI, 10 statistically significant second order texture values were identified as significant factors capable of differentiating among the two groups (p < 0.05). Both of the models of our dataset make a diagnostic contribution to the discrimination between BopTs-MPTs and BPTs.

CONCLUSION

 In PTs, US is the main diagnostic method. Adding machine learning-based TAUI to conventional US findings can provide optimal diagnosis, thereby helping to choose the correct surgical method. Consequently, decreased local recurrence rates can be achieved.

Pretreatment Multiparametric MRI-Based Radiomics Analysis for the Diagnosis of Breast Phyllodes Tumors

BACKGROUND

Preoperative pathological grading assessment is important for patients with breast phyllodes tumors (PTs).

PURPOSE

To develop and validate a clinical-radiomics model based on multiparametric MRI and clinical information for the pretreatment differential diagnosis of PTs.

STUDY TYPE

Retrospective.

POPULATION

A total of 216 patients with PTs, 133 in the training cohort (55 benign PTs [BPTs] and 78 borderline/malignant PTs [BMPTs]) and 83 in the validation cohort (28 BPTs and 55 BMPTs).

FIELD STRENGTH/SEQUENCE

1.5 T and 3 T; T2-weighted imaging (T2WI), precontrast T1-weighted imaging (T1WI) and dynamic contrast-enhanced T1-weighted imaging (DCE-T1WI).

ASSESSMENT

A total of 3138 radiomics features were computed to decode the imaging phenotypes of PTs. To build the classification models, the following workflow was followed: minimum-maximum scaling normalization method, recursive feature elimination based on ridge regression (Ridge-RFE), synthetic minority oversampling technique, and support vector machine classifier. We established several models based on the statistically significant features (Ridge-RFE selected) of each sequence to distinguish BPTs from BMPTs, including precontrast T1WI model, DCE-T1WI phase 1 model, T1WI feature fusion model, T2WI model, T1WI + T2WI model, clinical feature model, conventional MRI characteristics model, and combined clinical-radiomics model.

STATISTICAL TESTS

Univariate analysis was utilized to compare variables between the BPT and BMPT groups. The receiver operating characteristic curve (ROC) analysis was used to evaluate the diagnostic performance of these models.

RESULTS

In the training cohort, the clinical-radiomics model had excellent diagnostic efficiency, with an area under ROC (AUC) of 0.91 ± 0.02 (95% CI: 0.87-0.94). In the validation cohort, the AUCs were 0.79 ± 0.05 (95% CI: 0.70-0.87) for the combined model and 0.77 ± 0.05 (95% CI: 0.67-0.85) for the radiomics model.

DATA CONCLUSION

Compared with conventional MRI characteristics, radiomics features extracted from multiparametric MRI are helpful for improving the accuracy of differentiating the pathological grades of PTs preoperatively. The model based on radiomics and clinical information is expected to become a potential noninvasive tool for the assessment of PTs grades.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

Case report: Osteosarcomatous differentiation in the lung metastasis of a malignant phyllodes tumor

Malignant phyllodes tumor is a rare breast tumor, with distant metastases and heterologous differentiation in a few cases. We report a case of malignant phyllodes tumor with liposarcomatous differentiation in the primary tumor and osteosarcomatous differentiation in the lung metastatic tumor. A middle-aged female presented with a well-defined mass in the upper lobe of the right lung measuring 5.0 × 5.0 × 3.0 cm. The patient had a history of malignant phyllodes tumor in the breast. The patient underwent a right superior lobectomy. Histologically, the primary tumor was a typical malignant phyllodes tumor with pleomorphic liposarcomatous differentiation, while the lung metastasis showed osteosarcomatous differentiation without original biphasic features. The phyllodes tumor and heterologous components showed CD10 and p53 expression, and were negative for ER, PR, and CD34. Exome sequencing revealed TP53, TERT, EGFR, RARA, RB1, and GNAS mutations in all three components. Although the lung metastasis were morphologically different from the primary breast tumor, their common origin was demonstrated through immunohistochemical and molecular characterization. Cancer stem cells give rise to tumor heterogeneous cells, and heterologous components in malignant phyllodes tumors may indicate unfavorable prognosis and a greater risk of early recurrence and metastasis.

Transformation of a Benign-Appearing Fibroepithelial Lesion to a Giant Malignant Phyllodes Tumor of the Breast

This is a case of a woman who presented with a left breast mass that was initially diagnosed as fibroadenoma on core biopsy and, after three years without any surgical intervention, was found to be a malignant phyllodes tumor. Initially, a core needle biopsy of the mass showed probable fibroadenoma. Because of the initial benign seeming diagnosis and the need to treat her tongue cancer, the patient did not recognize the need for a recommended surgical consultation and excision. Three years later, she presented after the mass had enlarged to encompass nearly the whole left breast. Core needle biopsy revealed spindle cell proliferation with scattered benign-looking tubules. Due to the large size of the mass, she underwent a total mastectomy, and the final pathology demonstrated a malignant phyllodes tumor. This case demonstrates a case of progression of a benign-appearing fibroepithelial lesion to a malignant phyllodes tumor three years later.

Management of phyllodes tumor: A systematic review and meta-analysis of real-world evidence

BACKGROUND

Phyllodes tumor is rare but has a high recurrence rate. Treatment modalities and clinicopathological prognostic factors for recurrence remain unclear. The synthesis of real-world data can enable the integration of sufficient evidence on optimal treatment for this population.

METHODS

We searched PubMed, Embase, and Cochrane Library databases for studies focusing on the management of phyllodes tumor including the surgical margin, different clinicopathological prognostic factors, and postoperative adjuvant radiotherapy versus no radiotherapy.

RESULTS

Fifty-two studies were retrieved. The pooled estimated recurrence rates of benign, borderline, and malignant tumors were 7.1%, 16.7%, and 25.1%, respectively. Surgical margins of 1 mm (odds ratio [OR]: 0.4, 95% confidence interval [CI]: 0.27-0.61) and 1 cm (OR: 0.45, 95% CI: 0.15-0.85) resulted in significantly higher recurrence rates. Postoperative adjuvant radiotherapy significantly reduced the recurrence rate of malignant tumors relative to no radiotherapy (P = 0.034) but did not significantly reduce the recurrence rates of overall and borderline tumors. Regarding clinicopathological features, moderate or severe stromal atypia and hypercellularity, stromal overgrowth, mitotic number of 5, tumor necrosis, tumor border, and margin status were determined as independent prognostic factors for recurrence, except a tumor size of 5 cm.

CONCLUSION

The ideal surgical margin for phyllodes tumor incision should be at least 1 cm in width. Adjuvant radiotherapy reduced the recurrence of malignant tumor. By identifying patients with poor clinicopathological risk factors, surgeons may reduce the recurrence rate of phyllodes tumor.

The Predictive Value of Magnetic Resonance Imaging-based Texture Analysis in Evaluating Histopathological Grades of Breast Phyllodes Tumor

PURPOSE

Knowing the distinction between benign and borderline/malignant phyllodes tumors (PTs) can help in the surgical treatment course. Herein, we investigated the value of magnetic resonance imaging-based texture analysis (MRI-TA) in differentiating between benign and borderline/malignant PTs.

METHODS

Forty-three women with 44 histologically proven PTs underwent breast MRI before surgery and were classified into benign (n = 26) and borderline/malignant groups (n = 18 [15 borderline, 3 malignant]). Clinical and routine MRI parameters (CRMP) and MRI-TA were used to distinguish benign from borderline/malignant PT. In total, 298 texture parameters were extracted from fat-suppression (FS) T2-weighted, FS unenhanced T1-weighted, and FS first-enhanced T1-weighted sequences. To evaluate the diagnostic performance, receiver operating characteristic curve analysis was performed for the K-nearest neighbor classifier trained with significantly different parameters of CRMP, MRI sequence-based TA, and the combination strategy.

RESULTS

Compared with benign PTs, borderline/malignant ones presented a higher local recurrence (p = 0.045); larger size (p < 0.001); different time-intensity curve pattern (p = 0.010); and higher frequency of strong lobulation (p = 0.024), septation enhancement (p = 0.048), cystic component (p = 0.023), and irregular cystic wall (p = 0.045). TA of FS T2-weighted images (0.86) showed a significantly higher area under the curve (AUC) than that of FS unenhanced T1-weighted (0.65, p = 0.010) or first-enhanced phase (0.72, p = 0.049) images. The texture parameters of FS T2-weighted sequences tended to have a higher AUC than CRMP (0.79, p = 0.404). Additionally, the combination strategy exhibited a similar AUC (0.89, p = 0.622) in comparison with the texture parameters of FS T2-weighted sequences.

CONCLUSION

MRI-TA demonstrated good predictive performance for breast PT pathological grading and could provide surgical planning guidance. Clinical data and routine MRI features were also valuable for grading PTs.

Surgical management in phyllodes tumors of the breast: a systematic review and meta-analysis

BACKGROUND

Information is still controversial in the studies regarding the current optimal surgical management of phyllodes tumors (PTs) of the breast. Local recurrence (LR) may occur with an upgraded in the pathological grade, influencing the prognosis of patients with PT. This systematic review and meta-analysis aimed to investigate the association of LR risk with margin status and margin width which could have significant implications on the surgical management of PT.

METHODS

Independent and comprehensive searches were performed by two authors through five databases including PubMed, Medline, Embase, ScienceDirect and Cochrane Library from January 1990 to October 2021. Studies investigating the association between margin width, margin status and LR rates were considered for inclusion. Study quality was evaluated using the Newcastle-Ottawa Scale (NOS). Meta-analysis was performed using RevMan5.3 software, and statistical heterogeneity was assessed using the Chi-square test and quantified using the I2 statistic. Visual inspection of funnel plots was used to judge publication bias.

RESULTS

A total of 34 articles were included in this article, all of which with NOS scores above 5. Regardless of the PT grade, positive margin significantly increased the risk of LR [odds ratio (OR) 3.64, 95% confidence interval (CI): 2.60-5.12]. No significant difference was found in the risk of LR between the margins <1 and ≥1 cm (OR 1.39, 95% CI: 0.67-2.92). For benign and borderline PTs, there were no significant differences of the LR risk between breast-conserving surgery (BCS) and mastectomy (benign OR 0.68, 95% CI: 0.12-3.78; borderline OR 1.14, 95% CI: 0.29-4.51). While the LR risk was significantly increased by BCS for malignant PT (OR 2.77, 95% CI: 1.33-5.74).

DISCUSSION

Different surgical management strategies should be considered for different PT grades. BCS was a feasible option and margins <1 cm was not significantly associated with LR risk for all grade of PT. After BCS, benign PT with positive margin could adopt the "wait and watch" strategy with regular follow-up, while borderline and malignant PTs were expected to underwent re-excision to ensure negative margins. More studies are still needed to clarify and update the existing conclusions and improve the prognosis of PT patients.

Predicting the pathological grade of breast phyllodes tumors: a nomogram based on clinical and magnetic resonance imaging features

OBJECTIVE

To explore the potential factors related to the pathological grade of breast phyllodes tumors (PTs) and to establish a nomogram to improve their differentiation ability.

METHODS

Patients with PTs diagnosed by post-operative pathology who underwent pretreatment magnetic resonance imaging (MRI) from January 2015 to June 2020 were retrospectively reviewed. Traditional clinical features and MRI features evaluated according to the fifth BI-RADS were analyzed by statistical methods and introduced to a stepwise multivariate logistic regression analysis to develop a prediction model. Then, a nomogram was developed to graphically predict the probability of non-benign (borderline/malignant) PTs.

RESULTS

Finally, 61 benign, 73 borderline and 48 malignant PTs were identified in 182 patients. Family history of tumor, diameter, lobulation, cystic component, signal on fat saturated T₂ weighted imaging (FS T₂WI), BI-RADS category and time-signal intensity curve (TIC) patterns were found to be significantly different between benign and non-benign PTs. The nomogram was finally developed based on five risk factors: family history of tumor, lobulation, cystic component, signal on FS T₂WI and internal enhancement. The AUC of the nomogram was 0.795 (95% CI: 0.639, 0.835).

CONCLUSION

Family history of tumor, lobulation, cystic components, signals on FS T₂WI and internal enhancement are independent predictors of non-benign PTs. The prediction nomogram developed based on these features can be used as a supplemental tool to pre-operatively differentiate PTs grades.

ADVANCES IN KNOWLEDGE

More sample size and characteristics were used to explore the factors related to the pathological grade of PTs and establish a predictive nomogram for the first time.