Preoperative CT-Based Radiomics Combined With Nodule Type to Predict the Micropapillary Pattern in Lung Adenocarcinoma of Size 2 cm or Less: A Multicenter Study

PurposeTo construct an optimal radiomics model for preoperative prediction micropapillary pattern (MPP) in adenocarcinoma (ADC) of size ≤ 2 cm, nodule type was used for stratification to construct two radiomics models based on high-resolution computed tomography (HRCT) images.Materials and MethodsWe retrospectively analyzed patients with pathologically confirmed ADC of size ≤ 2 cm who presented to three hospitals. Patients presenting to the hospital with the greater number of patients were included in the training set (n = 2386) and those presenting to the other two hospitals were included in the external validation set (n = 119). HRCT images were used for delineation of region of interest of tumor and extraction of radiomics features; dimensionality reduction was performed for the features. Nodule type was used to stratify the data and the random forest method was used to construct two models for preoperative prediction MPP in ADC of size ≤ 2 cm. Model 1 included all nodule types and model 2 included only solid nodules. The receiver operating characteristic curve was used to assess the prediction performance of the two models and independent validation was used to assess its generalizability.ResultsBoth models predicted ADC with MPP preoperatively. The area under the curve (AUC) of prediction performance of models 1 and 2 were 0.91 and 0.78, respectively. The prediction performance of model 2 was lower than that of model 1. The AUCs in the external validation set were 0.81 and 0.72, respectively. The DeLong test showed statistically significant differences between the training and validation sets in model 1 (p = 0.0296) with weak generalizability. There was no statistically significant difference between the training and validation sets in model 2 (p = 0.2865) with some generalizability.ConclusionNodule type is an important factor that affects the performance of radiomics predictor model for MPP with ADC of size ≤ 2 cm. The radiomics prediction model constructed based on solid nodules alone, can be used to evaluate MPP and may contribute to proper surgical planning in patients with ADC of size ≤ 2 cm.

Pure Mucinous Breast Carcinoma with Micropapillary Pattern in a 32-Year-Old Female

Background: Mucinous carcinoma (MC) is a rare breast malignancy with a large extracellular mucin secretion. It has a good prognosis in comparison to other breast malignancies. Case presentation: We report a 32 years old female with multiple hard palpable masses in the left breast with rapid growth in 6 months. She was mentally retarded with lower limb varicose veins associated with mucocutaneous lesions on the face. She underwent ultrasound examination of the breast, thyroid and lower extremity veins. Core needle biopsy and fine needle aspiration from left breast lesions and right thyroid nodules showed MC and follicular lesion with hurtle cell change, respectively. Suspected metastasis in the left rib and calvarium in the subsequent bone scan survey and brain magnetic resonance imaging was reported. She underwent radical mastectomy and right hemi-thyroidectomy. Conclusion: Pure mucinous carcinoma with micropapillary pattern (MUMPC) is a new histology variant of Pure Mucinous Carcinoma (PMC) that shows favorable prognosis with less aggression and occurs in older patients. However, PMC in our patient occurred at a young age with greater aggression.

Sonographic Features of Pure Mucinous Brelast Carcinoma With Micropapillary Pattern

ObjectivePrevious studies have mostly discussed the clinical manifestations and prognosis of mucinous breast carcinoma with a micropapillary pattern. The purposes of this study were to investigate the sonographic features of pure mucinous breast carcinoma with micropapillary pattern (MUMPC) and to identify the role of ultrasound in the differential diagnosis between MUMPC and conventional pure mucinous breast carcinoma (cPMBC).Materials and MethodsWe obtained written informed consent from all patients, and the Ethics Committee of West China Hospital approved this retrospective study. The study was conducted between May and August 2020. We enrolled 133 patients with 133 breast lesions confirmed as mucinous breast carcinoma (MBC) histopathologically between January 2014 and January 2020.We retrospectively assessed sonographic features (margin, shape, internal echogenicity, calcification, posterior acoustic feature, invasive growth, blood flow grade, and rate of missed diagnosis) and clinical characteristics (age, tumor size, tumor texture, initial symptom, and lymph node metastasis). Bivariable analyses were performed using SPSS version 19.0.ResultsThe 133 lesions included 11 MUMPCs, 65 cPMBCs, and 57 mixed MBCs (MMBCs). There were significant differences in margin, shape, calcification, posterior acoustic feature, invasive growth, rate of missed diagnosis, average tumor size, and lymph node metastasis among the three groups (p < 0.05). The subsequent pairwise comparisons showed that there were significant differences in lymph node metastasis, margin, and invasive growth between MUMPC and cPMBC (p < 0.05). In patients aged >45 years, there was a significant difference in tumor size among the three groups (p = 0.045), and paired comparison showed that the average tumor size in the cPMBC group was larger than that in the MMBC group (p = 0.014).ConclusionMUMPC showed a non-circumscribed margin and invasive growth more frequently than cPMBC did. Lymphatic metastasis was more likely to occur in MUMPC than cPMBC. Ultrasound is helpful to distinguish MUMPC from cPMBC.

Enhanced CT-Based Radiomics to Predict Micropapillary Pattern Within Lung Invasive Adenocarcinoma

ObjectiveWe aimed to investigate whether enhanced CT-based radiomics can predict micropapillary pattern (MPP) of lung invasive adenocarcinoma (IAC) in the pre-op phase and to develop an individual diagnostic predictive model for MPP in IAC.Methods170 patients who underwent complete resection for pathologically confirmed lung IAC were included in our study. Of these 121 were used as a training cohort and the other 49 as a test cohort. Clinical features and enhanced CT images were collected and assessed. Quantitative CT analysis was performed based on feature types including first order, shape, gray-level co-occurrence matrix-based, gray-level size zone matrix-based, gray-level run length matrix-based, gray-level dependence matrix-based, neighboring gray tone difference matrix-based features and transform types including Log, wavelet and local binary pattern. Receiver operating characteristic (ROC) and area under the curve (AUC) were used to value the ability to identify the lung IAC with MPP using these characteristics.ResultsUsing quantitative CT analysis, one thousand three hundred and seventeen radiomics features were deciphered from R (https://www.r-project.org/). Then these radiomic features were decreased to 14 features after dimension reduction using the least absolute shrinkage and selection operator (LASSO) method in R. After correlation analysis, 5 key features were obtained and used as signatures for predicting MPP within IAC. The individualized prediction model which included age, smoking, family tumor history and radiomics signature had better identification (AUC=0.739) in comparison with the model consisting only of radiomics features (AUC=0.722). DeLong test showed that the difference in AUC between the two models was statistically significant (P<0.01). Compared with the simple radiomics model, the more comprehensive individual prediction model has better prediction performance.ConclusionThe use of radiomics approach is of great value in the diagnosis of tumors by non-invasive means. The individualized prediction model in the study, when incorporated with age, smoking and radiomics signature, had effective predictive performance of lung IAC with MPP lesions. The combination of imaging features and clinical features can provide additional diagnostic value to identify the micropapillary pattern in IAC and can affect clinical diagnosis and treatment.

The Prognostic Value of Non-Predominant Micropapillary Pattern in a Large Cohort of Resected Invasive Lung Adenocarcinoma Measuring ≤3 cm

The aim of this study was to analyze the influence of non-predominant micropapillary pattern in small sized invasive lung adenocarcinoma. A total of 986 lung adenocarcinoma patients with tumor size ≤3 cm were identified and classified according to the IALSC/ATS/ERS classification. Emphasis was placed on the impact of non-predominant micropapillary pattern on disease-free survival (DFS) and overall survival (OS). The relationship between lung adenocarcinoma subtype and lymph node involvement, EGFR mutation and KRAS mutation was also evaluated. A nomogram was developed to predict the probability of 3- and 5-year OS for these patients. The concordance index and calibration plot were used to validate this model. Among all 986 patients, the percentages of lymph node involvement were: 58.1, 50.0, 33.5, 21.4, 21.1, 10.9, 0, and 0% for micropapillary predominant, solid predominant, acinar predominant, papillary predominant, invasive mucinous adenocarcinoma (IMA), lepidic predominant, minimally invasive adenocarcinoma (MIA), adenocarcinoma in situ (AIS), respectively. The frequency of EGFR mutation in the cases of lepidic predominant, acinar predominant, MIA, micropapillary predominant, papillary predominant, solid predominant, IMA, and AIS were 51.1, 45.2, 44.4, 36.8, 29.3, 26.8, 8.3, and 0%, respectively. A non-predominant micropapillary pattern was observed in 344 (38.4%) invasive adenocarcinoma (IAC), and its presence predicted a poorer DFS (median: 56.0 months vs. 66.0 months, P <0.001) and OS (median: 61.0 months vs. 70.0 months, P <0.001). After propensity score matching, non-predominant micropapillary pattern retained its unfavorable effect on DFS (P = 0.007) and OS (P = 0.001). Multivariate analysis showed that non-predominant micropapillary pattern was identified as an independent prognostic factor for DFS (P = 0.003) and OS (P <0.001) in IAC. The nomogram showed good calibration and reliable discrimination ability (C-index = 0.775) to evaluated the 3- and 5-year OS. This retrospective analysis of patients with small sized IAC suggests the value of non-predominant micropapillary pattern to predict poor prognosis. A reliable nomogram model was constructed to provide personalized survival predictions.

Mucinous Carcinoma of the breast with micropapillary pattern and psammomatous calcification: A case study.

Mucinous carcinoma with a micropapillary pattern is an unusual form of Invasive breast cancer exhibiting dual mucinous and micropapillary differentiation. The present case is of a 47-year-old nulliparous female who presented with an incidental finding of a hard lump in her left breast. Mammography revealed a BIRADS 4 lesion. Modified radical mastectomy was done and the specimen was grossed, revealing a tumor of 3x2.6x2.6 cm in the outer quadrant. Microscopy revealed the tumor having extracellular mucin pools with floating psammoma bodies and focal micropapillary pattern. Four of the twenty-six lymph nodes sampled were found to have tumor deposits. The micropapillary pattern was maintained in the metastatic deposits. Immunohistochemistry revealed ER and PR positivity and Her2Neu negativity. EMA corroborated the findings. It is important to recognize the micropapillary pattern in mucinous carcinomas of the breast as these tumors tend to be more aggressive than pure mucinous breast lesions.

Micropapillary pattern of stage IIIA-N2 lung adenocarcinoma is a prognostic factor after adjuvant chemoradiotherapy

Aim: This study aims to investigate the significance of a micropapillary pattern in stage IIIA-N2 lung adenocarcinoma after adjuvant chemoradiotherapy. Patients & methods: A total of 257 patients with stage IIIA-N2 lung adenocarcinoma were enrolled in this study. Patients were classified into three groups based on the proportion of micropapillary components: micropapillary negative, micropapillary minor component and micropapillary predominant component. Results: The micropapillary predominant group had the shortest median disease-free survival and overall survival times compared with the micropapillary minor component and micropapillary negative groups (median overall survival time: 54 months vs 64 months vs not reached; p = 0.004). Furthermore, the micropapillary pattern was an independent prognostic factor for disease-free survival and overall survival (p < 0.05). Conclusion: The micropapillary pattern of IIIA-N2 lung adenocarcinoma is related to worse prognosis.