Non-mass lesions detected by breast US: stratification of cancer risk for clinical management.

OBJECTIVE: To develop a classification system using imaging features to interpret breast non-mass lesions (NMLs) detected on US and to stratify their cancer risk. METHODS: This retrospective study included 715 patients with 715 breast NMLs detected on breast US from 2012 to 2016. Each patient underwent mammography at the time of diagnosis. Radiologists assessed US and mammographic features and final BI-RADS categories. Multivariable logistic regression was used to find imaging features associated with malignancy in a development dataset (n = 460). A system to classify BI-RADS categories (3 to 5) was developed based on the odds ratios (ORs) of imaging features significantly associated with malignancy and validated in a distinct validation dataset (n = 255). RESULTS: Among 715 NMLs, 385 (53.8%) were benign and 330 (46.2%) were malignant. In the development dataset, the following B-mode US features were associated with malignancy (all p < 0.001): segmental distribution (OR = 3.03; 95% confidence interval [CI], 1.50-6.15), associated calcifications (OR = 4.26; 95% CI, 1.62-11.18), abnormal ductal change (OR = 4.91; 95% CI, 2.07-11.68), and posterior shadowing (OR = 20.20; 95% CI, 6.46-63.23). The following mammographic features were also associated with malignancy (all p < 0.001): calcifications (OR = 7.98; 95% CI, 3.06-20.81) and focal asymmetry (OR = 4.75; 95% CI, 1.90-11.88). In the validation dataset, our classification system using US and mammography showed a higher area under the curve (0.951-0.956) compared to when it was not applied (0.908-0911) to predict malignancy with BI-RADS categories (p < 0.05). CONCLUSION: Our classification system which incorporates US and mammographic features of breast NMLs can help interpret and manage all NMLs detected on breast US by stratifying cancer risk according to BI-RADS categories. KEY POINTS: • When diagnosing breast NMLs detected on US, suspicious US features are segmental distribution, associated abnormal ductal change, calcifications, and posterior shadowing within or around the NML on B-mode US, while a probably benign US feature is the presence of multiple small cysts. • Corresponding suspicious mammographic features of breast NMLs detected on US are associated calcifications and focal asymmetry. • Our classification system which incorporates US features with and without mammography can potentially be used to interpret and manage any NMLs detected on breast US in clinical practice.

Spread through air spaces (STAS) in invasive mucinous adenocarcinoma of the lung: Incidence, prognostic impact, and prediction based on clinicoradiologic factors.

BACKGROUND: Spread through air spaces (STAS) has recently been demonstrated to exhibit a negative impact on lung adenocarcinoma prognosis. However, most of these studies investigated STAS in nonmucinous adenocarcinoma. Here, we investigated the incidence of STAS in invasive mucinous adenocarcinoma (IMA) of the lung and evaluated whether tumor STAS was a risk factor of disease recurrence in IMA. We also examined clinicoradiologic factors in patients with IMA harboring STAS. METHODS: We reviewed pathologic specimens and imaging characteristics of primary tumors from 132 consecutive patients who underwent surgical resection for IMA to evaluate STAS. Patients with and without STAS were compared with respect to clinical characteristics as well as computed tomography (CT) imaging using logistic regression. The relationships between all variables including STAS and survival were analyzed. RESULTS: Among a total of 132 patients, full pathologic specimens were available for 119 patients, and STAS was observed in 86 (72.3%). IMA patients with STAS were significantly associated with older age, presence of lobulated and spiculated margins on CT scan (P = 0.009, P = 0.006, and P = 0.027). In multivariate analysis for overall survival (OS), STAS was a borderline independent poor prognostic predictor (P = 0.028). Older age, history of smoking, higher T stage, presence of lymph node metastasis, and consolidative morphologic type remained independent predictors for OS. CONCLUSIONS: STAS was associated with reduced OS and was a borderline independent poor prognostic factor in IMA. IMA with STAS was associated with older age and presence of lobulated and spiculated margins on CT scan. KEY POINTS: SIGNIFICANT FINDINGS OF THE STUDY: Compared with other subtypes, IMA shows a higher incidence of STAS, which is an independent poor prognostic predictor even in IMA. Lobulated and spiculated margins on CT are associated with STAS. WHAT THIS STUDY ADDS: Considering that STAS can carry the potential for aerogenous metastasis, predicting STAS using preoperative surrogate CT imaging is desirable to avoid limited resection.