Hemorrhagic Complications Following Ultrasound-Guided Breast Biopsy: A Prospective Patient-Centered Study.

OBJECTIVE: We aimed to evaluate the clinical and imaging factors associated with hemorrhagic complications and patient discomfort following ultrasound (US)-guided breast biopsy. MATERIALS AND METHODS: We prospectively enrolled 94 patients who were referred to our hospital between June 2022 and December 2022 for US-guided breast biopsy. After obtaining informed consent, two breast radiologists independently performed US-guided breast biopsy and evaluated the imaging findings. A hemorrhagic complication was defined as the presence of bleeding or hematoma on US. The patients rated symptoms of pain, febrile sensation, swelling at the biopsy site, and dyspnea immediately, 20 minutes, and 2 weeks after the procedure on a visual analog scale, with 0 for none and 10 for the most severe symptoms. Additional details recorded included those of nausea, vomiting, bleeding, bruising, and overall satisfaction score. We compared the clinical symptoms, imaging characteristics, and procedural features between patients with and those without hemorrhagic complications. RESULTS: Of 94 patients, 7 (7%) developed hemorrhagic complications, while 87 (93%) did not. The complication resolved with 20 minutes of manual compression, and no further intervention was required. Vascularity on Doppler examination (P = 0.008), needle type (P = 0.043), and lesion location (P < 0.001) were significantly different between the groups. Patients with hemorrhagic complications reported more frequent nausea or vomiting than those without hemorrhagic complications (29% [2/7] vs. 2% [2/87], respectively; P = 0.027). The overall satisfaction scores did not differ between the two groups (P = 0.396). After 2 weeks, all symptoms subsided, except bruising (50% 2/4 in the complication group and 25% [16/65] in the no-complication group). CONCLUSION: US-guided breast biopsy is a safe procedure with a low complication rate. Radiologists should be aware of hemorrhagic complications, patient discomfort, and overall satisfaction related to this procedure.

Artificial Intelligence for Breast Cancer Detection on Mammography: Factors Related to Cancer Detection.

RATIONALE AND OBJECTIVES: Little is known about the factors affecting the Artificial Intelligence (AI) software performance on mammography for breast cancer detection. This study was to identify factors associated with abnormality scores assigned by the AI software. MATERIALS AND METHODS: A retrospective database search was conducted to identify consecutive asymptomatic women who underwent breast cancer surgery between April 2016 and December 2019. A commercially available AI software (Lunit INSIGHT, MMG, Ver. 1.1.4.0) was used for preoperative mammography to assign individual abnormality scores to the lesions and score of 10 or higher was considered as positive detection by AI software. Radiologists without knowledge of the AI results retrospectively assessed the mammographic density and classified mammographic findings into positive and negative finding. General linear model (GLM) analysis was used to identify the clinical, pathological, and mammographic findings related to the abnormality scores, obtaining coefficient ß values that represent the mean difference per unit or comparison with the reference value. Additionally, the reasons for non-detection by the AI software were investigated. RESULTS: Among the 1001 index cancers (830 invasive cancers and 171 ductal carcinoma in situs) in 1001 patients, 717 (72%) were correctly detected by AI, while the remaining 284 (28%) were not detected. Multivariable GLM analysis showed that abnormal mammography findings (ß = 77.0 for mass, ß = 73.1 for calcification only, ß = 49.4 for architectural distortion, and ß = 47.6 for asymmetry compared to negative; all Ps < 0.001), invasive tumor size (ß = 4.3 per 1 cm, P < 0.001), and human epidermal growth receptor type 2 (HER2) positivity (ß = 9.2 compared to hormone receptor positive, HER2 negative, P = 0.004) were associated with higher mean abnormality score. AI failed to detect small asymmetries in extremely dense breasts, subcentimeter-sized or isodense lesions, and faint amorphous calcifications. CONCLUSION: Cancers with positive abnormal mammographic findings on retrospective review, large invasive size, HER2 positivity had high AI abnormality scores. Understanding the patterns of AI software performance is crucial for effectively integrating AI into clinical practice.

Problem Solving MRI to Reduce False-Positive Biopsy Related to Breast US: Conductivity vs. DWI vs. Abbreviated Contrast-Enhanced MRI.

BACKGROUND: While breast ultrasound (US) is a useful tool for diagnosing breast masses, it can entail false-positive biopsy results because of some overlapping features between benign and malignant breast masses and subjective interpretation. PURPOSE: To evaluate the performance of conductivity imaging for reducing false-positive biopsy results related to breast US, as compared to diffusion-weighted imaging (DWI) and abbreviated MRI consisting of one pre- and one post-contrast T1-weighted imaging. STUDY TYPE: Prospective. SUBJECTS: Seventy-nine women (median age, 44 years) with 86 Breast Imaging Reporting and Data System (BI-RADS) category 4 masses as detected by breast US. FIELD STRENGTH/SEQUENCE: 3-T, T2-weighted turbo spin echo sequence, DWI, and abbreviated contrast-enhanced MRI (T1-weighted gradient echo sequence). ASSESSMENT: US-guided biopsy (reference standard) was obtained on the same day as MRI. The maximum and mean conductivity parameters from whole and single regions of interest (ROIs) were measured. Apparent diffusion coefficient (ADC) values were obtained from an area with the lowest signal within a lesion on the ADC map. The performance of conductivity, ADC, and abbreviated MRI for reducing false-positive biopsies was evaluated using the following criteria: lowest conductivity and highest ADC values among malignant breast lesions and BI-RADS categories 2 or 3 on abbreviated MRI. STATISTICAL TESTS: One conductivity parameter with the maximum area under the curve (AUC) from receiver operating characteristics was selected. A P-value <0.05 was considered statistically significant. RESULTS: US-guided biopsy revealed 65 benign lesions and 21 malignant lesions. The mean conductivity parameter of the single ROI method was selected (AUC = 0.74). Considering conductivity (≤0.10 S/m), ADC (≥1.60 × 10-3 mm2 /sec), and BI-RADS categories 2 or 3 reduced false-positive biopsies by 23% (15 of 65), 38% (25 of 65), and 43% (28 of 65), respectively, without missing malignant lesions. DATA CONCLUSION: Conductivity imaging may show lower performance than DWI and abbreviated MRI in reducing unnecessary biopsies. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Ultrafast MRI and T1 and T2 Radiomics for Predicting Invasive Components in Ductal Carcinoma in Situ Diagnosed With Percutaneous Needle Biopsy.

OBJECTIVE: This study aimed to investigate the feasibility of ultrafast magnetic resonance imaging (MRI) and radiomic features derived from breast MRI for predicting the upstaging of ductal carcinoma in situ (DCIS) diagnosed using percutaneous needle biopsy. MATERIALS AND METHODS: Between August 2018 and June 2020, 95 patients with 98 DCIS lesions who underwent preoperative breast MRI, including an ultrafast sequence, and subsequent surgery were included. Four ultrafast MRI parameters were analyzed: time-to-enhancement, maximum slope (MS), area under the curve for 60 s after enhancement, and time-to-peak enhancement. One hundred and seven radiomic features were extracted for the whole tumor on the first post-contrast T1WI and T2WI using PyRadiomics. Clinicopathological characteristics, ultrafast MRI findings, and radiomic features were compared between the pure DCIS and DCIS with invasion groups. Prediction models, incorporating clinicopathological, ultrafast MRI, and radiomic features, were developed. Receiver operating characteristic curve analysis and area under the curve (AUC) were used to evaluate model performance in distinguishing between the two groups using leave-one-out cross-validation. RESULTS: Thirty-six of the 98 lesions (36.7%) were confirmed to have invasive components after surgery. Compared to the pure DCIS group, the DCIS with invasion group had a higher nuclear grade (P < 0.001), larger mean lesion size (P = 0.038), larger mean MS (P = 0.002), and different radiomic-related characteristics, including a more extensive tumor volume; higher maximum gray-level intensity; coarser, more complex, and heterogeneous texture; and a greater concentration of high gray-level intensity. No significant differences in AUCs were found between the model incorporating nuclear grade and lesion size (0.687) and the models integrating additional ultrafast MRI and radiomic features (0.680-0.732). CONCLUSION: High nuclear grade, larger lesion size, larger MS, and multiple radiomic features were associated with DCIS upstaging. However, the addition of MS and radiomic features to the prediction model did not significantly improve the prediction performance.

Artificial Intelligence Improves Detection of Supplemental Screening Ultrasound-detected Breast Cancers in Mammography.

Despite recent advances in artificial intelligence (AI) software with improved performance in mammography screening for breast cancer, insufficient data are available on its performance in detecting cancers that were initially missed on mammography. In this study, we aimed to determine whether AI software-aided mammography could provide additional value in identifying cancers detected through supplemental screening ultrasound. We searched our database from 2017 to 2018 and included 238 asymptomatic patients (median age, 50 years; interquartile range, 45-57 years) diagnosed with breast cancer using supplemental ultrasound. Two unblinded radiologists retrospectively reviewed the mammograms using commercially available AI software and identified the reasons for missed detection. Clinicopathological characteristics of AI-detected and AI-undetected cancers were compared using univariate and multivariate logistic regression analyses. A total of 253 cancers were detected in 238 patients using ultrasound. In an unblinded review, the AI software failed to detect 187 of the 253 (73.9%) mammography cases with negative findings in retrospective observations. The AI software detected 66 cancers (26.1%), of which 42 (63.6%) exhibited indiscernible findings obscured by overlapping dense breast tissues, even with the knowledge of magnetic resonance imaging and post-wire localization mammography. The remaining 24 cases (36.4%) were considered interpretive errors by the radiologists. Invasive tumor size was associated with AI detection after multivariable analysis (odds ratio, 2.2; 95% confidence intervals, 1.5-3.3; p < 0.001). In the control group of 160 women without cancer, the AI software identified 19 false positives (11.9%, 19/160). Although most ultrasound-detected cancers were not detected on mammography with the use of AI, the software proved valuable in identifying breast cancers with indiscernible abnormalities or those that clinicians may have overlooked.

Prediction of Tumor Progression During Neoadjuvant Chemotherapy and Survival Outcome in Patients With Triple-Negative Breast Cancer.

OBJECTIVE: To investigate the association of clinical, pathologic, and magnetic resonance imaging (MRI) variables with progressive disease (PD) during neoadjuvant chemotherapy (NAC) and distant metastasis-free survival (DMFS) in patients with triple-negative breast cancer (TNBC). MATERIALS AND METHODS: This single-center retrospective study included 252 women with TNBC who underwent NAC between 2010 and 2019. Clinical, pathologic, and treatment data were collected. Two radiologists analyzed the pre-NAC MRI. After random allocation to the development and validation sets in a 2:1 ratio, we developed models to predict PD and DMFS using logistic regression and Cox proportional hazard regression, respectively, and validated them. RESULTS: Among the 252 patients (age, 48.3 ± 10.7 years; 168 in the development set; 84 in the validation set), PD was occurred in 17 patients and 9 patients in the development and validation sets, respectively. In the clinical-pathologic-MRI model, the metaplastic histology (odds ratio [OR], 8.0; P = 0.032), Ki-67 index (OR, 1.02; P = 0.044), and subcutaneous edema (OR, 30.6; P = 0.004) were independently associated with PD in the development set. The clinical-pathologic-MRI model showed a higher area under the receiver-operating characteristic curve (AUC) than the clinical-pathologic model (AUC: 0.69 vs. 0.54; P = 0.017) for predicting PD in the validation set. Distant metastases occurred in 49 patients and 18 patients in the development and validation sets, respectively. Residual disease in both the breast and lymph nodes (hazard ratio [HR], 6.0; P = 0.005) and the presence of lymphovascular invasion (HR, 3.3; P < 0.001) were independently associated with DMFS. The model consisting of these pathologic variables showed a Harrell's C-index of 0.86 in the validation set. CONCLUSION: The clinical-pathologic-MRI model, which considered subcutaneous edema observed using MRI, performed better than the clinical-pathologic model for predicting PD. However, MRI did not independently contribute to the prediction of DMFS.

Background Parenchymal Enhancement at Postoperative Surveillance Breast MRI: Association with Future Second Breast Cancer Risk.

Background Background parenchymal enhancement (BPE) is a known risk factor for breast cancer. However, studies on the association between BPE and second breast cancer risk are still lacking. Purpose To investigate whether BPE at surveillance breast MRI is associated with subsequent second breast cancer risk in women with a personal history of breast cancer. Materials and Methods A retrospective search of the imaging database of an academic medical center identified consecutive surveillance breast MRI examinations performed between January 2008 and December 2017 in women who underwent surgery for primary breast cancer and had no prior diagnosis of second breast cancer. BPE at surveillance breast MRI was qualitatively assessed using a four-category classification of minimal, mild, moderate, or marked. Future second breast cancer was defined as ipsilateral breast tumor recurrence or contralateral breast cancer diagnosed at least 1 year after each surveillance breast MRI examination. Factors associated with future second breast cancer risk were evaluated using the multivariable Fine-Gray subdistribution hazard model. Results Among the 2668 women (mean age at baseline surveillance breast MRI, 49 years ± 8 [SD]), 109 developed a second breast cancer (49 ipsilateral, 58 contralateral, and two ipsilateral and contralateral) at a median follow-up of 5.8 years. Mild, moderate, or marked BPE at surveillance breast MRI (hazard ratio [HR], 2.1 [95% CI: 1.4, 3.1]; P < .001), young age (<45 years) at initial breast cancer diagnosis (HR, 3.4 [95% CI: 1.7, 6.4]; P < .001), positive results from a BRCA1/2 genetic test (HR, 6.5 [95% CI: 3.5, 12.0]; P < .001), and negative hormone receptor expression in the initial breast cancer (HR, 1.6 [95% CI: 1.1, 2.6]; P = .02) were independently associated with an increased risk of future second breast cancer. Conclusion Background parenchymal enhancement at surveillance breast MRI was associated with future second breast cancer risk in women with a personal history of breast cancer. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Niell in this issue.

Abbreviated Screening MRI for Women with a History of Breast Cancer: Comparison with Full-Protocol Breast MRI.

Background Few studies have compared abbreviated breast MRI with full-protocol MRI in women with a personal history of breast cancer (PHBC), and they have not adjusted for confounding variables. Purpose To compare abbreviated breast MRI with full-protocol MRI in women with PHBC by using propensity score matching to adjust for confounding variables. Materials and Methods In this single-center retrospective study, women with PHBC who underwent full-protocol MRI (January 2008-August 2017) or abbreviated MRI (September 2017-April 2019) were identified. With use of a propensity score-matched cohort, screening performances were compared between the two MRI groups with the McNemar test or a propensity score-adjusted generalized estimating equation. The coprimary analyses were sensitivity and specificity. The secondary analyses were the cancer detection rate, interval cancer rate, positive predictive value for biopsies performed (PPV3), and Breast Imaging Reporting and Data System (BI-RADS) category 3 short-term follow-up rate. Results There were 726 women allocated to each MRI group (mean age ± SD, 50 years ± 8 for both groups). Abbreviated MRI and full-protocol MRI showed comparable sensitivity (15 of 15 cancers [100%; 95% CI: 78, 100] vs nine of 13 cancers [69%; 95% CI: 39, 91], respectively; P = .17). Abbreviated MRI showed higher specificity than full-protocol MRI (660 of 711 examinations [93%; 95% CI: 91, 95] vs 612 of 713 examinations [86%; 95% CI: 83, 88], respectively; P < .001). The cancer detection rate (21 vs 12 per 1000 examinations), interval cancer rate (0 vs five per 1000 examinations), and PPV3 (61% [14 of 23 examinations] vs 41% [nine of 22 examinations]) were comparable (all P < .05). The BI-RADS category 3 short-term follow-up rate of abbreviated MRI was less than half that of full-protocol MRI (5% [36 of 726 examinations] vs 12% [84 of 726 examinations], respectively; P < .001). Ninety-three percent (14 of 15) of cancers detected at abbreviated MRI were node-negative T1-invasive cancers (n = 6) or ductal carcinoma in situ (n = 8). Conclusion Abbreviated breast MRI showed comparable sensitivity and superior specificity to full-protocol MRI in breast cancer detection in women with a personal history of breast cancer. © RSNA, 2022 Online supplemental material is available for this article.

US Evaluation of Axillary Lymphadenopathy Following COVID-19 Vaccination: A Prospective Longitudinal Study.

Background Both temporal changes in imaging characteristics of lymphadenopathy on US scans after COVID-19 vaccination and expected duration of radiologically evident lymphadenopathy remain uncertain. Purpose To longitudinally evaluate COVID-19 vaccine-associated lymphadenopathy on axillary US scans at various time intervals in both messenger (mRNA) and vector vaccine recipients. Materials and Methods This prospective cohort study was conducted between March 2021 and January 2022. The participants were asymptomatic women without breast cancer who had received COVID-19 vaccination. Serial follow-up US was performed in women with lymphadenopathy. The following variables were assessed: cortical thickness, number of lymph nodes, morphologic characteristics, and Doppler signal. Temporal changes in cortical thickness and number of lymph nodes during follow-up were assessed using a linear mixed model. Results Ninety-one women with lymphadenopathy in the vaccinated arm had undergone a total of 215 serial US examinations (mean age, 44 years ± 13 [SD]). Fifty-one participants had received a vector vaccine (ChAdOx1 nCoV-19 vaccine) and 40 had received an mRNA vaccine (BNT162b2 vaccine [n = 37] and mRNA-1273 vaccine [n = 3]). Three of the 91 women were lost to follow-up; thus, 88 women underwent serial US. Complete resolution of axillary lymphadenopathy was observed at a median of 6 weeks after vaccination (range, 4-7 weeks) in 26% of women (23 of 88). Among 49 women with follow-up US at a median of 12 weeks after vaccination (range, 8-14 weeks), persistent lymphadenopathy was observed in 25 (51%). During the follow-up period, the cortical thickness gradually decreased (P < .001) over time regardless of vaccine type; however, values were higher in recipients of the mRNA vaccine than in recipients of the vector vaccine (P = .02). Conclusion COVID-19 vaccine-associated axillary lymphadenopathy frequently persisted for more than 6 weeks on US scans. Lymphadenopathy should be interpreted considering vaccine type and time elapsed since vaccination. Follow-up US examination at least 12 weeks after vaccination may be reasonable, particularly for recipients of the messenger RNA vaccine. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Moy and Kim in this issue.

Ipsilateral Lymphadenopathy After COVID-19 Vaccination in Patients With Newly Diagnosed Breast Cancer.

This study aimed to evaluate the imaging and pathological findings in axillary lymph nodes in patients with breast cancer who received concurrent ipsilateral coronavirus disease 2019 (COVID-19) vaccination. Of the 19 women with breast cancer who received concurrent COVID-19 vaccination shot in the arm ipsilateral to breast cancer, axillary lymphadenopathy was observed in 84.2% (16 of 19) of patients on ultrasound (US) and 71.4% (10 of 14) of patients on magnetic resonance imaging (MRI), and 21.0% (4 of 19) of patients were diagnosed with metastasis. Abnormal US and MRI findings of cortical thickening, effacement of the fatty hilum, round shape, and asymmetry in the number or size relative to the contralateral side were noted in more than half of the non-metastatic and metastatic lymph nodes; however, statistical significance was not noted. Axillary lymphadenopathy is commonly observed in patients with breast cancer who receive concurrent ipsilateral COVID-19 vaccination without specific differential imaging features. Thus, understanding the limitations of axillary imaging and cautious interpretation is necessary to avoid overestimation or underestimation of the axillary disease burden.

Comparisons between image quality and diagnostic performance of 2D- and breath-hold 3D magnetic resonance cholangiopancreatography at 3T.

OBJECTIVES: To compare the image quality and diagnostic performance of 2D MRCP to those of breath-hold 3D MRCP using compressed sensing (CS-MRCP) and gradient and spin-echo (GRASE-MRCP) at 3T. METHODS: From January to November 2018, patients who underwent pancreatobiliary MRI including 2D MRCP and two breath-hold 3D MRCP using CS and GRASE at 3T were included. Three radiologists independently evaluated image quality, motion artifact, and pancreatic cyst conspicuity. Diagnostic performance was assessed for bile duct anatomic variation, bile duct, and pancreatic diseases using a composite algorithm as reference standards. Pancreatic lesion detectability and conspicuity were evaluated using JAFROC and generalized estimating equation analysis. RESULTS: One hundred patients (male = 50) were included. Bile duct anatomic variation, bile duct and pancreatic diseases were present in respectively 31, 15, and 79 patients. Breath-hold 3D MRCP provided better image quality than 2D MRCP (3.5 ± 0.6 in 2D MRCP; 4.0 ± 0.7 in GRASE-MRCP and 3.9 ± 0.8 in CS-MRCP, p < 0.001 for both). There was no difference in motion artifact between 2D and breath-hold 3D MRCP (p = 0.1). Breath-hold 3D CS-MRCP provided better pancreatic cyst conspicuity than 2D MRCP (2.7 [95% CI: 2.5-3.0] vs. 2.3 [95% CI: 2.1-2.5], p = 0.001). There were no significant differences between the diagnostic performance of the three sequences in the detection of bile duct anatomic variation or pancreatic lesions (p > 0.05). CONCLUSION: Breath-hold 3D MRCP with GRASE or CS can provide better image quality than 2D MRCP in a comparable scan time. KEY POINTS: • Breath-hold 3D MRCP using compressed sensing (CS) or gradient and spin-echo (GRASE) provided a better image quality with less image blurring than 2D MRCP. • There were no significant differences between 2D MRCP and breath-hold 3D MRCP in either motion artifact or the number of non-diagnostic exams. • There were no significant differences between 2D MRCP and either type of breath-hold 3D MRCP in the diagnosis of bile duct anatomic variation or detection of pancreatic lesions.

Blood-Brain Barrier Disruption in Mild Traumatic Brain Injury Patients with Post-Concussion Syndrome: Evaluation with Region-Based Quantification of Dynamic Contrast-Enhanced MR Imaging Parameters Using Automatic Whole-Brain Segmentation.

OBJECTIVE: This study aimed to investigate the blood-brain barrier (BBB) disruption in mild traumatic brain injury (mTBI) patients with post-concussion syndrome (PCS) using dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging and automatic whole brain segmentation. MATERIALS AND METHODS: Forty-two consecutive mTBI patients with PCS who had undergone post-traumatic MR imaging, including DCE MR imaging, between October 2016 and April 2018, and 29 controls with DCE MR imaging were included in this retrospective study. After performing three-dimensional T1-based brain segmentation with FreeSurfer software (Laboratory for Computational Neuroimaging), the mean Ktrans and vp from DCE MR imaging (derived using the Patlak model and extended Tofts and Kermode model) were analyzed in the bilateral cerebral/cerebellar cortex, bilateral cerebral/cerebellar white matter (WM), and brainstem. Ktrans values of the mTBI patients and controls were calculated using both models to identify the model that better reflected the increased permeability owing to mTBI (tendency toward higher Ktrans values in mTBI patients than in controls). The Mann-Whitney U test and Spearman rank correlation test were performed to compare the mean Ktrans and vp between the two groups and correlate Ktrans and vp with neuropsychological tests for mTBI patients. RESULTS: Increased permeability owing to mTBI was observed in the Patlak model but not in the extended Tofts and Kermode model. In the Patlak model, the mean Ktrans in the bilateral cerebral cortex was significantly higher in mTBI patients than in controls (p = 0.042). The mean vp values in the bilateral cerebellar WM and brainstem were significantly lower in mTBI patients than in controls (p = 0.009 and p = 0.011, respectively). The mean Ktrans of the bilateral cerebral cortex was significantly higher in patients with atypical performance in the auditory continuous performance test (commission errors) than in average or good performers (p = 0.041). CONCLUSION: BBB disruption, as reflected by the increased Ktrans and decreased vp values from the Patlak model, was observed throughout the bilateral cerebral cortex, bilateral cerebellar WM, and brainstem in mTBI patients with PCS.

Prediction of tumor recurrence and poor survival of ampullary adenocarcinoma using preoperative clinical and CT findings.

OBJECTIVES: To predict poor survival and tumor recurrence in patients with ampullary adenocarcinoma using preoperative clinical and CT findings. MATERIALS AND METHODS: A total of 216 patients with ampullary adenocarcinoma who underwent preoperative CT and surgery were retrospectively included. CT was assessed by two radiologists. Clinical and histopathological characteristics including histologic subtypes were investigated. A Cox proportional hazard model and the Kaplan-Meier method were used to identify disease-free survival (DFS) and overall survival (OS). A nomogram was created based on the multivariate analysis. The optimal cutoff size of the tumor was evaluated and validated by internal cross validation. RESULTS: The median OS was 62.8 ± 37.9, and the median DFS was 54.3 ± 41.2 months. For OS, tumor size (hazard ratio [HR] 2.79, p < 0.001), papillary bulging (HR 0.63, p = 0.049), organ invasion on CT (HR 1.92, p = 0.04), male sex (HR 1.59, p = 0.046), elevated CA 19-9 (HR 1.92, p = 0.01), pT stage (HR 2.45, p = 0.001), and pN stage (HR 3.04, p < 0.001) were important predictors of survival. In terms of recurrence, tumor size (HR 2.37, p = 0.04), pT stage (HR 1.76, p = 0.03), pN stage (HR 2.23, p = 0.001), and histologic differentiation (HR 4.31, p = 0.008) were important predictors of recurrence. In terms of tumor size on CT, 2.65 cm and 3.15 cm were significant cutoff values for poor OS and RFS (p < 0.001). CONCLUSION: Preoperative clinical and CT findings were useful to predict the outcomes of ampullary adenocarcinoma. In particular, tumor size, papillary bulging, organ invasion on CT, male sex, and elevated CA 19-9 were important predictors of poor survival after surgery. KEY POINTS: • Clinical staging based on preoperative clinical information and CT findings can be useful to predict the prognosis of ampullary adenocarcinoma patients. • In terms of survival, tumor size (HR 2.79), papillary bulging (HR 0.63), organ invasion on CT (HR 1.92), male sex (HR 1.59), and elevated CA 19-9 (HR 1.92) were important clinical predictors of poor survival. • Tumor size on CT was of special importance for both poor overall survival and disease-free survival, with optimal cutoff values of 2.65 cm and 3.15 cm, respectively (p < 0.001).

Prognostic Value of Tumor Regression Grade on MR in Rectal Cancer: A Large-Scale, Single-Center Experience.

OBJECTIVE: To determine the prognostic value of MRI-based tumor regression grading (mrTRG) in rectal cancer compared with pathological tumor regression grading (pTRG), and to assess the effect of diffusion-weighted imaging (DWI) on interobserver agreement for evaluating mrTRG. MATERIALS AND METHODS: Between 2007 and 2016, we retrospectively enrolled 321 patients (male:female = 208:113; mean age, 60.2 years) with rectal cancer who underwent both pre-chemoradiotherapy (CRT) and post-CRT MRI. Two radiologists independently determined mrTRG using a 5-point grading system with and without DWI in a one-month interval. Two pathologists graded pTRG using a 5-point grading system in consensus. Kaplan-Meier estimation and Cox-proportional hazard models were used for survival analysis. Cohen's kappa analysis was used to determine interobserver agreement. RESULTS: According to mrTRG on MRI with DWI, there were 6 mrTRG 1, 48 mrTRG 2, 109 mrTRG 3, 152 mrTRG 4, and 6 mrTRG 5. By pTRG, there were 7 pTRG 1, 59 pTRG 2, 180 pTRG 3, 73 pTRG 4, and 2 pTRG 5. A 5-year overall survival (OS) was significantly different according to the 5-point grading mrTRG (p = 0.024) and pTRG (p = 0.038). The 5-year disease-free survival (DFS) was significantly different among the five mrTRG groups (p = 0.039), but not among the five pTRG groups (p = 0.072). OS and DFS were significantly different according to post-CRT MR variables: extramural venous invasion after CRT (hazard ratio = 2.259 for OS, hazard ratio = 5.011 for DFS) and extramesorectal lymph node (hazard ratio = 2.610 for DFS). For mrTRG, k value between the two radiologists was 0.309 (fair agreement) without DWI and slightly improved to 0.376 with DWI. CONCLUSION: mrTRG may predict OS and DFS comparably or even better compared to pTRG. The addition of DWI on T2-weighted MRI may improve interobserver agreement on mrTRG.

A Novel Algorithm to Differentiate Between Multiple Primary Lung Cancers and Intrapulmonary Metastasis in Multiple Lung Cancers With Multiple Pulmonary Sites of Involvement.

INTRODUCTION: Differentiating between multiple primary lung cancer (MPLC) and intrapulmonary metastasis (IPM) is critical for developing a therapeutic strategy to treat multiple lung cancers with multiple pulmonary sites of involvement. METHODS: We retrospectively included 252 lesions (126 pairs) from 126 patients with surgically resected multiple lung adenocarcinomas. Each pair was classified as MPLC or IPM based on histopathologic findings as the reference standard. A novel algorithm was established with four sequential decision steps based on the combination of computed tomography (CT) lesion types (step 1), CT lesion morphology (step 2), difference of maximal standardized uptake values on positron-emission tomography/CT (step 3), and presence of N2/3 lymph node metastasis or distant metastasis (step 4). The diagnostic accuracy of the algorithm was analyzed. Performances of 11 observers were assessed without and with knowledge of algorithm. RESULTS: Among 126 pairs, 90 (71.4%) were classified as MPLCs and 36 (28.6%) as IPMs. On applying the diagnostic algorithm, the overall accuracy for diagnosis of IPM among conclusive cases up to step 4 was 88.9%, and 65 and 44 pairs were correctly diagnosed based on step 1 and step 2, respectively. Specificity and positive predictive value for diagnosis of IPM increased significantly in all observers compared with reading rounds without the algorithm. CONCLUSIONS: Application of the algorithm based on comprehensive information on clinical and imaging variables can allow differentiation between MPLCs and IPMs. When both of two suspected malignant lesions appear as solid predominant lesions without spiculation or air-bronchogram on CT, IPM should be considered.

Fate of small pancreatic cysts (<3 cm) after long-term follow-up: analysis of significant radiologic characteristics and proposal of follow-up strategies.

OBJECTIVE: To describe the natural history of pancreatic cysts after long-term follow-up, with an emphasis on the identifying indicators of indolent lesions. METHODS: We retrospectively sampled 95 patients with 149 cysts <3 cm detected by CT from 2003 to 2004, and followed them for more than five years (mean 117.5 ± 18.8 months). Two radiologists reviewed the initial CT images, then recorded changes after the follow-up. We compared the cysts' initial characteristics between the surgery and non-surgery patient groups, and also between non-benign lesions and benign lesions. RESULTS: Twelve of the 95 patients, who among them had 16 cysts, underwent surgery. Of the 133 cysts in the 83 nonsurgical patients, 57 cysts (42.9 %) enlarged, although only five cysts increased to larger than 3 cm at the end of observation. The initial size of the cyst was significantly larger in the surgery group than non-surgery group. Also, according to cyst-based analysis, ductal communication, dilatation, and shape correlated with those of non-benign cysts and the non-surgical group. No cysts < 15 mm and without p-duct change showed a significant change within three years. CONCLUSION: Small pancreatic cysts, without p-duct change, and without a pleomorphic or clubbed shape, may be followed for a longer interval than current consensus. KEY POINTS: • Almost all small cysts < 3 cm were indolent in long term observation. • No cysts < 15 mm, without p-duct change showed significant change within 3 years. • Cyst size, ductal change and shape can be useful in predicting progress. • Only cysts with IPMN- like features and p-duct change need follow-up with cautions.