Use of automated assessment for determining associations of low muscle mass and muscle loss with overall survival in patients with colorectal cancer - A validation study.

BACKGROUND: Low muscle mass and skeletal muscle mass (SMM) loss are associated with adverse patient outcomes, but the time-consuming nature of manual SMM quantification prohibits implementation of this metric in clinical practice. Therefore, we assessed the feasibility of automated SMM quantification compared to manual quantification. We evaluated both diagnostic accuracy for low muscle mass and associations of SMM (change) with survival in colorectal cancer (CRC) patients. METHODS: Computed tomography (CT) images from CRC patients enrolled in two clinical studies were analyzed. We compared i) manual vs. automated segmentation of preselected slices at the third lumbar [L3] vertebra ("semi-automated"), and ii) manual L3-slice-selection + manual segmentation vs. automated L3-slice-selection + automated segmentation ("fully-automated"). Automated L3-selection and automated segmentation was performed with Quantib Body Composition v0.2.1. Bland-Altman analyses, within-subject coefficients of variation (WSCVs) and Intraclass Correlation Coefficients (ICCs) were used to evaluate the agreement between manual and automatic segmentation. Diagnostic accuracy for low muscle mass (defined by an established sarcopenia cut-off) was calculated with manual assessment as the "gold standard". Using either manual or automated assessment, Cox proportional hazard ratios (HRs) were used to study the association between changes in SMM (>5% decrease yes/no) during first-line metastatic CRC treatment and mortality adjusted for prognostic factors. SMM change was also assessed separately in weight-stable (<5%, i.e. occult SMM loss) patients. RESULTS: In total, 1580 CT scans were analyzed, while a subset of 307 scans were analyzed in the fully-automated comparison. Included patients (n = 553) had a mean age of 63 ± 9 years and 39% were female. The semi-automated comparison revealed a bias of -2.41 cm2, 95% limits of agreement [-9.02 to 4.20], a WSCV of 2.25%, and an ICC of 0.99 (95% confidence intervals (CI) 0.97 to 1.00). The fully-automated comparison method revealed a bias of -0.08 cm2 [-10.91 to 10.75], a WSCV of 2.85% and an ICC of 0.98 (95% CI 0.98 to 0.99). Sensitivity and specificity for low muscle mass were 0.99 and 0.89 for the semi-automated comparison and 0.96 and 0.90 for the fully-automated comparison. SMM decrease was associated with shorter survival in both manual and automated assessment (n = 78/280, HR 1.36 [95% CI 1.03 to 1.80] and n = 89/280, HR 1.38 [95% CI 1.05 to 1.81]). Occult SMM loss was associated with shorter survival in manual assessment, but not significantly in automated assessment (n = 44/263, HR 1.43 [95% CI 1.01 to 2.03] and n = 51/2639, HR 1.23 [95% CI 0.87 to 1.74]). CONCLUSION: Deep-learning based assessment of SMM at L3 shows reliable performance, enabling the use of CT measures to guide clinical decision making. Implementation in clinical practice helps to identify patients with low muscle mass or (occult) SMM loss who may benefit from lifestyle interventions.

Re-attendance in supplemental breast MRI screening rounds of the DENSE trial for women with extremely dense breasts.

OBJECTIVES: Supplemental MRI screening improves early breast cancer detection and reduces interval cancers in women with extremely dense breasts in a cost-effective way. Recently, the European Society of Breast Imaging recommended offering MRI screening to women with extremely dense breasts, but the debate on whether to implement it in breast cancer screening programs is ongoing. Insight into the participant experience and willingness to re-attend is important for this discussion. METHODS: We calculated the re-attendance rates of the second and third MRI screening rounds of the DENSE trial. Moreover, we calculated age-adjusted odds ratios (ORs) to study the association between characteristics and re-attendance. Women who discontinued MRI screening were asked to provide one or more reasons for this. RESULTS: The re-attendance rates were 81.3% (3458/4252) and 85.2% (2693/3160) in the second and third MRI screening round, respectively. A high age (> 65 years), a very low BMI, lower education, not being employed, smoking, and no alcohol consumption were correlated with lower re-attendance rates. Moderate or high levels of pain, discomfort, or anxiety experienced during the previous MRI screening round were correlated with lower re-attendance rates. Finally, a plurality of women mentioned an examination-related inconvenience as a reason to discontinue screening (39.1% and 34.8% in the second and third screening round, respectively). CONCLUSIONS: The willingness of women with dense breasts to re-attend an ongoing MRI screening study is high. However, emphasis should be placed on improving the MRI experience to increase the re-attendance rate if widespread supplemental MRI screening is implemented. CLINICAL RELEVANCE STATEMENT: For many women, MRI is an acceptable screening method, as re-attendance rates were high - even for screening in a clinical trial setting. To further enhance the (re-)attendance rate, one possible approach could be improving the overall MRI experience. KEY POINTS: • The willingness to re-attend in an ongoing MRI screening study is high. • Pain, discomfort, and anxiety in the previous MRI screening round were related to lower re-attendance rates. • Emphasis should be placed on improving MRI experience to increase the re-attendance rate in supplemental MRI screening.

Automated rating of background parenchymal enhancement in MRI of extremely dense breasts without compromising the association with breast cancer in the DENSE trial.

OBJECTIVES: Background parenchymal enhancement (BPE) on dynamic contrast-enhanced MRI (DCE-MRI) as rated by radiologists is subject to inter- and intrareader variability. We aim to automate BPE category from DCE-MRI. METHODS: This study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial. 4553 women with extremely dense breasts who received supplemental breast MRI screening in eight hospitals were included. Minimal, mild, moderate and marked BPE rated by radiologists were used as reference. Fifteen quantitative MRI features of the fibroglandular tissue were extracted to predict BPE using Random Forest, Naïve Bayes, and KNN classifiers. Majority voting was used to combine the predictions. Internal-external validation was used for training and validation. The inverse-variance weighted mean accuracy was used to express mean performance across the eight hospitals. Cox regression was used to verify non inferiority of the association between automated rating and breast cancer occurrence compared to the association for manual rating. RESULTS: The accuracy of majority voting ranged between 0.56 and 0.84 across the eight hospitals. The weighted mean prediction accuracy for the four BPE categories was 0.76. The hazard ratio (HR) of BPE for breast cancer occurrence was comparable between automated rating and manual rating (HR = 2.12 versus HR = 1.97, P = 0.65 for mild/moderate/marked BPE relative to minimal BPE). CONCLUSION: It is feasible to rate BPE automatically in DCE-MRI of women with extremely dense breasts without compromising the underlying association between BPE and breast cancer occurrence. The accuracy for minimal BPE is superior to that for other BPE categories.

The value of chest radiography after chest tube removal in nonventilated trauma patients: A post hoc analysis of a multicenter prospective cohort study.

BACKGROUND: Chest tubes are commonly placed in trauma care to treat life-threatening intrathoracic injuries by evacuating blood or air from the pleural cavity. Currently, it is common practice to routinely obtain chest radiographs between 1 to 8 hours after chest tube removal, while the necessity of it has been questioned. This study describes the "ins-and-outs" of chest tubes and evaluates the value of routine postremoval chest radiography in nonventilated trauma patients. METHODS: A post hoc analysis of a multicenter observational prospective cohort study was performed in blunt chest trauma patients admitted with multiple rib fractures to two level 1 trauma centers between January 2018 and March 2021 and treated with one or more chest tubes. Exclusion criteria were mechanical ventilation during chest tube removal, missing reports of postremoval chest radiography, transfer to another hospital, or mortality before chest tube removal. Descriptive analyses were performed to calculate the number of findings on postremoval chest radiographs and reinterventions. RESULTS: A total of 207 patients were included for analysis of whom 14 underwent bilateral chest tube placement, resulting in 221 chest tube removals investigated in this study. The mean ± SD age was 58 ± 17 years, 71% were male, 73% had American Society of Anesthesiologists scores of 1 or 2, and the median Injury Severity Score was 19 (interquartile range, 14-29). In 68 of 221 chest tube removals (31%), postremoval chest radiography showed increased or recurrent intrathoracic pathology (i.e., 13% pneumothorax, 18% pleural fluid, and 8% atelectasis). Only two (3%) of these patients underwent a same-day reintervention based on these findings, of whom one had signs or symptoms of recurrent pathology and one was asymptomatic. CONCLUSION: It seems safe to omit routine use of postremoval chest radiography in nonventilated blunt chest trauma patients and to selectively use imaging in those patients presenting with clinical signs or symptoms after chest tube removal. LEVEL OF EVIDENCE: Diagnostic Tests/Criteria; Level IV.

Assessing Quantitative Parenchymal Features at Baseline Dynamic Contrast-enhanced MRI and Cancer Occurrence in Women with Extremely Dense Breasts.

Background Automated identification of quantitative breast parenchymal enhancement features on dynamic contrast-enhanced (DCE) MRI scans could provide added value in assessment of breast cancer risk in women with extremely dense breasts. Purpose To automatically identify quantitative properties of the breast parenchyma on baseline DCE MRI scans and assess their association with breast cancer occurrence in women with extremely dense breasts. Materials and Methods This study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial. MRI was performed in eight hospitals between December 2011 and January 2016. After segmentation of fibroglandular tissue, quantitative features (including volumetric density, volumetric morphology, and enhancement characteristics) of the parenchyma were extracted from baseline MRI scans. Principal component analysis was used to identify parenchymal measures with the greatest variance. Multivariable Cox proportional hazards regression was applied to assess the association between breast cancer occurrence and quantitative parenchymal features, followed by stratification of significant features into tertiles. Results A total of 4553 women (mean age, 55.7 years ± 6 [SD]) with extremely dense breasts were included; of these women, 122 (3%) were diagnosed with breast cancer. Five principal components representing 96% of the variance were identified, and the component explaining the greatest independent variance (42%) consisted of MRI features relating to volume of enhancing parenchyma. Multivariable analysis showed that volume of enhancing parenchyma was associated with breast cancer occurrence (hazard ratio [HR], 1.09; 95% CI: 1.01, 1.18; P = .02). Additionally, women in the high tertile of volume of enhancing parenchyma showed a breast cancer occurrence twice that of women in the low tertile (HR, 2.09; 95% CI: 1.25, 3.61; P = .005). Conclusion In women with extremely dense breasts, a high volume of enhancing parenchyma on baseline DCE MRI scans was associated with increased occurrence of breast cancer as compared with a low volume of enhancing parenchyma. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Grimm in this issue.

Optimizing carboplatin dosing by an improved prediction of carboplatin clearance using a CT-enhanced estimate of renal function.

AIMS: Carboplatin is generally dosed based on a modified Calvert formula, in which the Cockcroft-Gault-based creatinine clearance (CRCL) is used as proxy for the glomerular filtration rate (GFR). The Cockcroft-Gault formula (CG) overpredicts CRCL in patients with an aberrant body composition. The CT-enhanced estimate of RenAl FuncTion (CRAFT) was developed to compensate for this overprediction. We aimed to evaluate whether carboplatin clearance is better predicted by CRCL based on the CRAFT compared to the CG. METHODS: Data of four previously conducted trials was used. The CRAFT was divided by serum creatinine to derive CRCL. The difference between CRAFT- and CG-based CRCL was assessed by population pharmacokinetic modelling. Furthermore, the difference in calculated carboplatin dose was assessed in a heterogeneous dataset. RESULTS: In total, 108 patients were included in the analysis. Addition of the CRAFT- and CG-based CRCL as covariate on carboplatin clearance led, respectively, to an improved model fit with a 26-point drop in objective function value and a worsened model fit with an increase of 8 points. In 19 subjects with serum creatinine <50 µmol/L, the calculated carboplatin dose was 233 mg higher using the CG. CONCLUSIONS: Carboplatin clearance is better predicted by CRAFT vs. CG-based CRCL. In subjects with low serum creatinine, the calculated carboplatin dose using CG exceeds the dose using CRAFT, which might explain the need for dose capping when using the CG. Therefore, the CRAFT might be an alternative for dose capping while still dosing accurately.

The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients.

PURPOSE: The present study aims to assess whether CT-derived muscle mass, muscle density, and visceral fat mass are associated with in-hospital complications and clinical outcome in level-1 trauma patients. METHODS: A retrospective cohort study was conducted on adult patients admitted to the University Medical Center Utrecht following a trauma between January 1 and December 31, 2017. Trauma patients aged 16 years or older without severe neurological injuries, who underwent a CT that included the abdomen within 7 days of admission, were included. An artificial intelligence (AI) algorithm was used to retrieve muscle areas to calculate the psoas muscle index and to retrieve psoas muscle radiation attenuation and visceral fat (VF) area from axial CT images. Multivariable logistic and linear regression analyses were performed to assess associations between body composition parameters and outcomes. RESULTS: A total of 404 patients were included for analysis. The median age was 49 years (interquartile range [IQR] 30-64), and 66.6% were male. Severe comorbidities (ASA 3-4) were seen in 10.9%, and the median ISS was 9 (IQR 5-14). Psoas muscle index was not independently associated with complications, but it was associated with ICU admission (odds ratio [OR] 0.79, 95% confidence interval [CI] 0.65-0.95), and an unfavorable Glasgow Outcome Scale (GOS) score at discharge (OR 0.62, 95% CI 0.45-0.85). Psoas muscle radiation attenuation was independently associated with the development of any complication (OR 0.60, 95% CI 0.42-0.85), pneumonia (OR 0.63, 95% CI 0.41-0.96), and delirium (OR 0.49, 95% CI 0.28-0.87). VF was associated with developing a delirium (OR 1.95, 95% CI 1.12-3.41). CONCLUSION: In level-1 trauma patients without severe neurological injuries, automatically derived body composition parameters are able to independently predict an increased risk of specific complications and other poor outcomes.

Challenges and Changes of the Breast Cancer Screening Paradigm.

Since four decades mammography is used for early breast cancer detection in asymptomatic women and still remains the gold standard imaging modality. However, population screening programs can be personalized and women can be divided into different groups based on risk factors and personal preferences. The availability of new and evolving imaging modalities, for example, digital breast tomosynthesis, dynamic-contrast-enhanced magnetic resonance imaging (MRI), abbreviated MRI protocols, diffusion-weighted MRI, and contrast-enhanced mammography leads to new challenges and perspectives regarding the feasibility and potential harms of breast cancer screening. The aim of this review is to discuss the current guidelines for different risk groups, to analyze the recent published studies about the diagnostic performance of the imaging modalities and to discuss new developments and future perspectives. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 6.

Validation of Combined Deep Learning Triaging and Computer-Aided Diagnosis in 2901 Breast MRI Examinations From the Second Screening Round of the Dense Tissue and Early Breast Neoplasm Screening Trial.

OBJECTIVES: Computer-aided triaging (CAT) and computer-aided diagnosis (CAD) of screening breast magnetic resonance imaging have shown potential to reduce the workload of radiologists in the context of dismissing normal breast scans and dismissing benign disease in women with extremely dense breasts. The aim of this study was to validate the potential of integrating CAT and CAD to reduce workload and workup on benign lesions in the second screening round of the DENSE trial, without missing cancer. METHODS: We included 2901 breast magnetic resonance imaging scans, obtained from 8 hospitals in the Netherlands. Computer-aided triaging and CAD were previously developed on data from the first screening round. Computer-aided triaging dismissed examinations without lesions. Magnetic resonance imaging examinations triaged to radiological reading were counted and subsequently processed by CAD. The number of benign lesions correctly classified by CAD was recorded. The false-positive fraction of the CAD was compared with that of unassisted radiological reading in the second screening round. Receiver operating characteristics (ROC) analysis was performed and the generalizability of CAT and CAD was assessed by comparing results from first and second screening rounds. RESULTS: Computer-aided triaging dismissed 950 of 2901 (32.7%) examinations with 49 lesions in total; none were malignant. Subsequent CAD classified 132 of 285 (46.3%) lesions as benign without misclassifying any malignant lesion. Together, CAT and CAD yielded significantly fewer false-positive lesions, 53 of 109 (48.6%) and 89 of 109 (78.9%), respectively ( P = 0.001), than radiological reading alone. Computer-aided triaging had a smaller area under the ROC curve in the second screening round compared with the first, 0.83 versus 0.76 ( P = 0.001), but this did not affect the negative predictive value at the 100% sensitivity operating threshold. Computer-aided diagnosis was not associated with significant differences in area under the ROC curve (0.857 vs 0.753, P = 0.08). At the operating thresholds, the specificities of CAT (39.7% vs 41.0%, P = 0.70) and CAD (41.0% vs 38.2%, P = 0.62) were successfully reproduced in the second round. CONCLUSION: The combined application of CAT and CAD showed potential to reduce workload of radiologists and to reduce number of biopsies on benign lesions. Computer-aided triaging (CAT) correctly dismissed 950 of 2901 (32.7%) examinations with 49 lesions in total; none were malignant. Subsequent computer-aided diagnosis (CAD) classified 132 of 285 (46.3%) lesions as benign without misclassifying any malignant lesion. Together, CAT and CAD yielded significantly fewer false-positive lesions, 53 of 109 (48.6%) and 89 of 109 (78.9%), respectively ( P = 0.001), than radiological reading alone.

Cardiovascular parameters on computed tomography are independently associated with in-hospital complications and outcomes in level-1 trauma patients.

BACKGROUND: In-hospital complications after trauma may result in prolonged stays, higher costs, and adverse functional outcomes. Among reported risk factors for complications are pre-existing cardiopulmonary comorbidities. Objective and quick evaluation of cardiovascular risk would be beneficial for risk assessment in trauma patients. Studies in non-trauma patients suggested an independent association between cardiovascular abnormalities visible on routine computed tomography (CT) imaging and outcomes. However, whether this applies to trauma patients is unknown. PURPOSE: To assess the association between cardiopulmonary abnormalities visible on routine CT images and the development of in-hospital complications in patients in a level-1 trauma center. METHODS: All trauma patients aged 16 years or older with CT imaging of the abdomen, thorax, or spine and admitted to the UMC Utrecht in 2017 were included. Patients with an active infection upon admission or severe neurological trauma were excluded. Routine trauma CT images were analyzed for visible abnormalities: pulmonary emphysema, coronary artery calcifications, and abdominal aorta calcification severity. Drug-treated complications were scored. The discharge condition was measured on the Glasgow Outcome Scale. RESULTS: In total, 433 patients (median age 50 years, 67% male, 89% ASA 1-2) were analyzed. Median Injury Severity Score and Glasgow Coma Scale score were 9 and 15, respectively. Seventy-six patients suffered from at least one complication, mostly pneumonia (n = 39, 9%) or delirium (n = 19, 4%). Left main coronary artery calcification was independently associated with the development of any complication (OR 3.9, 95% CI 1.7-8.9). An increasing number of calcified coronary arteries showed a trend toward an association with complications (p = 0.07) and was significantly associated with an adverse discharge condition (p = 0.02). Pulmonary emphysema and aortic calcifications were not associated with complications. CONCLUSION: Coronary artery calcification, visible on routine CT imaging, is independently associated with in-hospital complications and an adverse discharge condition in level-1 trauma patients. The findings of this study may help to identify trauma patients quickly and objectively at risk for complications in an early stage without performing additional diagnostics or interventions.

Computed tomographic bone mineral density is independently associated with adverse in-hospital outcomes in Dutch level-1 trauma patients.

BACKGROUND: Aging, inactivity, and malnutrition are risk factors for adverse in-hospital outcomes and can manifest in bone loss. Use of bone mineral density (BMD) as an objective marker might improve early identification of patients at risk for complications. AIM: To assess the association of computed tomography (CT) determined BMD values of the first lumbar vertebra with in-hospital complications and outcomes in trauma patients. METHODS: All consecutive hospitalized trauma patients (≥ 16 years) that underwent CT-imaging within 7 days of admission in 2017 were included. Patients with an active infection or antibiotic treatment upon admission, severe neurologic trauma, or an unassessable vertebra were excluded. BMD at the first lumbar vertebra was determined with CT by placing a circular region of interest in homogeneous trabecular bone to obtain mean Hounsfield Units (HU). Regression analyses were performed to assess the association of BMD with in-hospital complications and outcomes. RESULTS: In total, 410 patients were included (median age: 49 years [interquartile range 30-64], 68.3% men, mean BMD 159 ± 66 HU). A total of 94 complications, primarily infection-related, were registered in 74 patients. After adjustment for covariates, a decrease of BMD by one standard deviation was significantly associated with increased risk of complications (odds ratio [OR] 1.9, 95% confidence interval [CI] 1.1-3.1), pneumonia (OR 2.2, 95% CI 1.2-4.5), delirium (OR 4.5, 95% CI 1.7-13.5), and intensive care unit (ICU) admission (OR 1.8, 95% CI 1.1-2.9). CONCLUSION: Bone mineral density of the first lumbar vertebra is independently associated with in-hospital complications, pneumonia, delirium, and ICU admission. These findings could help identify patients at risk early.

Fluorescent Indocyanine Green versus Technetium-99m and Blue Dye for Bilateral SENTinel Lymph Node Detection in Stage I-IIA Cervical Cancer (FluoreSENT): protocol for a non-inferiority study.

INTRODUCTION: Nowadays, two predominant methods for detecting sentinel lymph nodes (SLNs) in cervical cancer are in use. The most conventional method is a combination of a radiotracer, technetium-99m (99mTc) and blue dye. More recently, another method for SLN mapping using indocyanine green (ICG) is becoming widely accepted. ICG is a fluorescent dye, visualised intraoperatively with near-infrared (NIR) fluorescence imaging, providing real-time visual navigation. The presumed advantages of ICG over 99mTc, that is, being cheaper, non-radioactive and logistically more attractive, are only valuable if its detection rate proves to be at least non-inferior. Before omitting the well-functioning and evidence-based combined approach of 99mTc and blue dye, we aim to provide prospective evidence on the non-inferiority of ICG with NIR fluorescence imaging. METHODS AND ANALYSIS: We initiated a prospective non-inferiority study with a paired comparison of both SLN methods in a single sample of 101 patients with International Federation of Gynecology and Obstetrics (FIGO) stage IA-IB2 or IIA1 cervical cancer receiving primary surgical treatment. All patients undergo SLN mapping with ICG and NIR fluorescence imaging in adjunct to mapping with 99mTc (including single photon emission computed tomography with X-ray computed tomography (SPECT/CT)) and blue dye. Surgeons start SLN detection with ICG while being blinded for the preoperative outcome of SPECT/CT to avoid biased detection with ICG. Primary endpoint of this study is bilateral SLN detection rate of both methods (ie, detection of at least one SLN in each hemipelvis). Since we compare strategies for SLN mapping that are already applied in current daily practice for different types of cancer, no additional risks or burdens are expected from these study procedures. ETHICS AND DISSEMINATION: The current study is approved by the Medical Ethics Research Committee Utrecht (reference number 21-014). Findings arising from this study will be disseminated in peer-reviewed journals, academic conferences and through patient organisations. TRIAL REGISTRATION NUMBER: NL9011 and EudraCT 2020-005134-15.

Exposure-Response Analysis of Osimertinib in EGFR Mutation Positive Non-Small Cell Lung Cancer Patients in a Real-Life Setting.

BACKGROUND: Osimertinib, an irreversible inhibitor of the epidermal growth factor receptor (EGFR) is an important drug in the treatment of EGFR-mutation positive non-small cell lung cancer (NSCLC). Clinical trials with osimertinib could not demonstrate an exposure-efficacy relationship, while a relationship between exposure and toxicity has been found. In this study, we report the exposure-response relationships of osimertinib in a real-life setting. METHODS: A retrospective observational cohort study was performed, including patients receiving 40 - 80 mg osimertinib as ≥ 2 line therapy and from whom pharmacokinetic samples were collected during routine care. Trough plasma concentrations (Cmin,pred) were estimated and used as a measure of osimertinib exposure. A previously defined exploratory pharmacokinetic threshold of 166 µg/L was taken to explore the exposure-efficacy relationship. RESULTS: A total of 145 patients and 513 osimertinib plasma concentration samples were included. Median progression free survival (PFS) was 13.3 (95% confidence interval (CI):10.3 - 19.1) months and 9.3 (95% CI: 7.2 - 11.1) months for patients with Cmin,pred < 166 µg/L and Cmin,pred ≥ 166 µg/L, respectively (p = 0.03). In the multivariate analysis, a Cmin,pred < 166 µg/L resulted in a non-statistically significant hazard ratio of 1.10 (95% CI: 0.60 - 2.01; p = 77). Presence of a EGFR driver-mutation other than the exon 19 del or L858R mutations, led to a shorter PFS with a hazard ratio of 2.89 (95% CI: 1.18 - 7.08; p = 0.02). No relationship between exposure and toxicity was observed (p = 0.91). CONCLUSION: In our real-life cohort, no exposure-response relationship was observed for osimertinib in the current dosing scheme. The feasibility of a standard lower fixed dosing of osimertinib in clinical practice should be studied prospectively.

Dynamic Contrast-enhanced and Diffusion-weighted Magnetic Resonance Imaging for Response Evaluation After Single-Dose Ablative Neoadjuvant Partial Breast Irradiation.

Purpose: We aimed to evaluate changes in dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance imaging (MRI) scans acquired before and after single-dose ablative neoadjuvant partial breast irradiation (NA-PBI), and explore the relation between semiquantitative MRI parameters and radiologic and pathologic responses. Methods and Materials: We analyzed 3.0T DCE and DW-MRI of 36 patients with low-risk breast cancer who were treated with single-dose NA-PBI, followed by breast-conserving surgery 6 or 8 months later. MRI was acquired before NA-PBI and 1 week, 2, 4, and 6 months after NA-PBI. Breast radiologists assessed the radiologic response and breast pathologists scored the pathologic response after surgery. Patients were grouped as either pathologic responders or nonresponders (<10% vs ≥10% residual tumor cells). The semiquantitative MRI parameters evaluated were time to enhancement (TTE), 1-minute relative enhancement (RE1min), percentage of enhancing voxels (%EV), distribution of washout curve types, and apparent diffusion coefficient (ADC). Results: In general, the enhancement increased 1 week after NA-PBI (baseline vs 1 week median - TTE: 15s vs 10s; RE1min: 161% vs 197%; %EV: 47% vs 67%) and decreased from 2 months onward (6 months median - TTE: 25s; RE1min: 86%; %EV: 12%). Median ADC increased from 0.83 × 10-3 mm2/s at baseline to 1.28 × 10-3 mm2/s at 6 months. TTE, RE1min, and %EV showed the most potential to differentiate between radiologic responses, and TTE, RE1min, and ADC between pathologic responses. Conclusions: Semiquantitative analyses of DCE and DW-MRI showed changes in relative enhancement and ADC 1 week after NA-PBI, indicating acute inflammation, followed by changes indicating tumor regression from 2 to 6 months after radiation therapy. A relation between the MRI parameters and radiologic and pathologic responses could not be proven in this exploratory study.

Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial.

Background Supplemental screening with MRI has proved beneficial in women with extremely dense breasts. Most MRI examinations show normal anatomic and physiologic variation that may not require radiologic review. Thus, ways to triage these normal MRI examinations to reduce radiologist workload are needed. Purpose To determine the feasibility of an automated triaging method using deep learning (DL) to dismiss the highest number of MRI examinations without lesions while still identifying malignant disease. Materials and Methods This secondary analysis of data from the Dense Tissue and Early Breast Neoplasm Screening, or DENSE, trial evaluated breast MRI examinations from the first screening round performed in eight hospitals between December 2011 and January 2016. A DL model was developed to differentiate between breasts with lesions and breasts without lesions. The model was trained to dismiss breasts with normal phenotypical variation and to triage lesions (Breast Imaging Reporting and Data System [BI-RADS] categories 2-5) using eightfold internal-external validation. The model was trained on data from seven hospitals and tested on data from the eighth hospital, alternating such that each hospital was used once as an external test set. Performance was assessed using receiver operating characteristic analysis. At 100% sensitivity for malignant disease, the fraction of examinations dismissed from radiologic review was estimated. Results A total of 4581 MRI examinations of extremely dense breasts from 4581women (mean age, 54.3 years; interquartile range, 51.5-59.8 years) were included. Of the 9162 breasts, 838 had at least one lesion (BI-RADS category 2-5, of which 77 were malignant) and 8324 had no lesions. At 100% sensitivity for malignant lesions, the DL model considered 90.7% (95% CI: 86.7, 94.7) of the MRI examinations with lesions to be nonnormal and triaged them to radiologic review. The DL model dismissed 39.7% (95% CI: 30.0, 49.4) of the MRI examinations without lesions. The DL model had an average area under the receiver operating characteristic curve of 0.83 (95% CI: 0.80, 0.85) in the differentiation between normal breast MRI examinations and MRI examinations with lesions. Conclusion Automated analysis of breast MRI examinations in women with dense breasts dismissed nearly 40% of MRI scans without lesions while not missing any cancers. ClinicalTrials.gov: NCT01315015 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Joe in this issue.

Indocyanine green versus technetium-99m with blue dye for sentinel lymph node detection in early-stage cervical cancer: A systematic review and meta-analysis.

BACKGROUND: The fluorescent dye indocyanine green (ICG) has emerged as a promising tracer for intraoperative detection of sentinel lymph nodes (SLNs) in early-stage cervical cancer. Although researchers suggest the SLN detection of ICG is equal to the more conventional combined approach of a radiotracer and blue dye, no consensus has been reached. AIMS: We aimed to assess the differences in overall and bilateral SLN detection rates with ICG versus the combined approach, the radiotracer technetium-99m (99m Tc) with blue dye. METHODS AND RESULTS: We searched MEDLINE, Embase, and the Cochrane Library from inception to January 1, 2020 and included studies reporting on a comparison of SLN detection with ICG versus 99m Tc with blue dye in early-stage cervical cancer. The overall and bilateral detection rates were pooled with random-effects meta-analyses. From 118 studies retrieved seven studies (one cross-sectional; six retrospective cohorts) were included, encompassing 589 patients. No significant differences were found in the pooled overall SLN detection rate of ICG versus 99m Tc with blue dye. Meta-analyses of all studies showed ICG to result in a higher bilateral SLN detection rate than 99m Tc with blue dye; 90.3% (95%CI, 79.8-100.0%) with ICG versus 73.5% (95%CI, 66.4-80.6%) with 99mTc with blue dye. This resulted in a significant and clinically relevant risk difference of 16.6% (95%CI, 5.3-28.0%). With sensitivity analysis, the risk difference of the bilateral detection rate maintained in favor of ICG but was no longer significant (13.2%, 95%CI -0.8-27.3%). CONCLUSION: ICG appears to provide higher bilateral SLN detection rates compared to 99m Tc with blue dye in patients with early-stage cervical cancer. However, in adherence with the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) guidelines, the quality of evidence is too low to provide strong recommendations and directly omit the combined approach of 99m Tc with blue dye.

Cost-Effectiveness of Magnetic Resonance Imaging Screening for Women With Extremely Dense Breast Tissue.

BACKGROUND: Extremely dense breast tissue is associated with increased breast cancer risk and limited sensitivity of mammography. The DENSE trial showed that additional magnetic resonance imaging (MRI) screening in women with extremely dense breasts resulted in a substantial reduction in interval cancers. The cost-effectiveness of MRI screening for these women is unknown. METHODS: We used the MISCAN-breast microsimulation model to simulate several screening protocols containing mammography and/or MRI to estimate long-term effects and costs. The model was calibrated using results of the DENSE trial and adjusted to incorporate decreases in breast density with increasing age. Screening strategies varied in the number of MRIs and mammograms offered to women ages 50-75 years. Outcomes were numbers of breast cancers, life-years, quality-adjusted life-years (QALYs), breast cancer deaths, and overdiagnosis. Incremental cost-effectiveness ratios (ICERs) were calculated (3% discounting), with a willingness-to-pay threshold of €22 000. RESULTS: Calibration resulted in a conservative fit of the model regarding MRI detection. Both strategies of the DENSE trial were dominated (biennial mammography; biennial mammography plus MRI). MRI alone every 4 years was cost-effective with €15 620 per QALY. Screening every 3 years with MRI alone resulted in an incremental cost-effectiveness ratio of €37 181 per QALY. All strategies with mammography and/or a 2-year interval were dominated because other strategies resulted in more additional QALYs per additional euro. Alternating mammography and MRI every 2 years was close to the efficiency frontier. CONCLUSIONS: MRI screening is cost-effective for women with extremely dense breasts, when applied at a 4-year interval. For a willingness to pay more than €22 000 per QALY gained, MRI at a 3-year interval is cost-effective as well.

Reducing False-Positive Screening MRI Rate in Women with Extremely Dense Breasts Using Prediction Models Based on Data from the DENSE Trial.

Background High breast density increases breast cancer risk and lowers mammographic sensitivity. Supplemental MRI screening improves cancer detection but increases the number of false-positive screenings. Thus, methods to distinguish true-positive MRI screening results from false-positive ones are needed. Purpose To build prediction models based on clinical characteristics and MRI findings to reduce the rate of false-positive screening MRI findings in women with extremely dense breasts. Materials and Methods Clinical characteristics and MRI findings in Dutch breast cancer screening participants (age range, 50-75 years) with positive first-round MRI screening results (Breast Imaging Reporting and Data System 3, 4, or 5) after a normal screening mammography with extremely dense breasts (Volpara density category 4) were prospectively collected within the randomized controlled Dense Tissue and Early Breast Neoplasm Screening (DENSE) trial from December 2011 through November 2015. In this secondary analysis, prediction models were built using multivariable logistic regression analysis to distinguish true-positive MRI screening findings from false-positive ones. Results Among 454 women (median age, 52 years; interquartile range, 50-57 years) with a positive MRI result in a first supplemental MRI screening round, 79 were diagnosed with breast cancer (true-positive findings), and 375 had false-positive MRI results. The full prediction model (area under the receiver operating characteristics curve [AUC], 0.88; 95% CI: 0.84, 0.92), based on all collected clinical characteristics and MRI findings, could have prevented 45.5% (95% CI: 39.6, 51.5) of false-positive recalls and 21.3% (95% CI: 15.7, 28.3) of benign biopsies without missing any cancers. The model solely based on readily available MRI findings and age had a comparable performance (AUC, 0.84; 95% CI: 0.79, 0.88; P = .15) and could have prevented 35.5% (95% CI: 30.4, 41.1) of false-positive MRI screening results and 13.0% (95% CI: 8.8, 18.6) of benign biopsies. Conclusion Prediction models based on clinical characteristics and MRI findings may be useful to reduce the false-positive first-round screening MRI rate and benign biopsy rate in women with extremely dense breasts. Clinical trial registration no. NCT01315015 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Imbriaco in this issue.

Robot-assisted laparoscopic debulking surgery for recurrent adult granulosa cell tumors.

Despite an often early diagnosis and effective initial surgical management, one third of adult granulosa cell tumors (aGCTs) eventually, and often repeatedly, recurs. Debulking surgery remains the preferred treatment modality for recurrent aGCT, although the risk of intraoperative complications increases with repeated laparotomy. Minimally invasive surgery may limit the risk of complications. We aim to share our initial experience with robotic debulking surgery for recurrent aGCT. Clinical and surgical data of patients with recurrent aGCT who underwent robotic cytoreductive surgery over a three-year period at a tertiary referral center were retrospectively collected and analyzed. Between 2017 and 2020, three patients underwent robotic debulking surgery for recurrent aGCT at our institution. Complete cytoreduction was achieved in all patients. No intraoperative or postoperative complications were reported. This small pilot series at a single academic institution suggests that robot-assisted laparoscopy may be feasible and safe in selected patients with recurrent aGCT. A minimally invasive approach could reduce the complexity of successive surgeries for aGCT relapse.