The Effect of Neutropenia and Filgrastim (G-CSF) on Cancer Patients With Coronavirus Disease 2019 (COVID-19) Infection.

BACKGROUND: Neutropenia is commonly encountered in cancer patients. Recombinant human granulocyte colony-stimulating factor (G-CSF, filgrastim), a cytokine that initiates proliferation and differentiation of mature granulocytes, is widely given to oncology patients to counteract neutropenia, reducing susceptibility to infection. However, the clinical impact of neutropenia and G-CSF use in cancer patients with coronavirus disease 2019 (COVID-19) remains unknown. METHODS: An observational cohort of 379 actively treated cancer patients with COVID-19 was assembled to investigate links between concurrent neutropenia and G-CSF administration on COVID-19-associated respiratory failure and death. These factors were encoded as time-dependent predictors in an extended Cox model, controlling for age and underlying cancer diagnosis. To determine whether the degree of granulocyte response to G-CSF affected outcomes, the degree of response to G-CSF, based on rise in absolute neutrophil count (ANC) 24 hours after growth factor administration, was also incorporated into a similar Cox model. RESULTS: In the setting of active COVID-19 infection, outpatient receipt of G-CSF led to an increased number of hospitalizations (hazard ratio [HR]: 3.54, 95% confidence interval [CI]: 1.25-10.0, P value: .017). Furthermore, among inpatients, G-CSF administration was associated with increased need for high levels of oxygen supplementation and death (HR: 3.56, 95% CI: 1.19-10.2, P value: .024). This effect was predominantly seen in patients that exhibited a high response to G-CSF based on their ANC increase post-G-CSF administration (HR: 7.78, 95% CI: 2.05-27.9, P value: .004). CONCLUSIONS: The potential risks versus benefits of G-CSF administration should be considered in neutropenic cancer patients with COVID-19, because G-CSF administration may lead to worsening clinical and respiratory status.

CT-based Radiogenomic Analysis of Clinical Stage I Lung Adenocarcinoma with Histopathologic Features and Oncologic Outcomes.

Background A preoperative predictive model is needed that can be used to identify patients with lung adenocarcinoma (LUAD) who have a higher risk of recurrence or metastasis. Purpose To investigate associations between CT-based radiomic consensus clustering of stage I LUAD and clinical-pathologic features, genomic data, and patient outcomes. Materials and Methods Patients who underwent complete surgical resection for LUAD from April 2014 to December 2017 with preoperative CT and next-generation sequencing data were retrospectively identified. Comprehensive radiomic analysis was performed on preoperative CT images; tumors were classified as solid, ground glass, or mixed. Patients were clustered into groups based on their radiomics features using consensus clustering, and clusters were compared with tumor genomic alterations, histopathologic features, and recurrence-specific survival (Kruskal-Wallis test for continuous data, χ2 or Fisher exact test for categorical data, and log-rank test for recurrence-specific survival). Cluster analysis was performed on the entire cohort and on the solid, ground-glass, and mixed lesion subgroups. Results In total, 219 patients were included in the study (median age, 68 years; interquartile range, 63-74 years; 150 [68%] women). Four radiomic clusters were identified. Cluster 1 was associated with lepidic, acinar, and papillary subtypes (76 of 90 [84%]); clusters 2 (13 of 50 [26%]) and 4 (13 of 45 [29%]) were associated with solid and micropapillary subtypes (P < .001). The EGFR alterations were highest in cluster 1 (38 of 90 [42%], P = .004). Clusters 2, 3, and 4 were associated with lymphovascular invasion (19 of 50 [38%], 14 of 34 [41%], and 28 of 45 [62%], respectively; P < .001) and tumor spread through air spaces (32 of 50 [64%], 21 of 34 [62%], and 31 of 45 [69%], respectively; P < .001). STK11 alterations (14 of 45 [31%]; P = .006), phosphoinositide 3-kinase pathway alterations (22 of 45 [49%], P < .001), and risk of recurrence (log-rank P < .001) were highest in cluster 4. Conclusion CT-based radiomic consensus clustering enabled identification of associations between radiomic features and clinicalpathologic and genomic features and outcomes in patients with clinical stage I lung adenocarcinoma. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Nishino in this issue.

Outcomes of Patients with COVID-19 from a Specialized Cancer Care Emergency Room.

PURPOSE: Our goal was to identify discrete clinical characteristics associated with safe discharge from an emergency department/urgent care for patients with a history of cancer and concurrent COVID-19 infection during the SARS-CoV-2 pandemic and prior to widespread vaccination. PATIENTS AND METHODS: We retrospectively analyzed 255 adult patients with a history of cancer who presented to Memorial Sloan Kettering Cancer Center (MSKCC) urgent care center (UCC) from March 1, 2020 to May 31, 2020 with concurrent COVID-19 infection. We evaluated associations between patient characteristics and 30-day mortality from initial emergency department (ED) or urgent care center (UCC) visit and the absence of a severe event within 30 days. External validation was performed on a retrospective data from 29 patients followed at Fred Hutchinson Cancer Research Center that presented to the local emergency department. A late cohort of 108 additional patients at MSKCC from June 1, 2020 to January 31, 2021 was utilized for further validation. RESULTS: In the MSKCC cohort, 30-day mortality and severe event rate was 15% and 32% respectively. Using stepwise regression analysis, elevated BUN and glucose, anemia, and tachypnea were selected as the main predictors of 30-day mortality. Conversely, normal albumin, BUN, calcium, and glucose, neutrophil-lymphocyte ratio <3, lack of (severe) hypoxia, lack of bradycardia or tachypnea, and negative imaging were selected as the main predictors of an uneventful course as defined as a Lack Of a Severe Event within Thirty Days (LOSETD). Utilizing this information, we devised a tool to predict 30-day mortality and LOSETD which achieved an area under the operating curve (AUC) of 79% and 74% respectively. Similar estimates of AUC were obtained in an external validation cohort. A late cohort at MSKCC was consistent with the prior, albeit with a lower AUC. CONCLUSION: We identified easily obtainable variables that predict 30-day mortality and the absence of a severe event for patients with a history of cancer and concurrent COVID-19. This has been translated into a bedside tool that the clinician may utilize to assist disposition of this group of patients from the emergency department or urgent care setting.

Frequency and outcomes of MRI-detected axillary adenopathy following COVID-19 vaccination.

OBJECTIVES: To assess the frequency of ipsilateral axillary adenopathy on breast MRI after COVID-19 vaccination. To investigate the duration, outcomes, and associated variables of vaccine-related adenopathy. METHODS: In this retrospective cohort study, our database was queried for patients who underwent breast MRI following COVID-19 vaccination from January 22, 2021, to March 21, 2021. The frequency of ipsilateral axillary adenopathy and possible associated variables were evaluated, including age, personal history of ipsilateral breast cancer, clinical indication for breast MRI, type of vaccine, side of vaccination, number of doses, and number of days between the vaccine and the MRI exam. The outcomes of the adenopathy were investigated, including the duration of adenopathy and biopsy results. RESULTS: A total of 357 patients were included. The frequency of adenopathy on breast MRI was 29% (104/357 patients). Younger patients and shorter time intervals from the second dose of the vaccine were significantly associated with the development of adenopathy (p = 0.002 for both). Most adenopathy resolved or decreased on follow-up, with 11% of patients presenting persistence of adenopathy up to 64 days after the second dose of the vaccine. Metastatic axillary carcinoma was diagnosed in three patients; all three had a current ipsilateral breast cancer diagnosis. CONCLUSIONS: Vaccine-related adenopathy is a frequent event after COVID-19 vaccination; short-term follow-up is an appropriate clinical approach, except in patients with current ipsilateral breast cancer. Adenopathy may often persist 4-8 weeks after the second dose of the vaccine, thus favoring longer follow-up periods. KEY POINTS: • MRI-detected ipsilateral axillary adenopathy is a frequent benign finding after mRNA COVID-19 vaccination. • Axillary adenopathy following COVID-19 vaccination often persists > 4 weeks after vaccination, favoring longer follow-up periods. • In patients with concurrent ipsilateral breast cancer, axillary adenopathy can represent metastatic carcinoma and follow-up is not appropriate.

COVID-19 in patients with cancer: can baseline radiologic severity and early evolution predict clinical outcomes?

OBJECTIVE: To determine whether the degree of parenchymal involvement on chest radiograph (CXR) at the time of COVID-19 diagnosis and its early radiologic evolution can predict adverse events including hospitalization, intubation, and death in patients with cancer. METHODS: Retrospective study of 627 COVID-19-positive patients between March and April 2020, of which 248 had baseline CXR within 72 h of diagnosis and 64 patients had follow-up wihtin72 h. CXRs were classified as abnormal (i.e., radiologic findings suggestive of COVID-19 infection were noted), normal, or indeterminate. Baseline and follow-up severity scores were calculated based on lung regions in abnormal CXRs. Statistical analysis was performed to determine associations between abnormal CXR or severity score with adverse events. RESULTS: Of 248 patients (median age = 65) with a baseline CXR, 172/248 (69%) had an abnormal baseline study, which was associated with hospitalization (p < 0.001), intubation (p = 0.001), and death (p = 0.005). For patients with solid neoplasms, when adjusted for stage, it was associated with hospitalization (p = 0.0002), intubation (p = 0.019), and death (p = 0.03). The median baseline severity score was 3 (range = 1-10); the greater the score, the higher the likelihood of adverse outcome (p < 0.003 for all). A baseline severity score > 9 predicted > 50% probability of intubation and a score of ≥ 10 predicted > 50% of probability of death. The baseline severity score was not correlated with cancer-related treatment. Early radiologic progression was not correlated with hospitalization, intubation, or death. CONCLUSION: The degree of parenchymal involvement on CXR within 72 h of COVID-19 diagnosis is associated with adverse outcomes in patients with cancer. KEY POINTS: • In patients with cancer, the presence and severity of radiologic manifestation of COVID-19 on chest radiographs within 72 h of COVID-19 diagnosis are associated with hospitalization, intubation, and death. • Early radiologic progression on chest radiographs is not correlated with adverse outcomes.

Multidisciplinary Recommendations Regarding Post-Vaccine Adenopathy and Radiologic Imaging: Radiology Scientific Expert Panel.

Vaccination-associated adenopathy is a frequent imaging finding after administration of COVID-19 vaccines that may lead to a diagnostic conundrum in patients with manifest or suspected cancer, in whom it may be indistinguishable from malignant nodal involvement. To help the medical community address this concern in the absence of studies and evidence-based guidelines, this special report offers recommendations developed by a multidisciplinary panel of experts from three of the leading tertiary care cancer centers in the United States. According to these recommendations, some routine imaging examinations, such as those for screening, should be scheduled before or at least 6 weeks after the final vaccination dose to allow for any reactive adenopathy to resolve. However, there should be no delay of other clinically indicated imaging (eg, for acute symptoms, short-interval treatment monitoring, urgent treatment planning or complications) due to prior vaccination. The vaccine should be administered on the side contralateral to the primary or suspected cancer, and both doses should be administered in the same arm. Vaccination information-date(s) administered, injection site(s), laterality, and type of vaccine-should be included in every preimaging patient questionnaire, and this information should be made readily available to interpreting radiologists. Clear and effective communication between patients, radiologists, referring physician teams, and the general public should be considered of the highest priority when managing adenopathy in the setting of COVID-19 vaccination.

Perfusion defects on dual-energy CTA in patients with suspected pulmonary embolism correlate with right heart strain and lower survival.

OBJECTIVES: To evaluate the utility of perfusion defects on dual-energy CT angiograms (DECTA) in assessing the clinical severity of pulmonary embolism (PE). METHODS: We retrospectively reviewed 1136 consecutive diagnostic DECTA exams performed on patients with suspected PE between January 2014 and September 2014. Presence and location of obstructive and non-obstructive PE, right ventricular to left ventricular ratio (RV/LV ratio), and inferior vena cava (IVC) backflow were recorded. Iodine maps were reviewed to establish the presence of perfusion defect and its extent was determined through a score-based segmental impaired perfusion. Subsequently, the perfusion defect scores were correlated with clinical parameters including vital signs, electrocardiogram (ECG) abnormalities, echocardiogram findings, troponin, and brain natriuretic peptide (bnp) levels. Clinical information regarding primary cancer diagnosis, oncologic stage, and date of death if applicable was also recorded. RESULTS: Of the 1136 diagnostic iodine maps, 96 of these patients had perfusion defects on iodine maps. After uni- and multivariate analysis, significant correlation was found between the presence of a perfusion defect and RV/LV ratio (p = 0.05), IVC backflow (p = 0.03), elevated troponin (p = 0.03), and right heart dysfunction as determined on an echocardiogram (p = 0.05). The greater the perfusion defect score, the higher the likelihood of IVC backflow (p = 0.005) and obstructive PE (p = 0.002). When adjusted for oncologic stage, patients with a perfusion defect and a higher perfusion defect score had a higher mortality rate (p = 0.005). CONCLUSION: The presence of a perfusion defect correlates with several parameters evaluating PE severity. A perfusion defect and higher perfusion defect score were associated with a lower survival. KEY POINTS: • Detection of perfusion defects on dual-energy CT angiograms and its extent correlates with right heart strain in the setting of pulmonary embolism. • The presence and extent of a perfusion defect in patients with pulmonary embolism are associated with lower survival.

Risk stratification of cardiac metastases using late gadolinium enhancement cardiovascular magnetic resonance: prognostic impact of hypo-enhancement evidenced tumor avascularity.

BACKGROUND: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is widely used to identify cardiac neoplasms, for which diagnosis is predicated on enhancement stemming from lesion vascularity: Impact of contrast-enhancement pattern on clinical outcomes is unknown. The objective of this study was to determine whether cardiac metastasis (CMET) enhancement pattern on LGE-CMR impacts prognosis, with focus on heterogeneous lesion enhancement as a marker of tumor avascularity. METHODS: Advanced (stage IV) systemic cancer patients with and without CMET matched (1:1) by cancer etiology underwent a standardized CMR protocol. CMET was identified via established LGE-CMR criteria based on lesion enhancement; enhancement pattern was further classified as heterogeneous (enhancing and non-enhancing components) or diffuse and assessed via quantitative (contrast-to-noise ratio (CNR); signal-to-noise ratio (SNR)) analyses. Embolic events and mortality were tested in relation to lesion location and contrast-enhancement pattern. RESULTS: 224 patients were studied, including 112 patients with CMET and unaffected (CMET -) controls matched for systemic cancer etiology/stage. CMET enhancement pattern varied (53% heterogeneous, 47% diffuse). Quantitative analyses were consistent with lesion classification; CNR was higher and SNR lower in heterogeneously enhancing CMET (p < 0.001)-paralleled by larger size based on linear dimensions (p < 0.05). Contrast-enhancement pattern did not vary based on lesion location (p = NS). Embolic events were similar between patients with diffuse and heterogeneous lesions (p = NS) but varied by location: Patients with right-sided lesions had threefold more pulmonary emboli (20% vs. 6%, p = 0.02); those with left-sided lesions had lower rates equivalent to controls (4% vs. 5%, p = 1.00). Mortality was higher among patients with CMET (hazard ratio [HR] = 1.64 [CI 1.17-2.29], p = 0.004) compared to controls, but varied by contrast-enhancement pattern: Diffusely enhancing CMET had equivalent mortality to controls (p = 0.21) whereas prognosis was worse with heterogeneous CMET (p = 0.005) and more strongly predicted by heterogeneous enhancement (HR = 1.97 [CI 1.23-3.15], p = 0.005) than lesion size (HR = 1.11 per 10 cm [CI 0.53-2.33], p = 0.79). CONCLUSIONS: Contrast-enhancement pattern and location of CMET on CMR impacts prognosis. Embolic events vary by CMET location, with likelihood of PE greatest with right-sided lesions. Heterogeneous enhancement-a marker of tumor avascularity on LGE-CMR-is a novel marker of increased mortality risk.

Projecting COVID-19 disease severity in cancer patients using purposefully-designed machine learning.

BACKGROUND: Accurately predicting outcomes for cancer patients with COVID-19 has been clinically challenging. Numerous clinical variables have been retrospectively associated with disease severity, but the predictive value of these variables, and how multiple variables interact to increase risk, remains unclear. METHODS: We used machine learning algorithms to predict COVID-19 severity in 348 cancer patients at Memorial Sloan Kettering Cancer Center in New York City. Using only clinical variables collected on or before a patient's COVID-19 positive date (time zero), we sought to classify patients into one of three possible future outcomes: Severe-early (the patient required high levels of oxygen support within 3 days of being tested positive for COVID-19), Severe-late (the patient required high levels of oxygen after 3 days), and Non-severe (the patient never required oxygen support). RESULTS: Our algorithm classified patients into these classes with an area under the receiver operating characteristic curve (AUROC) ranging from 70 to 85%, significantly outperforming prior methods and univariate analyses. Critically, classification accuracy is highest when using a potpourri of clinical variables - including basic patient information, pre-existing diagnoses, laboratory and radiological work, and underlying cancer type - suggesting that COVID-19 in cancer patients comes with numerous, combinatorial risk factors. CONCLUSIONS: Overall, we provide a computational tool that can identify high-risk patients early in their disease progression, which could aid in clinical decision-making and selecting treatment options.

Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.

BACKGROUND: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is widely employed for flow quantification, but analysis typically requires time consuming manual segmentation which can require human correction. Advances in machine learning have markedly improved automated processing, but have yet to be applied to PC-CMR. This study tested a novel machine learning model for fully automated analysis of PC-CMR aortic flow. METHODS: A machine learning model was designed to track aortic valve borders based on neural network approaches. The model was trained in a derivation cohort encompassing 150 patients who underwent clinical PC-CMR then compared to manual and commercially-available automated segmentation in a prospective validation cohort. Further validation testing was performed in an external cohort acquired from a different site/CMR vendor. RESULTS: Among 190 coronary artery disease patients prospectively undergoing CMR on commercial scanners (84% 1.5T, 16% 3T), machine learning segmentation was uniformly successful, requiring no human intervention: Segmentation time was < 0.01 min/case (1.2 min for entire dataset); manual segmentation required 3.96 ± 0.36 min/case (12.5 h for entire dataset). Correlations between machine learning and manual segmentation-derived flow approached unity (r = 0.99, p < 0.001). Machine learning yielded smaller absolute differences with manual segmentation than did commercial automation (1.85 ± 1.80 vs. 3.33 ± 3.18 mL, p < 0.01): Nearly all (98%) of cases differed by ≤5 mL between machine learning and manual methods. Among patients without advanced mitral regurgitation, machine learning correlated well (r = 0.63, p < 0.001) and yielded small differences with cine-CMR stroke volume (∆ 1.3 ± 17.7 mL, p = 0.36). Among advanced mitral regurgitation patients, machine learning yielded lower stroke volume than did volumetric cine-CMR (∆ 12.6 ± 20.9 mL, p = 0.005), further supporting validity of this method. Among the external validation cohort (n = 80) acquired using a different CMR vendor, the algorithm yielded equivalently small differences (∆ 1.39 ± 1.77 mL, p = 0.4) and high correlations (r = 0.99, p < 0.001) with manual segmentation, including similar results in 20 patients with bicuspid or stenotic aortic valve pathology (∆ 1.71 ± 2.25 mL, p = 0.25). CONCLUSION: Fully automated machine learning PC-CMR segmentation performs robustly for aortic flow quantification - yielding rapid segmentation, small differences with manual segmentation, and identification of differential forward/left ventricular volumetric stroke volume in context of concomitant mitral regurgitation. Findings support use of machine learning for analysis of large scale CMR datasets.

Dual-Energy CT Angiography for Detection of Pulmonary Emboli: Incremental Benefit of Iodine Maps.

Purpose To determine if there is added benefit of using iodine maps from dual-energy (DE) CT in addition to conventional CT angiography images to diagnose pulmonary embolism (PE). Materials and Methods In this retrospective analysis, 1144 consecutive dual-energy CT angiography examinations performed from January through September 2014 at an oncologic referral center to evaluate for PE were reviewed. The 1144 examinations included 1035 patients (mean age, 58.7 years; range, 15-99 years). First, the location, level, and type (occlusive vs nonocclusive) of PEs on conventional CT angiograms were recorded. Iodine maps were then reviewed for defects suggestive of PE. Last, CT angiograms were rereviewed to detect additional PEs suggested by the iodine map. Consensus reviews were performed for examinations with PEs. The confidence interval of percentages was calculated by using the Clopper-Pearson method. Results On 147 of 1144 (12.8%) CT angiograms, a total of 372 PEs were detected at initial review. After review of the DE CT iodine map, 27 additional PEs were found on 26 of 1144 CT angiograms (2.3%; 95% confidence interval [CI]: 1.5%, 3.3%). Of the 27 additional PEs, six (22.2%) were segmental, 21 (77.8%) were subsegmental, 24 (88.9%) were occlusive, and three (11.1%) were nonocclusive. Eleven of 1144 (1.0%; 95% CI: 0.5%, 1.7%) CT angiograms had a new diagnosis of PE after review of the DE CT iodine maps. Conclusion Dual-energy CT iodine maps show a small incremental benefit for the detection of occlusive segmental and subsegmental pulmonary emboli. © RSNA, 2018.

AACE/ACE disease state clinical review: pancreatic neuroendocrine incidentalomas.

Incidental detection of pancreatic neuroendocrine tumors (PNETs) has substantially increased over the last decade due to widespread use of advanced imaging studies. Reliable initial imaging-based characterization is crucial for the differential diagnosis from other exocrine neoplasms and to determine the appropriate management plan. Measurements of chromogranin A, pancreatic polypeptide, and calcitonin are recommended for the biochemical evaluation. A thorough medical history needs to be performed to rule out multiple endocrine neoplasia (MEN) type 1. The European Neuroendocrine Tumor Society (ENETS)/Tumor Node Metastasis (TNM) staging system together with a grading based on the Ki-67 proliferation index and mitotic counts has proven to give more appropriate prognostic information than the World Health Organization (WHO)/American Joint Committee on Cancer (AJCC) TNM staging but may still fail to safely differentiate benign from malignant lesions. Poorly differentiated PNETs generally present with metastases and are rarely amenable for resection. Well- or intermediately differentiated tumors ≥2 cm with imaging evidence of malignancy or with a Ki-67 >2% should be resected. It has been suggested that non-MEN related, nonfunctioning, and asymptomatic PNETs <2 cm with a Ki-67 index ≤2% carry a low risk of metastasis and may be observed in the absence of clinical or radiologic criteria of malignancy or progression, especially in older patients. However, because metastases may occur with long delay with smaller PNETS, physicians should consider patient age, lesion location, and the risks of operation, and patients not undergoing surgery need to be closely followed closely.

Body oncologic imaging subspecialty training a curriculum based on the experience in a tertiary cancer center.

PURPOSE: To describe the structure of a dedicated body oncologic imaging fellowship program. To summarize the numbers and types of cross-sectional imaging examinations reported by fellows. METHODS: The curriculum, training methods, and assessment measures utilized in the program were reviewed and described. An educational retrospective analysis was conducted. Data on the number of examinations interpreted by fellows, breakdown of modalities, and examinations by disease management team (DMT) were collected. RESULTS: A total of 38 fellows completed the fellowship program during the study period. The median number of examinations reported per fellow was 2296 [interquartile range: 2148 - 2534], encompassing all oncology-relevant imaging modalities: CT 721 [646-786], MRI 1158 [1016-1309], ultrasound 256 [209-320] and PET/CT 176 [130-202]. The breakdown of examinations by DMT revealed variations in imaging patterns, with MRIs most frequently interpreted for genitourinary, musculoskeletal, and hepatobiliary cancers, and CTs most commonly for general staging or assessment of nonspecific symptoms. CONCLUSION: This descriptive analysis may serve as a foundation for the development of similar fellowship programs and the advancement of body oncologic imaging. The volume and diversity of examinations reported by fellows highlights the comprehensive nature of body oncologic imaging.

Percutaneous biopsy of focal lesions of the gastrointestinal tract.

PURPOSE: To evaluate the technical success and diagnostic accuracy of image-guided percutaneous biopsy of the gastrointestinal (GI) tract. MATERIALS AND METHODS: An interventional radiology database was used to retrospectively identify patients who underwent image-guided percutaneous biopsy of the GI tract. The medical and imaging records were reviewed to assess biopsy results and complications. RESULTS: Twenty-nine patients (M:F = 19:10, mean age 65 years) were identified who underwent image-guided (CT/US) percutaneous biopsies of the GI tract. All biopsies were performed using coaxial technique with 18 g core and 22 g FNA needles. Twenty-two biopsies (76 %) were for circumferential or segmental wall thickening; the remaining were wall thickening with exophytic mass. Mean tumor diameter was 7.4 cm (SD = 3.4 cm), average wall thickening was 2.1 cm (SD 7.2), and exophytic mass was 10.0 cm (SD = 4.2). Tumor locations included stomach (n = 5), small bowel (n = 8), and colon (n = 16). Malignancy was confirmed in 22 patients, 12 of whom underwent excision, with 3 false positive samples. Benign disease was diagnosed in 7 patients, including 3 with pathology confirmation, with one false negative sample. The overall sensitivity was 83 % and accuracy was 84 %. There was one complication presenting as bleeding at the biopsy site, treated conservatively. CONCLUSION: Percutaneous biopsy of the GI tract is an uncommon procedure. The results of this study suggest that it is a safe and sensitive procedure that may be considered for small bowel lesions in which endoscopy is not feasible, for submucosal lesions, or in the setting of patients with previously negative endoscopic biopsies.

Diagnostic accuracy of laxative-free computed tomographic colonography for detection of adenomatous polyps in asymptomatic adults: a prospective evaluation.

BACKGROUND: Colon screening by optical colonoscopy (OC) or computed tomographic colonography (CTC) requires a laxative bowel preparation, which inhibits screening participation. OBJECTIVE: To assess the performance of detecting adenomas 6 mm or larger and patient experience of laxative-free, computer-aided CTC. DESIGN: Prospective test comparison of laxative-free CTC and OC. The CTC included electronic cleansing and computer-aided detection. Optical colonoscopy examinations were initially blinded to CTC results, which were subsequently revealed during colonoscope withdrawal; this method permitted reexamination to resolve discrepant findings. Unblinded OC served as a reference standard. (ClinicalTrials.gov registration number: NCT01200303) SETTING: Multicenter ambulatory imaging and endoscopy centers. PARTICIPANTS: 605 adults aged 50 to 85 years at average to moderate risk for colon cancer. MEASUREMENTS: Per-patient sensitivity and specificity of CTC and first-pass OC for detecting adenomas at thresholds of 10 mm or greater, 8 mm or greater, and 6 mm or greater; per-lesion sensitivity and survey data describing patient experience with preparations and examinations. RESULTS: For adenomas 10 mm or larger, per-patient sensitivity of CTC was 0.91 (95% CI, 0.71 to 0.99) and specificity was 0.85 (CI, 0.82 to 0.88); sensitivity of OC was 0.95 (CI, 0.77 to 1.00) and specificity was 0.89 (CI, 0.86 to 0.91). Sensitivity of CTC was 0.70 (CI, 0.53 to 0.83) for adenomas 8 mm or larger and 0.59 (CI, 0.47 to 0.70) for those 6 mm or larger; sensitivity of OC for adenomas 8 mm or larger was 0.88 (CI, 0.73 to 0.96) and 0.76 (CI, 0.64 to 0.85) for those 6 mm or larger. The specificity of OC at the threshold of 8 mm or larger was 0.91 and at 6 mm or larger was 0.94. Specificity for OC was greater than that for CTC, which was 0.86 at the threshold of 8 mm or larger and 0.88 at 6 mm or larger (P= 0.02). Reported participant experience for comfort and difficulty of examination preparation was better with CTC than OC. LIMITATIONS: There were 3 CTC readers. The survey instrument was not independently validated. CONCLUSION: Computed tomographic colonography was accurate in detecting adenomas 10 mm or larger but less so for smaller lesions. Patient experience was better with laxative-free CTC. These results suggest a possible role for laxative-free CTC as an alternate screening method.

Improving Radiology Oncologic Imaging Trainee Case Diversity through Automatic Examination Assignment: Retrospective Study from a Tertiary Cancer Center.

In a retrospective single-center study, the authors assessed the efficacy of an automated imaging examination assignment system for enhancing the diversity of subspecialty examinations reported by oncologic imaging fellows. The study aimed to mitigate traditional biases of manual case selection and ensure equitable exposure to various case types. Methods included evaluating the proportion of "uncommon" to "common" cases reported by fellows before and after system implementation and measuring the weekly Shannon Diversity Index to determine case distribution equity. The proportion of reported uncommon cases more than doubled from 8.6% to 17.7% in total, at the cost of a concurrent 9.0% decrease in common cases from 91.3% to 82.3%. The weekly Shannon Diversity Index per fellow increased significantly from 0.66 (95% CI: 0.65, 0.67) to 0.74 (95% CI: 0.72, 0.75; P < .001), confirming a more balanced case distribution among fellows after introduction of the automatic assignment. © RSNA, 2023 Keywords: Computer Applications, Education, Fellows, Informatics, MRI, Oncologic Imaging.

Conventional and radiomic features to predict pathology in the preoperative assessment of anterior mediastinal masses.

OBJECTIVES: The aim of this study was to differentiate benign from malignant tumors in the anterior mediastinum based on computed tomography (CT) imaging characteristics, which could be useful in preoperative planning. Additionally, our secondary aim was to differentiate thymoma from thymic carcinoma, which could guide the use of neoadjuvant therapy. MATERIALS AND METHODS: Patients referred for thymectomy were retrospectively selected from our database. Twenty-five conventional characteristics were evaluated by visual analysis, and 101 radiomic features were extracted from each CT. In the step of model training, we applied support vector machines to train classification models. Model performance was assessed using the area under the receiver operating curves (AUC). RESULTS: Our final study sample comprised 239 patients, 59 (24.7 %) with benign mediastinal lesions and 180 (75.3 %) with malignant thymic tumors. Among the malignant masses, there were 140 (58.6 %) thymomas, 23 (9.6 %) thymic carcinomas, and 17 (7.1 %) non-thymic lesions. For the benign versus malignant differentiation, the model that integrated both conventional and radiomic features achieved the highest diagnostic performance (AUC = 0.715), in comparison to the conventional (AUC = 0.605) and radiomic-only (AUC = 0.678) models. Similarly, regarding thymoma versus thymic carcinoma differentiation, the model that integrated both conventional and radiomic features also achieved the highest diagnostic performance (AUC = 0.810), in comparison to the conventional (AUC = 0.558) and radiomic-only (AUC = 0.774) models. CONCLUSION: CT-based conventional and radiomic features with machine learning analysis could be useful for predicting pathologic diagnoses of anterior mediastinal masses. The diagnostic performance was moderate for differentiating benign from malignant lesions and good for differentiating thymomas from thymic carcinomas. The best diagnostic performance was achieved when both conventional and radiomic features were integrated in the machine learning algorithms.

Prognosis of invasive intraductal papillary mucinous neoplasm depends on histological and precursor epithelial subtypes.

OBJECTIVE: Invasive cancers arising from intraductal papillary mucinous neoplasm (IPMN) are recognised as a morphologically and biologically heterogeneous group of neoplasms. Less is known about the epithelial subtypes of the precursor IPMN from which these lesions arise. The authors investigate the clinicopathological characteristics and the impact on survival of both the invasive component and its background IPMN. DESIGN AND PATIENTS: The study cohort comprised 61 patients with invasive IPMN (study group) and 570 patients with pancreatic ductal adenocarcinoma (PDAC, control group) resected at a single institution. Multivariate analyses were performed using a stage-matched Cox proportional hazard model. RESULTS: The histology of invasive components of the IPMN cohort was tubular in 38 (62%), colloid in 16 (26%), and oncocytic in seven (12%). Compared with PDAC, invasive IPMNs were associated with a lower incidence of adverse pathological features and improved mortality by multivariate analysis (HR 0.58; 95% CI 0.39 to 0.86). In subtype analysis, this favourable outcome remained only for colloid and oncocytic carcinomas, while tubular adenocarcinoma was associated with worse overall survival, not significantly different from that of PDAC (HR 0.85; 95% CI 0.53 to 1.36). Colloid and oncocytic carcinomas arose only from intestinal- and oncocytic-type IPMNs, respectively, and were mostly of the main-duct type, whereas tubular adenocarcinomas primarily originated in the gastric background, which was often associated with branch-duct IPMN. Overall survival of patients with invasive adenocarcinomas arising from gastric-type IPMN was significantly worse than that of patients with non-gastric-type IPMN (p=0.016). CONCLUSIONS: Tubular, colloid and oncocytic invasive IPMNs have varying prognosis, and arise from different epithelial subtypes. Colloid and oncocytic types have markedly improved biology, whereas the tubular type has a course that resembles PDAC. Analysis of these subtypes indicates that the background epithelium plays an equally, if not more, important role in defining the biology and prognosis of invasive IPMNs.