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Basophils have emerged in recent years as a small but potent subpopulation of leukocytes capable of bridging innate and adaptive immunity. They can be activated through IgE-dependent and IgE-independent mechanisms to release preformed mediators and to produce Th2 cytokines. In addition to their role in protective immunity to helminths, basophils are major participants in allergic reactions as diverse as anaphylaxis and immediate hypersensitivity reactions, late-phase hypersensitivity reactions, and delayed hypersensitivity reactions. Additionally, basophils have been implicated in the pathophysiology of autoimmune diseases such as lupus nephritis and rheumatoid arthritis, and the modulation of immune responses to bacterial infections, as well as being a feature of myelogenous leukemias. Distinct signals for activation, degranulation, transendothelial migration, and immune regulation are being defined, and demonstrate the important role of basophils in promoting a Th2 microenvironment. These mechanistic insights are driving innovative approaches for diagnostic testing and therapeutic targeting of basophils.

PurposeTo evaluate whether quantitative whole-body (WB) PSMA-PET metrics under long-term androgen deprivation therapy (ADT) and/or androgen receptor signaling inhibitors (ARSi) are associated with PSA progression.MethodsPatients who underwent at least 2 68Ga-PSMA-11 PET/CT scans between October 2016 and April 2021 (n = 372) and started a new line of ADT ± ARSi between PET1 and PET2 were retrospectively screened for inclusion. We investigated the association between PCWG3-defined PSA progression status at PET2 and the following PSMA-PET parameters: appearance of new lesions on PET2, ≥ 20% increase in WB-PSMA tumor volume (WB-PSMA-VOL), progression of disease (PD) by RECIP 1.0, and ≥ 30% increase in WB-PSMA-SUVmean from PET1 to PET2. Spearman’s rank correlation coefficients and Fisher’s exact test were used to evaluate the associations.ResultsThirty-five patients were included: 12/35 (34%) were treated with ADT only and 23/35 (66%) with ARSi ± ADT. The median time between PET1 and PET2 was 539 days. Changes (%) in median PSA levels, WB-PSMA-SUVmean, and WB-PSMA-VOL from PET1 to PET2 were -86%, -23%, and -86%, respectively. WB-PSMA-VOL ≥ 20%, new lesions, RECIP-PD, and WB-PSMA-SUVmean ≥ 30% were observed in 5/35 (14%), 9/35 (26%), 5/35 (14%), and 4/35 (11%) of the whole cohort, in 3/9 (33%), 7/9 (78%), 3/9 (33%), and 2/9 (22%) of patients with PSA progression at PET2, and in 2/26 (8%), 2/26 (8%), 2/26 (8%), and 2/26 (8%) of patients without PSA progression at PET2 (p = 0.058, p < 0.001, p = 0.058, p = 0.238, respectively). Changes in PSA were correlated to percent changes in WB-PSMA-VOL and WB-PSMA-SUVmean (Spearman ρ: 0.765 and 0.633, respectively; p < 0.001).ConclusionChanges in PSA correlated with changes observed on PSMA-PET, although discordance between PSA and PSMA-PET changes was observed. Further research is necessary to evaluate if PSMA-PET parameters can predict progression-free survival and overall survival and serve as novel endpoints in clinical trials.

National Comprehensive Cancer Network guidelines consider 18F-fluciclovine PET-CT for prostate cancer biochemical recurrence localisation after radical prostatectomy, whereas European Association of Urology guidelines recommend prostate-specific membrane antigen (PSMA) PET-CT. To the best of our knowledge, no prospective head-to-head comparison between these tests has been done so far. The aim of this study was to compare prospectively paired 18F-fluciclovine and PSMA PET-CT scans for localising biochemical recurrence of prostate cancer after radical prostatectomy in patients with low prostate-specific antigen (PSA) concentrations (<2·0 ng/mL). This was a prospective, single-centre, open-label, single-arm comparative study done at University of California Los Angeles (Los Angeles, CA, USA). Patients older than 18 years of age with prostate cancer biochemical recurrence after radical prostatectomy and PSA levels ranging from 0·2 to 2·0 ng/mL without any prior salvage therapy and with a Karnofsky performance status of at least 50 were eligible. Patients underwent 18F-fluciclovine (reference test) and PSMA (index test) PET-CT scans within 15 days. Detection rate of biochemical recurrence at the patient level and by anatomical region was the primary endpoint. A statistical power analysis demonstrated that a sample size of 50 patients was needed to show a 22% difference in detection rates in favour of PSMA (test for superiority). Each PET scan was interpreted by three independent masked readers and a consensus majority interpretation was generated (two vs one) to determine positive findings. This study is registered with ClinicalTrials.gov, number NCT03515577, and is complete. Between Feb 26, 2018, and Sept 20, 2018, 143 patients were screened for eligibility, of whom 50 patients were enrolled into the study. Median follow-up was 8 months (IQR 7–9). The primary endpoint was met; detection rates were significantly lower with 18F-fluciclovine PET-CT (13 [26%; 95% CI 15–40] of 50) than with PSMA PET-CT (28 [56%; 41–70] of 50), with an odds ratio (OR) of 4·8 (95% CI 1·6–19·2; p=0·0026) at the patient level; in the subanalysis of the pelvic nodes region (four [8%; 2–19] with 18F-fluciclovine vs 15 [30%; 18–45] with PSMA PET-CT; OR 12·0 [1·8–513·0], p=0·0034); and in the subanalysis of any extrapelvic lesions (none [0%; 0–6] vs eight [16%; 7–29]; OR non-estimable [95% CI non-estimable], p=0·0078). With higher detection rates, PSMA should be the PET tracer of choice when PET-CT imaging is considered for subsequent treatment management decisions in patients with prostate cancer and biochemical recurrence after radical prostatectomy and low PSA concentrations (≤2·0 ng/mL). Further research is needed to investigate whether higher detection rates translate into improved oncological outcomes. None.

Objective To compare texture analysis (TA) features of solid renal masses on renal protocol (non-contrast enhanced [NECT], corticomedullary [CM], nephrographic [NG]) CT. Materials and methods A total of 177 consecutive solid renal masses (116 renal cell carcinoma [RCC]; 51 clear cell [cc], 40 papillary, 25 chromophobe, and 61 benign masses; 49 oncocytomas, 12 fat-poor angiomyolipomas) with three-phase CT between 2012 and 2017 were studied. Two blinded radiologists independently assessed tumor heterogeneity (5-point Likert scale) and segmented tumors. TA features ( N  = 25) were compared between groups and between phases. Accuracy (area under the curve [AUC]) for RCC versus benign and cc-RCC versus other masses was compared. Results Subjectively, tumor heterogeneity differed between phases ( p  < 0.01) and between tumors within the same phase ( p  = 0.03 [NECT] and p  < 0.01 [CM, NG]). Inter-observer agreement was moderate to substantial (intraclass correlation coefficient = 0.55–0.73). TA differed in 92.0% (23/25) features between phases ( p  < 0.05) except for GLNU and f6. More TA features differed significantly on CM (80.0% [20/25]) compared with NG (40.0% [10/25]) and NECT (16.0% [4/25]) ( p  < 0.01). For RCC versus benign, AUCs of texture features did not differ comparing CM and NG ( p  > 0.05), but were higher for 20% (5/25) and 28% (7/25) of features comparing CM and NG with NECT ( p  < 0.05). For cc-RCC versus other, 36% (9/25) and 40% (10/25) features on CM had higher AUCs compared with NECT and NG images ( p  < 0.05). Conclusion Texture analysis of renal masses differs, when evaluated subjectively and quantitatively, by phase of CT enhancement. The corticomedullary phase had the highest discriminatory value when comparing masses and for differentiating cc-RCC from other masses. Key Points • Subjectively evaluated renal tumor heterogeneity on CT differs by phase of enhancement . • Quantitative CT texture analysis features in renal tumors differ by phases of enhancement with the corticomedullary phase showing the highest number and most significant differences compared with non-contrast-enhanced and nephrographic phase images . • For diagnosis of clear cell RCC, corticomedullary phase texture analysis features had improved accuracy of classification in approximately 40% of features studied compared with non-contrast-enhanced and nephrographic phase images .

ObjectiveThis article reviews the MRI appearance of cystic retroperitoneal (RP) masses.ConclusionLymphangiomas are the most common RP cystic masses and typically appear simple; microscopic fat is a specific but insensitive finding. Location, internal complexity, and enhancement pattern suggest alternative diagnoses which range from normal anatomic variants to congenital abnormalities and importantly include benign, neurogenic, and malignant neoplasms. An approach to the MR imaging of cystic RP masses is presented.

Background Somatostatin receptors (SSTR) represent an ideal target for nuclear theranostics applications in neuroendocrine tumors (NET). Studies suggest that high uptake on SSTR-PET is associated with response to SSTR peptide receptor radionuclide therapy (PRRT). The purpose of this study was to evaluate the role of baseline whole-body (WB) 68  Ga-DOTATATE PET/CT (SSTR-PET) quantitative parameters, and the presence of NET lesions without uptake on SSTR-PET, as outcome prognosticator in patients with NET treated with PRRT. Methods Patients with NET who underwent at least 4 177 Lu-DOTATATE PRRT cycles between 07/2016 and 03/2021 were included in this retrospective analysis if they fulfilled the following inclusion criteria: SSTR-PET within 6 months of 1st PRRT cycle, follow-up CT and/or MRI performed > 6 months after the 4th cycle of PRRT. The SSTR-PET analysis consisted of a visual and a quantitative analysis done independently by two board-certified physicians. The visual analysis assessed the presence of NET lesions visible on the SSTR-PET co-registered CT. The quantitative analysis consisted in contouring all SSTR-avid lesions on SSTR-PET and extracting WB quantitative parameters: SUVmean (WB-SUVmean), SUVmax of the lesion with highest uptake (H-SUVmax), and tumor volume (WB-TV). WB-SSTR-PET parameters and the presence of SSTR-PET-negative lesions were correlated to radiologic response (assessed by RECIST 1.1 criteria) and progression-free survival (PFS). Fisher’s exact test, Mann–Whitney’s U test and Kaplan–Meier curves with Cox-regression analysis were used for the statistical analysis. Results Forty patients (F/M: 21/19; 34/40 with gastro-entero-pancreatic (GEP) NET, 6/40 with non-GEP NET) were included in the analysis. The median follow-up period after the 4th PRRT cycle was 25.7 months (range 15.2–59.1). Fourteen/40 (35%) patients showed radiologic response (RECIST PR). PFS event was observed in 17/40 (42.5%) patients. Thirteen/40 (32.5%) patients had SSTR-PET-negative lesions at baseline. Higher WB-SUVmean and H-SUVmax were associated with better response ( p  = 0.015 and 0.005, respectively). The presence of SSTR-PET-negative lesions and lower WB-SUVmean were associated with shorter PFS ( p  = 0.026 and 0.008, respectively). Conclusion Visual and quantitative analyses of baseline SSTR-PET can yield valuable information to prognosticate outcomes after 177 Lu-DOTATATE PRRT.

ObjectiveTo compare machine learning (ML) of texture analysis (TA) features for classification of solid renal masses on non-contrast-enhanced CT (NCCT), corticomedullary (CM) and nephrographic (NG) phase contrast-enhanced (CE) CT.Materials and methodsWith IRB approval, we retrospectively identified 177 consecutive solid renal masses (116 renal cell carcinoma [RCC]; 51 clear cell [cc], 40 papillary, 25 chromophobe and 61 benign tumors; 49 oncocytomas and 12 fat-poor angiomyolipomas) with renal protocol CT between 2012 and 2017. Tumors were independently segmented by two blinded radiologists. Twenty-five 2-dimensional TA features were extracted from each phase. Diagnostic accuracy for 1) RCC versus benign tumor and 2) cc-RCC versus other tumor was assessed using XGBoost.ResultsML of texture analysis features on different phases achieved mean area under the ROC curve (AUC [SD]), sensitivity/specificity for 1) RCC vs benign = 0.70(0.19), 96%/32% on CM-CECT and 0.71(0.14), 83%/58% on NG-CECT and; 2) cc-RCC vs other = 0.77(0.12), 49%/90% on CM-CECT and 0.71(0.16), 22%/94% on NG-CECT. There was no difference in AUC comparing CECT to NCCT (p = 0.058–0.54) and no improvement when combining data across all three phases compared single-phase assessment (p = 0.39–0.68) for either outcome. AUCs decreased when ML models were trained with one phase and tested on a different phase for both outcomes (RCC;p = 0.045–0.106, cc-RCC; < 0.001).ConclusionAccuracy of machine learning classification of renal masses using texture analysis features did not depend on phase; however, models trained using one phase performed worse when tested on another phase particularly when associating NCCT and CECT. These findings have implications for large registries which use varying CT protocols to study renal masses.

Somatostatin receptors (SSTR) represent an ideal target for nuclear theranostics applications in neuroendocrine tumors (NET). Studies suggest that high uptake on SSTR-PET is associated with response to SSTR peptide receptor radionuclide therapy (PRRT). The purpose of this study was to evaluate the role of baseline whole-body (WB)  Ga-DOTATATE PET/CT (SSTR-PET) quantitative parameters, and the presence of NET lesions without uptake on SSTR-PET, as outcome prognosticator in patients with NET treated with PRRT. Patients with NET who underwent at least 4 Lu-DOTATATE PRRT cycles between 07/2016 and 03/2021 were included in this retrospective analysis if they fulfilled the following inclusion criteria: SSTR-PET within 6 months of 1st PRRT cycle, follow-up CT and/or MRI performed > 6 months after the 4th cycle of PRRT. The SSTR-PET analysis consisted of a visual and a quantitative analysis done independently by two board-certified physicians. The visual analysis assessed the presence of NET lesions visible on the SSTR-PET co-registered CT. The quantitative analysis consisted in contouring all SSTR-avid lesions on SSTR-PET and extracting WB quantitative parameters: SUVmean (WB-SUVmean), SUVmax of the lesion with highest uptake (H-SUVmax), and tumor volume (WB-TV). WB-SSTR-PET parameters and the presence of SSTR-PET-negative lesions were correlated to radiologic response (assessed by RECIST 1.1 criteria) and progression-free survival (PFS). Fisher's exact test, Mann-Whitney's U test and Kaplan-Meier curves with Cox-regression analysis were used for the statistical analysis. Forty patients (F/M: 21/19; 34/40 with gastro-entero-pancreatic (GEP) NET, 6/40 with non-GEP NET) were included in the analysis. The median follow-up period after the 4th PRRT cycle was 25.7 months (range 15.2-59.1). Fourteen/40 (35%) patients showed radiologic response (RECIST PR). PFS event was observed in 17/40 (42.5%) patients. Thirteen/40 (32.5%) patients had SSTR-PET-negative lesions at baseline. Higher WB-SUVmean and H-SUVmax were associated with better response (p = 0.015 and 0.005, respectively). The presence of SSTR-PET-negative lesions and lower WB-SUVmean were associated with shorter PFS (p = 0.026 and 0.008, respectively). Visual and quantitative analyses of baseline SSTR-PET can yield valuable information to prognosticate outcomes after Lu-DOTATATE PRRT.

Down syndrome (DS) is the most common chromosomal abnormality in the world, occurring at an incidence of one in 750 live births. This genetic condition stems from the nondisjunction of human chromosome 21 (Hsa21) during cell division, resulting in a third copy of the entire chromosome or a portion of it. The additional genetic material causes genomewide effects, and the resulting phenotypes are not well mapped or understood. Trisomy 21 (T21) is characterized by a broad spectrum of diseases, conditions, and disorders, most of which collectively contribute to a lower life expectancy. Respiratory infection is by far the largest contributor of morbidity and mortality worldwide in the DS population, but also in the typical population.There is little known about the cellular mechanisms responsible for varying susceptibilities to respiratory infections in DS, however studies have confirmed that trisomy 21 consistently activates the interferon response. Preliminary evidence suggests that the immune system mimics the phenotype of typical individuals after a course of viral infection, a state of immune dysfunction called “interferonopathy.” This consequently leads to a disrupted balance of chronic pro- and anti-inflammation in the airways and lungs, which ultimately increases the incidence of lower respiratory tract infections caused by pathobionts such as S. pneumoniae. Thus, this thesis sought to explore the central hypothesis that constitutive hyperactivation of type I interferon pathways and IL-10 signaling in individuals with Down syndrome results in increased predisposition to respiratory tract infections.The Human Trisome Project, an initiative created by the Linda Crnic Institute, is the largest biorepository of DS specimens in the world, containing peripheral blood samples from all over the US. The goal of this thesis was to create machine learning models using the samples analyzed using the V-PLEX Human Biomarker 54-Plex MesoScale Discovery Kit to predict susceptibility to respiratory tract infection (RTI) in DS. Three models were created, assessed, and improved upon: Multiple Logistic Regression, Principal Component Analysis, and Random Forest Analysis. Results suggest that the 54-Plex Cytokines do not predict RTI well collectively, however revealed promising biomarkers of interest to use in future linear models.

(1) Background: We sought to investigate the baseline lung and heart biology of the Dp16 mouse model of Down syndrome (DS) as a prelude to the investigation of recurrent respiratory tract infection. (2) Methods: In controls vs. Dp16 mice, we compared peripheral blood cell and plasma analytes. We examined baseline gene expression in lungs and hearts for key parameters related to susceptibility of lung infection. We investigated lung and heart protein expression and performed lung morphometry. Finally, and for the first time each in a model of DS, we performed pulmonary function testing and a hemodynamic assessment of cardiac function. (3) Results: Dp16 mice circulate unique blood plasma cytokines and chemokines. Dp16 mouse lungs over-express the mRNA of triplicated genes, but not necessarily corresponding proteins. We found a sex-specific decrease in the protein expression of interferon α receptors, yet an increased signal transducer and activator of transcription (STAT)-3 and phospho-STAT3. Platelet-activating factor receptor protein was not elevated in Dp16 mice. The lungs of Dp16 mice showed increased stiffness and mean linear intercept and contained bronchus-associated lymphoid tissue. The heart ventricles of Dp16 mice displayed hypotonicity. Finally, Dp16 mice required more ketamine to achieve an anesthetized state. (4) Conclusions: The Dp16 mouse model of DS displays key aspects of lung heart biology akin to people with DS. As such, it has the potential to be an extremely valuable model of recurrent severe respiratory tract infection in DS.