The German sickle cell disease registry reveals a surprising risk of acute splenic sequestration and an increased transfusion requirement in patients with compound heterozygous sickle cell disease HbS/ß-thalassaemia and no or low HbA expression.

Patients with sickle cell disease (SCD) in Germany exhibit a substantial genetic diversity in the ß-globin genotype. Data collected by the national German SCD registry reflect this diversity and allowed us to analyze the phenotypes associated with different SCD genotypes. Our study focused on 90 patients with HbS/ß-thalassaemia (HbS/ß-thal) and compared these to patients with HbSS and HbSC. Patients with HbS/ß-thal were classified into three groups: HbS/ß0-thal (no HbA), HbS/ß+-thal (HbA < 14%), and HbS/ß++-thal (HbA≥14%). In comparison to HbSS, patients with HbS/ß++-thal had higher Hb-levels, lower hemolytic activity and rarely required red blood cell transfusions. HbS/ß0-thal and HbS/ß+-thal closely resembled each other and are jointly referred to as HbS/ß0/+-thal. Compared to HbSS, patients with HbS/ß0/+-thal experienced a similar frequency of vasoocclusive crises and degree of hemolysis. However, the frequency of red blood cell transfusions (0.6 vs. 0.39/year, p = .0049) and splenic sequestration crises (42.4 vs. 15.5% of patients, p = 3.799e-05) was higher in HbS/ß0/+-thal than in HbSS, but close to zero in HbS/ß++-thal. In conclusion, the level of HbA expression determines the phenotype of HbS/ß+-thal. HbS/ß-thal expressing no or little HbA is hematologically similar to HbSS, but causes a previously unknown high risk of splenic sequestration.

Prediction of disease severity in COPD: a deep learning approach for anomaly-based quantitative assessment of chest CT.

OBJECTIVES: To quantify regional manifestations related to COPD as anomalies from a modeled distribution of normal-appearing lung on chest CT using a deep learning (DL) approach, and to assess its potential to predict disease severity. MATERIALS AND METHODS: Paired inspiratory/expiratory CT and clinical data from COPDGene and COSYCONET cohort studies were included. COPDGene data served as training/validation/test data sets (N = 3144/786/1310) and COSYCONET as external test set (N = 446). To differentiate low-risk (healthy/minimal disease, [GOLD 0]) from COPD patients (GOLD 1-4), the self-supervised DL model learned semantic information from 50 × 50 × 50 voxel samples from segmented intact lungs. An anomaly detection approach was trained to quantify lung abnormalities related to COPD, as regional deviations. Four supervised DL models were run for comparison. The clinical and radiological predictive power of the proposed anomaly score was assessed using linear mixed effects models (LMM). RESULTS: The proposed approach achieved an area under the curve of 84.3 ± 0.3 (p < 0.001) for COPDGene and 76.3 ± 0.6 (p < 0.001) for COSYCONET, outperforming supervised models even when including only inspiratory CT. Anomaly scores significantly improved fitting of LMM for predicting lung function, health status, and quantitative CT features (emphysema/air trapping; p < 0.001). Higher anomaly scores were significantly associated with exacerbations for both cohorts (p < 0.001) and greater dyspnea scores for COPDGene (p < 0.001). CONCLUSION: Quantifying heterogeneous COPD manifestations as anomaly offers advantages over supervised methods and was found to be predictive for lung function impairment and morphology deterioration. CLINICAL RELEVANCE STATEMENT: Using deep learning, lung manifestations of COPD can be identified as deviations from normal-appearing chest CT and attributed an anomaly score which is consistent with decreased pulmonary function, emphysema, and air trapping. KEY POINTS: • A self-supervised DL anomaly detection method discriminated low-risk individuals and COPD subjects, outperforming classic DL methods on two datasets (COPDGene AUC = 84.3%, COSYCONET AUC = 76.3%). • Our contrastive task exhibits robust performance even without the inclusion of expiratory images, while voxel-based methods demonstrate significant performance enhancement when incorporating expiratory images, in the COPDGene dataset. • Anomaly scores improved the fitting of linear mixed effects models in predicting clinical parameters and imaging alterations (p < 0.001) and were directly associated with clinical outcomes (p < 0.001).

The prognostic value of [18F]FDG PET/CT based response monitoring in metastatic melanoma patients undergoing immunotherapy: comparison of different metabolic criteria.

PURPOSE: To investigate the prognostic value of [18F]FDG PET/CT as part of response monitoring in metastatic melanoma patients treated with immune checkpoint inhibitors (ICIs). METHODS: Sixty-seven patients underwent [18F]FDG PET/CT before start of treatment (baseline PET/CT), after two cycles (interim PET/CT) and after four cycles of ICIs administration (late PET/CT). Metabolic response evaluation was based on the conventional EORTC and PERCIST criteria, as well as the newly introduced, immunotherapy-modified PERCIMT, imPERCIST5 and iPERCIST criteria. Metabolic response to immunotherapy was classified according to four response groups (complete metabolic response [CMR], partial metabolic response [PMR], stable metabolic disease [SMD], progressive metabolic disease [PMD]), and further dichotomized by response rate (responders = [CMR] + [PMR] vs. non-responders = [PMD] + [SMD]), and disease control rate (disease control = [CMR] + [PMR] + [SMD] vs. [PMD]). The spleen-to-liver SUV ratios (SLRmean, SLRmax) and bone marrow-to-liver SUV ratios (BLRmean, BLRmax) were also calculated. The results of PET/CT were correlated with patients' overall survival (OS). RESULTS: Median patient follow up [95% CI] was 61.5 months [45.3 - 66.7 months]. On interim PET/CT, the application of the novel PERCIMT demonstrated significantly longer survival for metabolic responders, while the rest criteria revealed no significant survival differences between the different response groups. Respectively on late PET/CT, both a trend for longer OS and significantly longer OS were observed in patients responding to ICIs with metabolic response and disease control after application of various criteria, both conventional and immunotherapy-modified. Moreover, patients with lower SLRmean values demonstrated significantly longer OS. CONCLUSION: In patients with metastatic melanoma PET/CT-based response assessment after four ICIs cycles is significantly associated with OS after application of different metabolic criteria. The prognostic performance of the modality is also high after the first two ICIs cycles, especially with employment of novel criteria. In addition, investigation of spleen glucose metabolism may provide further prognostic information.

Application of the long axial field-of-view PET/CT with low-dose [18F]FDG in melanoma.

AIM: The recent introduction of long axial field-of-view (LAFOV) PET/CT scanners has yielded very promising results regarding image quality and sensitivity in oncological patients. We, herein, aim to determine an appropriate acquisition time range for the new long axial field of view Biograph Vision Quadra PET/CT (Siemens Healthcare) using low dose [18F]FDG activity in a group of melanoma patients. METHODOLOGY: Forty-nine melanoma patients were enrolled in the study. All patients underwent total body PET/CT from the top of the head through the feet in two bed positions (field-of-view 106 cm) after i.v. injection of 2.0 MBq/kg [18F]FDG. The PET images of the first bed position (head to upper thigh; PET-10) were reconstructed and further split into 8-min (PET-8), 6-min (PET-6), 5-min (PET-5), 4-min (PET-4), and 2-min (PET-2) duration groups. Comparisons were performed between the different reconstructed scan times with regard to the visual evaluation of the PET/CT scans using the PET-10 images as reference and by calculating the 95%-CI for the differences between different time acquisitions. Moreover, objective evaluation of PET/CT image quality was performed based on SUV calculations of tumor lesions and background, leading to calculation of liver signal-to-noise ratio (SNR), and tumor-to-background ratio (TBR). RESULTS: A total of 60 scans were evaluated. Concerning visual analysis, 49/60 (81.7%) PET-10 scans were pathological, while the respective frequencies were 49/60 (81.7%) for PET-8 (95%-CI: - 0.0602-0.0602), 49/60 (81.7%) for PET-6 (95%-CI: - 0.0602-0.0602), 48/60 (80%) for PET-5 (95%-CI: - 0.0445-0.0886), 46/60 (76.7%) for PET-4 (95%-CI: - 0.0132-0.1370), and 45/60 (75%) for PET-2 (95%-CI: 0.0025-0.1593). In 18 PET-10 scans, the extent of metastatic involvement was very large, rendering the accurate calculation of [18F]FDG-avid tumor lesions very complicated. In the remaining 42 PET-10 scans, for which the exact calculation of tumor lesions was feasible, a total of 119 tumor lesions were counted, and the respective lesion detection rates for shorter acquisitions were as follows: 97.5% (116/119) for PET-8 (95%-CI: 0-1), 95.0% (113/119) for PET-6 (95%-CI: 0-1), 89.9% (107/119) for PET-5 (95%-CI: 0-2), 83.2% (99/119) for PET-4 (95%-CI: 1-2), and 73.9% (88/119) for PET-2 (95%-CI: 2-4). With regard to objective image quality evaluations, as a general trend, the reduction of acquisition time was associated with a decrease of liver SNR and a decrease of TBR, although in lesion-based analysis the change in TBR and tumor SUVmean values was non-significant up to 6 and 5 min acquisitions, respectively. CONCLUSIONS: In melanoma, low-dose LAFOV PET/CT imaging is feasible and can reduce the total scan time from head to upper thigh up to 5 min providing comparable diagnostic data to standard lengths of acquisition. This may have significant implications for the diagnostic work-up of patients with melanoma, given the need for true whole-body imaging in this type of cancer.

Can physiologic colonic [18F]FDG uptake in PET/CT imaging predict response to immunotherapy in metastatic melanoma?

AIM: The development of biomarkers that can reliably and early predict response to immune checkpoint inhibitors (ICIs) is crucial in melanoma. In recent years, the gut microbiome has emerged as an important regulator of immunotherapy response, which may, moreover, serve as a surrogate marker and prognosticator in oncological patients under immunotherapy. Aim of the present study is to investigate if physiologic colonic [18F]FDG uptake in PET/CT before start of ICIs correlates with clinical outcome of metastatic melanoma patients. The relation between [18F]FDG uptake in lymphoid cell-rich organs and long-term patient outcome is also assessed. METHODOLOGY: One hundred nineteen stage IV melanoma patients scheduled for immunotherapy with ipilimumab, applied either as monotherapy or in combination with nivolumab, underwent baseline [18F]FDG PET/CT. PET/CT data analysis consisted of standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) calculations in the colon as well as measurements of the colon-to-liver SUV ratios (CLRmean, CLRmax). Visual grading of colon uptake based on a four-point scale was also performed. Moreover, the spleen-to-liver SUV ratios (SLRmean, SLRmax) and the bone marrow-to-liver SUV ratios (BLRmean, BLRmax) were calculated. We also measured serum lipopolysaccharide (LPS) levels as a marker for bacterial translocation and surrogate for mucosal defense homeostasis. The results were correlated with patients' best clinical response, progression-free survival (PFS), and overall survival (OS) as well as clinical signs of colitis. RESULTS: Median follow-up [95%CI] from the beginning of immunotherapy was 64.6 months [61.0-68.6 months]. Best response to treatment was progressive disease (PD) for 60 patients, stable disease (SD) for 37 patients, partial response (PR) for 18 patients, and complete response (CR) for 4 patients. Kaplan-Meier curves demonstrated a trend for longer PFS and OS in patients with lower colonic SUV and CLR values; however, no statistical significance for these parameters as prognostic factors was demonstrated. On the other hand, patients showing disease control as best response to treatment (SD, PR, CR) had significantly lower colonic MTV and TLG than those showing PD. With regard to lymphoid cell-rich organs, significantly lower baseline SLRmax and BLRmax were observed in patients responding with disease control than progression to treatment. Furthermore, patients with lower SLRmax and BLRmax values had a significantly longer OS when dichotomized at their median. In multivariate analysis, PET parameters that were found to significantly adversely correlate with patient survival were colonic MTV for PFS, colonic TLG for PFS, and BLRmax for PFS and OS. CONCLUSIONS: Physiologic colonic [18F]FDG uptake in PET/CT, as assessed by means of SUV, before start of ipilimumab-based treatment does not seem to independently predict patient survival of metastatic melanoma. On the other hand, volumetric PET parameters, such as MTV and TLG, derived from the normal gut may identify patients showing disease control to immunotherapy and significantly correlate with PFS. Moreover, the investigation of glucose metabolism in the spleen and the bone marrow may offer prognostic information.

Detection of myeloma-associated osteolytic bone lesions with energy-integrating and photon-counting detector CT.

BACKGROUND: A recent innovation in computed tomography (CT) imaging has been the introduction of photon-counting detector CT (PCD-CT) systems, which are able to register the number and the energy level of incoming x­ray photons and have smaller detector elements compared with conventional CT scanners that operate with energy-integrating detectors (EID-CT). OBJECTIVES: The study aimed to evaluate the potential benefits of a novel, non-CE certified PCD-CT in detecting myeloma-associated osteolytic bone lesions (OL) compared with a state-of-the-art EID-CT. MATERIALS AND METHODS: Nine patients with multiple myeloma stage III (according to Durie and Salmon) underwent magnetic resonance imaging (MRI), EID-CT, and PCD-CT of the lower lumbar spine and pelvis. The PCD-CT and EID-CT images of all myeloma lesions that were visible in clinical MRI scans were reviewed by three radiologists for corresponding OL. Additionally, the visualization of destructions to cancellous or cortical bone, and trabecular structures, was compared between PCD-CT and EID-CT. RESULTS: Readers detected 21% more OL in PCD-CT than in EID-CT images (138 vs. 109; p < 0.0001). The sensitivity advantage of PCD-CT in lesion detection increased with decreasing lesion size. The visualization quality of cancellous and cortical destructions as well as of trabecular structures was rated higher by all three readers in PCD-CT images (mean image quality improvements for PCD-CT over EID-CT were +0.45 for cancellous and +0.13 for cortical destructions). CONCLUSIONS: For myeloma-associated OL, PCD-CT demonstrated significantly higher sensitivity, especially with small size. Visualization of bone tissue and lesions was considered significantly better in PCD-CT than in EID-CT. This implies that PCD-CT scanners could potentially be used in the early detection of myeloma-associated bone lesions.

How do deep-learning models generalize across populations? Cross-ethnicity generalization of COPD detection.

OBJECTIVES: To evaluate the performance and potential biases of deep-learning models in detecting chronic obstructive pulmonary disease (COPD) on chest CT scans across different ethnic groups, specifically non-Hispanic White (NHW) and African American (AA) populations. MATERIALS AND METHODS: Inspiratory chest CT and clinical data from 7549 Genetic epidemiology of COPD individuals (mean age 62 years old, 56-69 interquartile range), including 5240 NHW and 2309 AA individuals, were retrospectively analyzed. Several factors influencing COPD binary classification performance on different ethnic populations were examined: (1) effects of training population: NHW-only, AA-only, balanced set (half NHW, half AA) and the entire set (NHW + AA all); (2) learning strategy: three supervised learning (SL) vs. three self-supervised learning (SSL) methods. Distribution shifts across ethnicity were further assessed for the top-performing methods. RESULTS: The learning strategy significantly influenced model performance, with SSL methods achieving higher performances compared to SL methods (p < 0.001), across all training configurations. Training on balanced datasets containing NHW and AA individuals resulted in improved model performance compared to population-specific datasets. Distribution shifts were found between ethnicities for the same health status, particularly when models were trained on nearest-neighbor contrastive SSL. Training on a balanced dataset resulted in fewer distribution shifts across ethnicity and health status, highlighting its efficacy in reducing biases. CONCLUSION: Our findings demonstrate that utilizing SSL methods and training on large and balanced datasets can enhance COPD detection model performance and reduce biases across diverse ethnic populations. These findings emphasize the importance of equitable AI-driven healthcare solutions for COPD diagnosis. CRITICAL RELEVANCE STATEMENT: Self-supervised learning coupled with balanced datasets significantly improves COPD detection model performance, addressing biases across diverse ethnic populations and emphasizing the crucial role of equitable AI-driven healthcare solutions. KEY POINTS: Self-supervised learning methods outperform supervised learning methods, showing higher AUC values (p < 0.001). Balanced datasets with non-Hispanic White and African American individuals improve model performance. Training on diverse datasets enhances COPD detection accuracy. Ethnically diverse datasets reduce bias in COPD detection models. SimCLR models mitigate biases in COPD detection across ethnicities.

Capturing COPD heterogeneity: anomaly detection and parametric response mapping comparison for phenotyping on chest computed tomography.

Background: Chronic obstructive pulmonary disease (COPD) poses a substantial global health burden, demanding advanced diagnostic tools for early detection and accurate phenotyping. In this line, this study seeks to enhance COPD characterization on chest computed tomography (CT) by comparing the spatial and quantitative relationships between traditional parametric response mapping (PRM) and a novel self-supervised anomaly detection approach, and to unveil potential additional insights into the dynamic transitional stages of COPD. Methods: Non-contrast inspiratory and expiratory CT of 1,310 never-smoker and GOLD 0 individuals and COPD patients (GOLD 1-4) from the COPDGene dataset were retrospectively evaluated. A novel self-supervised anomaly detection approach was applied to quantify lung abnormalities associated with COPD, as regional deviations. These regional anomaly scores were qualitatively and quantitatively compared, per GOLD class, to PRM volumes (emphysema: PRMEmph, functional small-airway disease: PRMfSAD) and to a Principal Component Analysis (PCA) and Clustering, applied on the self-supervised latent space. Its relationships to pulmonary function tests (PFTs) were also evaluated. Results: Initial t-Distributed Stochastic Neighbor Embedding (t-SNE) visualization of the self-supervised latent space highlighted distinct spatial patterns, revealing clear separations between regions with and without emphysema and air trapping. Four stable clusters were identified among this latent space by the PCA and Cluster Analysis. As the GOLD stage increased, PRMEmph, PRMfSAD, anomaly score, and Cluster 3 volumes exhibited escalating trends, contrasting with a decline in Cluster 2. The patient-wise anomaly scores significantly differed across GOLD stages (p < 0.01), except for never-smokers and GOLD 0 patients. In contrast, PRMEmph, PRMfSAD, and cluster classes showed fewer significant differences. Pearson correlation coefficients revealed moderate anomaly score correlations to PFTs (0.41-0.68), except for the functional residual capacity and smoking duration. The anomaly score was correlated with PRMEmph (r = 0.66, p < 0.01) and PRMfSAD (r = 0.61, p < 0.01). Anomaly scores significantly improved fitting of PRM-adjusted multivariate models for predicting clinical parameters (p < 0.001). Bland-Altman plots revealed that volume agreement between PRM-derived volumes and clusters was not constant across the range of measurements. Conclusion: Our study highlights the synergistic utility of the anomaly detection approach and traditional PRM in capturing the nuanced heterogeneity of COPD. The observed disparities in spatial patterns, cluster dynamics, and correlations with PFTs underscore the distinct - yet complementary - strengths of these methods. Integrating anomaly detection and PRM offers a promising avenue for understanding of COPD pathophysiology, potentially informing more tailored diagnostic and intervention approaches to improve patient outcomes.

Test-retest, inter- and intra-rater reproducibility of size measurements of focal bone marrow lesions in MRI in patients with multiple myeloma.

OBJECTIVE: To investigate the reproducibility of size measurements of focal bone marrow lesions (FL) in MRI in patients with monoclonal plasma cell disorders under variation of patient positioning and observer. METHODS: A data set from a prospective test-retest study was used, in which 37 patients with a total of 140 FL had undergone 2 MRI scans with identical parameters after patient repositioning. Two readers measured long and short axis diameter on the initial scan in T1 weighted, T2 weighted short tau inversion recovery and diffusion-weighted imaging sequences. The first reader additionally measured FL on the retest-scan. The Bland-Altman method was used to assess limits of agreement (LoA), and the frequencies of absolute size changes were calculated. RESULTS: In the simple test-retest experiment with one identical reader, a deviation of ≥1 mm / ≥2 mm / ≥3 mm for the long axis diameter in T1 weighted images was observed in 66% / 25% / 8% of cases. When comparing measurements of one reader on the first scan to the measurement of the other reader on the retest scan, a change of ≥1 mm / ≥3 mm / ≥5 mm for the long axis diameter in T1 weighted images was observed in 78% / 21% / 5% of cases. CONCLUSION: Small deviations in FL size are common and probably due to variation in patient positioning or inter-rater variability alone, without any actual biological change of the FL. Knowledge of the uncertainty associated with size measurements of FLs is critical for radiologists and oncologists when interpreting changes in FL size in clinical practice and in clinical trials. ADVANCES IN KNOWLEDGE: According to the MY-RADs criteria, size measurements of focal lesions in MRI are now of relevance for response assessment in patients with monoclonal plasma cell disorders.Size changes of 1 or 2 mm are frequently observed due to uncertainty of the measurement only, while the actual focal lesion has not undergone any biological change.Size changes of at least 6 mm or more in T1 weighted or T2 weighted short tau inversion recovery sequences occur in only 5% or less of cases when the focal lesion has not undergone any biological change.

Same-day repeatability and Between-Sequence reproducibility of Mean ADC in PI-RADS lesions.

PURPOSE: This study aimed to assess repeatability after repositioning (inter-scan), intra-rater, inter-rater and inter-sequence variability of mean apparent diffusion coefficient (ADC) measurements in MRI-detected prostate lesions. METHOD: Forty-three patients with suspicion for prostate cancer were included and received a clinical prostate bi-/multiparametric MRI examination with repeat scans of the T2-weighted and two DWI-weighted sequences (ssEPI and rsEPI). Two raters (R1 and R2) performed single-slice, 2D regions of interest (2D-ROIs) and 3D-segmentation-ROIs (3D-ROIs). Mean bias, corresponding limits of agreement (LoA), mean absolute difference, within-subject coefficient of variation (CoV) and repeatability/reproducibility coefficient (RC/RDC) were calculated. Bradley & Blackwood test was used for variance comparison. Linear mixed models (LMM) were used to account for multiple lesions per patient. RESULTS: Inter-scan repeatability, intra-rater and inter-sequence reproducibility analysis of ADC showed no significant bias. 3D-ROIs demonstrated significantly less variability than 2D-ROIs (p < 0.01). Inter-rater comparison demonstrated small significant systematic bias of 57 × 10-6 mm2/s for 3D-ROIs (p < 0.001). Intra-rater RC, with the lowest variation, was 145 and 189 × 10-6 mm2/s for 3D- and 2D-ROIs, respectively. For 3D-ROIs of ssEPI, RCs and RDCs were 190-198 × 10-6 mm2/s for inter-scan, inter-rater and inter-sequence variation. No significant differences were found for inter-scan, inter-rater and inter-sequence variability. CONCLUSIONS: In a single-scanner setting, single-slice ADC measurements showed considerable variation, which may be lowered using 3D-ROIs. For 3D-ROIs, we propose a cut-off of âˆ¼ 200 × 10-6 mm2/s for differences introduced by repositioning, rater or sequence effects. The results suggest that follow-up measurements should be possible by different raters or sequences.

Detection of Clinically Significant Prostate Cancer Using Targeted Biopsy with Four Cores Versus Target Saturation Biopsy with Nine Cores in Transperineal Prostate Fusion Biopsy: A Prospective Randomized Trial.

BACKGROUND: Multiparametric magnetic resonance imaging (mpMRI) and targeted biopsy (TB) facilitate accurate detection of clinically significant prostate cancer (csPC). However, it remains unclear how targeted cores should be applied for accurate diagnosis of csPC. OBJECTIVE: To assess csPC detection rates for two target-directed MRI/transrectal ultrasonography (TRUS) fusion biopsy approaches, conventional TB and target saturation biopsy (TS). DESIGN, SETTING, AND PARTICIPANTS: This was a prospective single-center study of outcomes for transperineal MRI/TRUS fusion biopsies for 170 men. Half of the men (n = 85) were randomized to conventional TB with four cores per lesion and half (n = 85) to TS with nine cores. Biopsies were performed by three experienced board-certified urologists. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: PC and csPC (International Society of Urological Pathology grade group ≥2) detection rates for systematic biopsy (SB), TB, and TS were analyzed using McNemar's test for intrapatient comparisons and Fisher's exact test for TS versus TB. A combination of targeted biopsy (TS or TB) and SB served as the reference. RESULTS AND LIMITATIONS: According to the reference, csPC was diagnosed for 57 men in the TS group and 36 men in the TB group. Of these, TS detected 57/57 csPC cases and TB detected 33/36 csPC cases (p = 0.058). Detection of Gleason grade group 1 disease was 10/12 cases with TS and 8/17 cases with TB (p = 0.055). In addition, TS detected 97% of 63 csPC lesions, compared to 86% with TB (p = 0.1). Limitations include the single-center design, the limited generalizability owing to the transperineal biopsy route, the lack of central review of pathology and radical prostatectomy correlation, and uneven distributions of csPC prevalence, Prostate Imaging-Reporting and Data System (PI-RADS) 5 lesions, men with two or more PI-RADS ≥3 lesions, and prostate-specific antigen density between the groups, which may have affected the results. CONCLUSIONS: In our study, rates of csPC detection did not significantly differ between TS and TB. PATIENT SUMMARY: In this study, we investigated two targeted approaches for taking prostate biopsy samples after observation of suspicious lesions on prostate scans. We found that the rates of detection of prostate cancer did not significantly differ between the two approaches.

Low level of antioxidant capacity biomarkers but not target overexpression predicts vulnerability to ROS-inducing drugs.

Despite a strong rationale for why cancer cells are susceptible to redox-targeting drugs, such drugs often face tumor resistance or dose-limiting toxicity in preclinical and clinical studies. An important reason is the lack of specific biomarkers to better select susceptible cancer entities and stratify patients. Using a large panel of lung cancer cell lines, we identified a set of "antioxidant-capacity" biomarkers (ACB), which were tightly repressed, partly by STAT3 and STAT5A/B in sensitive cells, rendering them susceptible to multiple redox-targeting and ferroptosis-inducing drugs. Contrary to expectation, constitutively low ACB expression was not associated with an increased steady state level of reactive oxygen species (ROS) but a high level of nitric oxide, which is required to sustain high replication rates. Using ACBs, we identified cancer entities with a high percentage of patients with favorable ACB expression pattern, making it likely that more responders to ROS-inducing drugs could be stratified for clinical trials.

Deep Learning for Automatic Bone Marrow Apparent Diffusion Coefficient Measurements From Whole-Body Magnetic Resonance Imaging in Patients With Multiple Myeloma: A Retrospective Multicenter Study.

OBJECTIVES: Diffusion-weighted magnetic resonance imaging (MRI) is increasingly important in patients with multiple myeloma (MM). The objective of this study was to train and test an algorithm for automatic pelvic bone marrow analysis from whole-body apparent diffusion coefficient (ADC) maps in patients with MM, which automatically segments pelvic bones and subsequently extracts objective, representative ADC measurements from each bone. MATERIALS AND METHODS: In this retrospective multicentric study, 180 MRIs from 54 patients were annotated (semi)manually and used to train an nnU-Net for automatic, individual segmentation of the right hip bone, the left hip bone, and the sacral bone. The quality of the automatic segmentation was evaluated on 15 manually segmented whole-body MRIs from 3 centers using the dice score. In 3 independent test sets from 3 centers, which comprised a total of 312 whole-body MRIs, agreement between automatically extracted mean ADC values from the nnU-Net segmentation and manual ADC measurements from 2 independent radiologists was evaluated. Bland-Altman plots were constructed, and absolute bias, relative bias to mean, limits of agreement, and coefficients of variation were calculated. In 56 patients with newly diagnosed MM who had undergone bone marrow biopsy, ADC measurements were correlated with biopsy results using Spearman correlation. RESULTS: The ADC-nnU-Net achieved automatic segmentations with mean dice scores of 0.92, 0.93, and 0.85 for the right pelvis, the left pelvis, and the sacral bone, whereas the interrater experiment gave mean dice scores of 0.86, 0.86, and 0.77, respectively. The agreement between radiologists' manual ADC measurements and automatic ADC measurements was as follows: the bias between the first reader and the automatic approach was 49 × 10 -6 mm 2 /s, 7 × 10 -6 mm 2 /s, and -58 × 10 -6 mm 2 /s, and the bias between the second reader and the automatic approach was 12 × 10 -6 mm 2 /s, 2 × 10 -6 mm 2 /s, and -66 × 10 -6 mm 2 /s for the right pelvis, the left pelvis, and the sacral bone, respectively. The bias between reader 1 and reader 2 was 40 × 10 -6 mm 2 /s, 8 × 10 -6 mm 2 /s, and 7 × 10 -6 mm 2 /s, and the mean absolute difference between manual readers was 84 × 10 -6 mm 2 /s, 65 × 10 -6 mm 2 /s, and 75 × 10 -6 mm 2 /s. Automatically extracted ADC values significantly correlated with bone marrow plasma cell infiltration ( R = 0.36, P = 0.007). CONCLUSIONS: In this study, a nnU-Net was trained that can automatically segment pelvic bone marrow from whole-body ADC maps in multicentric data sets with a quality comparable to manual segmentations. This approach allows automatic, objective bone marrow ADC measurements, which agree well with manual ADC measurements and can help to overcome interrater variability or nonrepresentative measurements. Automatically extracted ADC values significantly correlate with bone marrow plasma cell infiltration and might be of value for automatic staging, risk stratification, or therapy response assessment.

Repeatability and Reproducibility of ADC Measurements and MRI Signal Intensity Measurements of Bone Marrow in Monoclonal Plasma Cell Disorders: A Prospective Bi-institutional Multiscanner, Multiprotocol Study.

BACKGROUND/OBJECTIVES: Apparent diffusion coefficient (ADC) and signal intensity (SI) measurements play an increasing role in magnetic resonance imaging (MRI) of monoclonal plasma cell disorders. The purpose of this study was to assess interrater variability, repeatability, and reproducibility of ADC and SI measurements from bone marrow (BM) under variation of MRI protocols and scanners. PATIENTS AND METHODS: Fifty-five patients with suspected or confirmed monoclonal plasma cell disorder were prospectively included in this institutional review board-approved study and underwent several measurements after the standard clinical whole-body MR scan, including repeated scan after repositioning, scan with a second MRI protocol, scan at a second 1.5 T scanner with a harmonized MRI protocol, and scan at a 3 T scanner. For T1-weighted, T2-weighted STIR, B800 images, and ADC maps, regions of interest were placed in the BM of the iliac crest and sacral bone, and in muscle tissue for image normalization. Bland-Altman plots were constructed, and absolute bias, relative bias to mean, limits of agreement, and coefficients of variation were calculated. RESULTS: Interrater variability and repeatability experiments showed a maximal relative bias of -0.077 and a maximal coefficient of variation of 16.2% for all sequences. Although the deviations at the second 1.5 T scanner with harmonized MRI protocol to the first 1.5 T scanner showed a maximal relative bias of 0.124 for all sequences, the variation of the MRI protocol and scan at the 3 T scanner led to large relative biases of up to -0.357 and -0.526, respectively. When comparing the 3 T scanner to the 1.5 T scanner, normalization to muscle reduced the bias of T1-weighted and T2-weighted sequences, but not of ADC maps. CONCLUSIONS: The MRI scanners with identical field strength and harmonized MRI protocols can provide relatively stable quantitative measurements of BM ADC and SI. Deviations in MRI field strength and MRI protocol should be avoided when applying ADC cutoff values, which were established at other scanners or when performing multicentric imaging trials.

Inflammatory exposure drives long-lived impairment of hematopoietic stem cell self-renewal activity and accelerated aging.

Hematopoietic stem cells (HSCs) mediate regeneration of the hematopoietic system following injury, such as following infection or inflammation. These challenges impair HSC function, but whether this functional impairment extends beyond the duration of inflammatory exposure is unknown. Unexpectedly, we observed an irreversible depletion of functional HSCs following challenge with inflammation or bacterial infection, with no evidence of any recovery up to 1 year afterward. HSCs from challenged mice demonstrated multiple cellular and molecular features of accelerated aging and developed clinically relevant blood and bone marrow phenotypes not normally observed in aged laboratory mice but commonly seen in elderly humans. In vivo HSC self-renewal divisions were absent or extremely rare during both challenge and recovery periods. The progressive, irreversible attrition of HSC function demonstrates that temporally discrete inflammatory events elicit a cumulative inhibitory effect on HSCs. This work positions early/mid-life inflammation as a mediator of lifelong defects in tissue maintenance and regeneration.

The prognostic significance of [18F]FDG PET/CT in multiple myeloma according to novel interpretation criteria (IMPeTUs).

PURPOSE: [18F]FDG PET/CT is the elective imaging modality for treatment monitoring in multiple myeloma (MM). However, MM is a heterogeneous disease from an imaging point of view, raising challenges in interpretation of PET/CT. We herein investigated the prognostic role of the novel Italian Myeloma criteria for PET Use (IMPeTUs) in MM patients undergoing high-dose chemotherapy (HDT) followed by autologous stem cell transplantation (ASCT). METHODS: Forty-seven patients with newly diagnosed MM underwent [18F]FDG PET/CT before commencement of treatment (baseline PET/CT). Thirty-four of them (72.3%) were also examined after completion of ASCT (follow-up PET/CT). PET/CT analysis was based on the IMPeTUs criteria, which take into consideration-among others-the metabolic state of the bone marrow based on the 5-point Deauville score (DS), the number and metabolic state of focal [18F]FDG-avid lesions, as well as the presence of paramedullary disease (PMD) and extramedullary disease (EMD). We analyzed whether parameters from IMPeTUs correlate with clinically relevant parameters and patients' outcome, as assessed by progression-free survival (PFS). RESULTS: Median follow-up from baseline and follow-up PET/CT were 85.1 months and 76.7 months, respectively. The number of focal, [18F]FDG-avid lesions significantly correlated with the bone marrow infiltration rate and the R-ISS stage, while the presence of PMD was associated with LDH. After univariate survival analysis, the number of focal, [18F]FDG-avid lesions both before and after therapy as well as the presence of PMD and EMD before therapy adversely affected PFS. Multivariate survival analysis for baseline parameters confirmed that the number of focal, [18F]FDG-avid lesions and the presence of EMD are associated with adverse prognosis, irrespective of the ISS stage and/or the presence of high-risk cytogenetic abnormalities. The 5-point DS of [18F]FDG uptake in reference bone marrow and focal lesions showed a significant decrease as response to treatment, but it did not affect PFS. CONCLUSION: Several parameters utilized in IMPeTUs predict PFS in MM patients, suggesting the potentially significant role of the new criteria in patient stratification and response assessment. Additional studies are warranted for the further evaluation of IMPeTUs in the direction of establishment of robust cut-off values with a prognostic significance in the disease.