Radiomic nomogram for predicting high-risk cytogenetic status in multiple myeloma based on fat-suppressed T2-weighted magnetic resonance imaging.

Rationale and Objectives: Radiomics has demonstrated potential in predicting the cytogenetic status of multiple myeloma (MM). However, the role of single-sequence radiomic nomograms in predicting the high-risk cytogenetic (HRC) status of MM remains underexplored. This study aims to develop and validate radiomic nomograms based on fat-suppressed T2-weighted images (T2WI-FS) for predicting MM's HRC status, facilitating pre-treatment decision-making and prognostic assessment. Materials and methods: A cohort of 159 MM patients was included, comprising 71 HRC and 88 non-HRC cases. Regions of interest within the most significant tumor lesions on T2WI-FS images were manually delineated, yielding 1688 features. Fourteen radiomic features were selected using 10-fold cross-validation, employing methods such as variance thresholds, Student's t-test, redundancy analysis, and least absolute shrinkage and selection operator (LASSO). Logistic regression was utilized to develop three prediction models: a clinical model (model 1), a T2WI-FS radiomic model (model 2), and a combined clinical-radiomic model (model 3). Receiver operating characteristic (ROC) curves evaluated and compared the diagnostic performance of these models. Kaplan-Meier survival analysis and log-rank tests assessed the prognostic value of the radiomic nomograms. Results: Models 2 and 3 demonstrated significantly greater diagnostic efficacy compared to model 1 (p < 0.05). The areas under the ROC curve for models 1, 2, and 3 were as follows: training set-0.650, 0.832, and 0.846; validation set-0.702, 0.730, and 0.757, respectively. Kaplan-Meier survival analysis indicated comparable prognostic values between the radiomic nomogram and MM cytogenetic status, with log-rank test results (p < 0.05) and concordance indices of 0.651 and 0.659, respectively; z-score test results were not statistically significant (p = 0.153). Additionally, Kaplan-Meier analysis revealed that patients in the non-HRC group, low-RS group, and aged ≤ 60 years exhibited the longest overall survival, while those in the HRC group, high-RS group, and aged > 60 years demonstrated the shortest overall survival (p = 0.004, Log-rank test). Conclusions: Radiomic nomograms are capable of predicting the HRC status in MM. The cytogenetic status, radiomics model Rad score, and age collectively influence the overall survival of MM patients. These factors potentially contribute to pre-treatment clinical decision-making and prognostic assessment.

Correlation of CT parameters and PD-L1 expression status in gastric cancer.

OBJECTIVE: We aimed to explore the correlation between routine computed tomography (CT) imaging features and programmed cell death ligand-1(PD-L1) expression status in gastric cancer and evaluate the predictive value of imaging parameters for this immunotherapy biomarker. MATERIALS AND METHODS: Patients with gastric adenocarcinoma who underwent abdominal CT three-stage enhanced scan and PD-L1 immunohistochemical testing before treatment were retrospectively examined. All diagnoses were confirmed through pathology. According to the expression status of PD-L1, they were divided into the positive (CPS ≥ 5) or negative group (CPS < 5). Baseline CT imaging features were collected. Diagnostic performances of the different variables were evaluated using receiver operating characteristic (ROC) curve. RESULTS: In total, 67 patients (17 women and 50 men; mean age: 59.55 ± 10.22 years) with gastric adenocarcinoma were included in the study. The overall stages, probability of maximum lymph node short diameter > 1 cm and peak of lesion enhancement occurring in the arterial phase were statistically significant between the two groups (p < 0.05). Moreover, the arterial enhancement fraction (AEF) was significantly higher in the positive group than that in the negative group (p < 0.05), and ROC curve analysis showed that the AEF exhibited a high evaluation efficacy (area under the curve [AUC] = 0.724 [95% confidence interval (CI): 0.602-0.826]). The combined parameters had the best diagnostic efficacy (AUC = 0.825 [95%CI: 0.716-0.933]), sensitivity (75.00%), and specificity (81.40%). CONCLUSIONS: These findings confirm a correlation between CT imaging features and PD-L1 expression status in gastric cancer, and AEF may help evaluate high PD-L1 expression and select patients suitable for immunotherapy.

Can spectral computed tomography (CT) replace perfusion CT to assess the histological classification of non-small cell lung cancer?

Background: Non-small cell lung cancer (NSCLC) accounts for 80% of total lung cancer cases, it is necessary to distinguish the histological types of NSCLC. This study set out to investigate the correlation between spectral computed tomography (CT) and CT perfusion parameters in patients with NSCLC and to compare the differential diagnostic efficacy of these two imaging modalities for the histological classification of NSCLC. Methods: A total of 62 eligible consecutive patients, including 32 with lung adenocarcinoma (LUAD) and 30 with lung squamous cell carcinoma (LUSC), who underwent "one-stop" spectral combined perfusion scan and pathologically confirmed NSCLC at Lanzhou University Second Hospital between September 2020 and December 2021 were prospectively enrolled. The spectral parameters of lesions in the arterial phase (AP) and venous phase (VP) [including iodine concentration (IC), effective atomic number (Zeff), CT40keV, and slope of the spectral curve (K70keV)] and perfusion parameters [blood flow (BF), blood volume (BV), surface permeability (PS), and mean transit time (MTT)] were assessed. Pearson or Spearman correlation analysis was performed to evaluate the correlation between the two imaging parameters, and the DeLong test was used to compare the diagnostic performance of the two imaging modalities. Results: BV and BF were strongly correlated with spectral parameters CT40keV, IC, Zeff, and K70keV in the AP and VP (0.6

Diagnostic Value of Dual-Energy CT Virtual Non-Calcium and Rho/Z Images for Bone Marrow Infiltration in Primary Malignant Bone Tumors.

RATIONALE AND OBJECTIVES: We investigated the diagnostic performance of dual-energy CT (DECT) virtual non-calcium (VNCa) and Rho/Z images for bone marrow infiltration of primary malignant bone tumors (PMBTs). MATERIALS AND METHODS: We retrospectively analyzed 65 patients with PMBT who underwent DECT and MRI within 2 weeks. DECT was used to evaluate the presence and extent of marrow involvement surrounding PMBTs using the SCT, VNCa, and Rho/Z images. MRI was used as the reference standard for measurements. CT values of normal and involved bone marrow areas were measured on VNCa images, and Zeff values were measured on Rho/Z images. The statistical methods used were the 2*C chi-square test, ANOVA test, paired samples t test, and diagnostic performance of the different variables were evaluated using receiver operating characteristic curves. RESULTS: VNCa and Rho/Z images showed higher accuracy (91%, 92% vs. 67%) and sensitivity (90%, 92% vs. 69%) than SCT images for diagnosing bone marrow infiltration in patients with PMBT. The maximum longitudinal diameter of tumor involvement measurements was statistically different between VNCa and SCT, Rho/Z and SCT, MRI, and SCT (all p < 0.05, p = 0.047, p = 0.049, and p = 0.023, respectively). The maximum transverse diameter was statistically significant between SCT and MRI, VNCa and MRI, Rho/Z and MRI (all p < 0.05, and p = 0.015, and p = 0.044, and p = 0.047, respectively). The HU or Zeff values based on the area of interest of VNCa and Rho/Z images differed significantly between the normal and infiltrated bone marrow area (p < 0.001). Receiver operating characteristic curve analysis revealed area under the curves of 0.995 and 0.988, respectively, with cut-off values of -31.57 HU and 7.8, and the sensitivity of both was 96.9%. CONCLUSION: DECT-VNCa and Rho/Z images have good diagnostic value when evaluating bone marrow infiltration in PMBTs.

Combination of clinical and spectral-CT parameters for predicting lymphovascular and perineural invasion in gastric cancer.

PURPOSE: The purpose of this study was to investigate the utility of combining clinical and spectral computed tomography (CT) parameters for the preoperative evaluation of lymphovascular invasion (LVI) and perineural invasion (PNI) in gastric cancers (GCs). MATERIALS AND METHODS: Patients with gastric adenocarcinoma who underwent spectral-CT examination were retrospectively examined. All diagnoses were confirmed by pathology, and the patients were divided into positive and negative groups based on LVI/PNI occurrence. Clinical characteristics, including demographic information, serum tumor markers, and gastroscopic pathological information, were collected. The effective atomic number (Zeff), iodine concentration (IC), and water concentration were measured in the arterial (AP) and venous phase (VP). Differences between the two groups were searched for using independent sample t-test, Mann-Whitney U test, or chi-square (χ2) test and diagnostic performances of the different variables were evaluated using receiver operating characteristic (ROC) curve. RESULTS: A total of 121 patients (96 men, 25 women; mean age: 59 ± 8.7 [SD] years, range: 36-82 years) with gastric adenocarcinoma were included in the study. The serum level of the tumor marker CA125, as well as Zeff and IC in the LVI/PNI-positive group, were significantly higher than in the negative group, and the histological grade and Borrmann type differed between the two groups (all P < 0.05). The discriminating capability analysis demonstrated that CA125 exhibited a favorable performance, and the VP parameters' diagnostic efficacy was superior to that of the AP parameters. The efficacy of the combination of clinical and spectral-CT parameters was superior to that of individual parameters (all AUC > 0.85). The clinical parameters combined with Zeff and IC in the AP and VP exhibited a high evaluation efficacy (AUC = 0.890 [95% CI: 0.826-0.955]; F1 score = 0.888; accuracy = 84.3% [102/121; 95% CI: 76.7-89.8]; sensitivity = 86.2% [75/87; 95% CI: 76.8-92.4]; specificity = 79.4% [27/34; 95% CI: 61.6-90.1]). CONCLUSIONS: Clinical and spectral-CT parameters exhibit considerable capabilities in the preoperative evaluation of LVI and PNI in GCs. The combination of clinical and spectral-CT parameters effectively predicts LVI and PNI in GCs.