Cancer Imaging最新文献

Background: Intraoperative bleeding is a serious complication of spinal tumor surgery. Preoperative identification of patients at high risk of intraoperative blood transfusion (IBT) and intraoperative massive bleeding (IMB) before spinal tumor resection surgery is difficult but critical for surgical planning and blood management. This study aims to develop and validate delta radiomics prediction models for IBT and IMB in spinal tumor surgery.

Methods: Patients diagnosed with spinal tumors who underwent spinal tumor resection surgery were retrospectively recruited. CT, CTE, delta, and clinical models based on CT native phase, CT arterial phase images, and clinical factors were constructed using 10-fold cross-validation and logistic regression (LR), random forest (RF), and support vector machine (SVM) in the training cohort. Receiver operating characteristic (ROC) curves, integrated discrimination improvement (IDI), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were used to evaluate and compare the diagnostic performance of these models.

Results: 231 patients were randomly divided into training (n = 161) and test (n = 70) cohorts, comprising 146 IBT and 85 no-IBT patients, 35 IMB and 196 no-IMB patients, respectively. The delta model performed best in predicting IBT and IMB risk, with better predictive ability than the clinical model (IDI = 0.11-0.13 for IBT, and IDI = 0.02-0.08 for IMB, p < 0.05, respectively). Calibration curves indicated that the predicted probabilities of IBT and IMB in the model did not differ significantly from the actual probabilities (p > 0.05).

Conclusion: The CT delta model we constructed may be a valuable tool to improve risk stratification before spinal tumor surgery, thus contributing to preoperative planning and improving patient prognosis.

Trial registration: Retrospectively registered (M2020435).

Background: Percutaneous computed tomography (CT)-guided biopsy and cryoablation are commonly used techniques for diagnosing and treating pulmonary malignant tumors. Performing these procedures simultaneously allows for tissue diagnosis while potentially offering therapeutic benefits. This study aimed to evaluate whether the efficacy and safety of simultaneous percutaneous CT-guided biopsy and cryoablation in managing pulmonary tumors suspected of malignancy are comparable to those of sequential procedures.

Methods: This retrospective study involved 124 patients with 131 highly suspicious malignant pulmonary nodules. Patients either underwent synchronous percutaneous core-needle biopsy and cryoablation (Group A) or separately underwent these procedures (Group B) from December 2020 to May 2024. All procedures were performed under CT guidance using a percutaneous approach. We analyzed technical success rates, complications, diagnostic yield, and local tumor control.

Results: Technical success rates were 100% in both groups. The rate of pneumothorax was 42.1% (16/38) in Group A and 34.9% (30/86) in Group B. In Group A, hemoptysis and pleural effusion rates were 18.4% (7/38) and 23.7% (9/38), respectively, while in Group B, these rates were 16.3% (14/86) and 12.8% (11/86). These differences were not statistically significant. The diagnostic positive rate in Group A was 87.5%. The mean follow-up duration was 11.8 months (95% confidence interval [CI], 10.2-13.4), with local tumor control rates of 97% for Group A and 88% for Group B. The effectiveness rates of synchronous and separate procedures were similar.

Conclusion: Synchronous biopsy-ablation is an effective method for obtaining tumor pathology and local treatment of lung tumors simultaneously. It is a viable option for select patients where expedited diagnosis-therapy is clinically justified, particularly when molecular profiling is not immediately indicated.

Objective: To evaluate the long-term efficacy of thermal ablation in the treatment of pulmonary oligometastases (POs) from hepatocellular carcinoma (HCC) and to explore the prognosis-related influencing factors.

Methods: From October 2012 to January 2019, 145 POs (mean diameter: 2.3 cm, ≤ 4 POs per patient) in 62 patients (male = 33, female = 29, mean age: 61.0 years old) with HCC were treated by thermal ablation. The primary endpoints were progression-free survival (PFS) and overall survival (OS), and the secondary endpoints were technical success, technical efficacy, and complications. PFS and OS were analyzed by the log-rank test and Cox proportional hazards regression models.

Results: Technical success, technical efficacy and major complications were 100, 96.8, and 21%, respectively. During the median follow-up of 30 months (range: 16-50), the median PFS was 11.4 months (95% CI 10.1-12.8), the 1- and 2-year PFS rates were 43.5 and 10.2%, respectively, and radical treatments for primary HCC (P < 0.01), metachronous POs (P < 0.01) and initial Barcelona Clinic Liver Cancer (BCLC) stage 0-B (P < 0.05) were significant indicators of superior PFS. The mOS was 33.0 months (95% CI 26.9-39.1), and the 1-, 2- and 3-year OS rates were 98.4, 78.7% and 43.7%, respectively. Radical treatments for primary HCC (P < 0.01) and initial BCLC stage 0-B (P < 0.05) showed superior OS.

Conclusion: POs ablation after primary HCC control is safe and effective, and initial BCLC stage evaluation and radical treatment strategies should be emphasized. This study has certain limitations, including the retrospective design, single-center data, selection bias and small sample size.

Purpose: This study aimed to evaluate the effectiveness of using a radiomics model to predict extraprostatic extension (EPE) in prostate cancer from PSMA PET/CT, and to directly compare its performance with the Mehralivand Grading System, an MRI-based method for EPE assessment.

Methods: A total of 206 patients who underwent radical prostatectomy were included in this study. Radiomics features were extracted from PSMA PET/CT images to construct predictive models using Support Vector Machine (SVM) and Random Forest algorithms. In addition, among the 63 patients who underwent both PSMA PET/CT and multiparametric MRI (mpMRI), the performance of the radiomics model was compared with that of the Mehralivand Grading System. Key performance metrics, including the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were reported.

Results: Among the 63 patients who underwent both PSMA PET/CT and multiparametric MRI (mpMRI), the radiomics model achieved an AUC of 76.8% (95% CI: 64.4-86.5%), sensitivity of 72.0%, specificity of 81.5%, PPV of 72.0%, and NPV of 81.6%. In comparison, the Mehralivand Grading System yielded AUCs of 66.8%, 63.5%, and 60.2% from three independent readers. DeLong's test showed that the radiomics model significantly outperformed all three readers in terms of AUC (p = 0.013, 0.003, and 0.001, respectively).

Conclusion: The radiomics model derived from PSMA PET/CT can better capture features associated with EPE and shows promise for aiding preoperative assessment in prostate cancer. However, further validation in larger, independent cohorts is necessary to confirm its stability and clinical utility.

Background: Pilot studies have indicated diagnostic benefits from using dual-energy CT (DECT) for staging and follow-up of melanoma patients. The purpose of this study was to investigate the sensitivity, specificity and qualitative assessment of spectral image reconstructions for metastases in melanoma patients in a large-scale, multi-reader evaluation.

Methods: In total, 308 patients with melanoma, 95 patients with metastases and a control group of 213 patients without metastases, who underwent oncologic staging CT of the chest, abdomen and pelvis on a dual-layer dual-energy CT system (dlDECT) were retrospectively included. Conventional images (CI), color-coded iodine overlays (IO) and virtual monoenergetic images at 40 keV (VMI_40keV) were reconstructed. 6 radiologists (3 experienced with 6 to 9 years and 3 less experienced with 2 to 4 years of experience) read all cases in a CI-based session, and a session based on a combination of CI, IO and VMI_40keV. Readers were asked to determine presence of metastases in specific tissues in a binary fashion and to indicate diagnostic certainty and lesion delineation on 5-point Likert scales.

Results: Sensitivity for detection of metastases in the skeletal muscle and peritoneum was significantly higher for the spectral assessment (for skeletal muscle 70% vs. 61%; for peritoneum 76% vs. 62%, both: p < 0.05). For subcutaneous metastases, there was a significant increase in specificity (92% vs. 89%, p < 0.05), however accompanied with a significant decrease in sensitivity (79% vs. 85%, p < 0.05). Diagnostic certainty was rated significantly higher for spectral images than CI in all (6/6) of the assessed tissues, whereas improvements in lesion delineation were noted for the skeletal muscle, the subcutaneous tissue and the pancreas.

Conclusions: We found that in melanoma patients, the benefit of dlDECT-derived spectral reconstructions depends on the assessed tissue. While assessment of skeletal muscle and peritoneal metastases was significantly improved, low or absent iodine uptake of subcutaneous lesions led to false negatives and a consecutive decrease in sensitivity.

Background: The clinical application of artificial intelligence (AI) models based on breast ultrasound static images has been hindered in real-world workflows due to operator-dependence of standardized image acquisition and incomplete view of breast lesions on static images. To better exploit the real-time advantages of ultrasound and more conducive to clinical application, we proposed a whole-lesion-aware network based on freehand ultrasound video (WAUVE) scanning in an arbitrary direction for predicting overall breast cancer risk score.

Methods: The WAUVE was developed using 2912 videos (2912 lesions) of 2771 patients retrospectively collected from May 2020 to August 2022 in two hospitals. We compared the diagnostic performance of WAUVE with static 2D-ResNet50 and dynamic TimeSformer models in the internal validation set. Subsequently, a dataset comprising 190 videos (190 lesions) from 175 patients prospectively collected from December 2022 to April 2023 in two other hospitals, was used as an independent external validation set. A reader study was conducted by four experienced radiologists on the external validation set. We compared the diagnostic performance of WAUVE with the four experienced radiologists and evaluated the auxiliary value of model for radiologists.

Results: The WAUVE demonstrated superior performance compared to the 2D-ResNet50 model, while similar to the TimeSformer model. In the external validation set, WAUVE achieved an area under the receiver operating characteristic curve (AUC) of 0.8998 (95% CI = 0.8529-0.9439), and showed a comparable diagnostic performance to that of four experienced radiologists in terms of sensitivity (97.39% vs. 98.48%, p = 0.36), specificity (49.33% vs. 50.00%, p = 0.92), and accuracy (78.42% vs.79.34%, p = 0.60). With the WAUVE model assistance, the average specificity of four experienced radiologists was improved by 6.67%, and higher consistency was achieved (from 0.807 to 0.838).

Conclusion: The WAUVE based on non-standardized ultrasound scanning demonstrated excellent performance in breast cancer assessment which yielded outcomes similar to those of experienced radiologists, indicating the clinical application of the WAUVE model promising.

Background: Pulmonary lesions inconclusive in ¹⁸F-FDG PET/CT are a known clinical problem. Both texture analysis and ⁶⁸Ga-FAPI-46 have shown potential in thoracic oncological problems but their combination has not been assessed yet. This initial analysis aims to evaluate the utility of ⁶⁸Ga-FAPI-46 PET texture parameters to differentiate between lung cancer and benign pulmonary lesions inconclusive in ¹⁸F-FDG PET/CT.

Materials and methods: 20 histologically confirmed pulmonary lesions (13 lung cancer, 7 benign) in 19 patients were evaluated. All patients underwent an inconclusive ¹⁸F-FDG PET/CT before ⁶⁸Ga-FAPI-46 PET/CT. 64 texture parameters and conventional parameters (SUVs, TBRs) were analyzed. Texture parameters with significant (P < 0.05) differences between lung cancer and benign lesions were detected by the Mann-Whitney U test. Boxplots and a scatter plot matrix were created. Principal component analyses and Spearman correlations were performed. Receiver operating characteristics curves with area under the curve (AUC) values were created for univariable and bivariable logistic regression.

Results: The texture parameters HIST Maximum grey level (AUC = 0.901), HIST Mean (AUC = 0.802), HIST Mode (AUC = 0.835), HIST Range (AUC = 0.901) and GLCM Information correlation 1 (AUC = 0.824) showed significant differences between lung cancer and benign pulmonary lesions. AUC values of conventional parameters (SUVmax, SUVmean, TBR(SUVmax), TBR(SUVmean)) were 0.791, 0.868, 0.802 and 0.857, respectively. Maximum AUC values of bivariable logistic regression were 0.967 and 0.978 for two texture parameters and the combination of conventional and texture parameters, respectively. Correlations between texture parameter pairs were mainly moderate (0.4≤ρ≤0.59). 2/5 texture parameters (HIST Mean, HIST Mode) displayed no very strong correlations (0.8≤ρ≤1.00) to any conventional parameters or lesion volume.

Conclusion: ⁶⁸Ga-FAPI-46 PET texture parameters show great potential to differentiate between lung cancer and benign pulmonary lesions inconclusive in ¹⁸F-FDG/PET. Spearman correlations indicate additional information value of texture parameters.

Objectives: This research aimed to examine the relationships between clinicopathological characteristics and the occurrence of Spread Through Air Spaces (STAS) in patients with stage IA lung adenocarcinoma (LUAD) and to develop a preoperative prediction model.

Methods: Data from 1,375 patients with stage IA LUAD at Sun Yat-sen University Cancer Center were analyzed. Propensity score matching (PSM) was employed to match 141 STAS-positive patients with 282 STAS-negative patients. Both univariate and multivariate logistic regression analyses were performed to determine independent variables among 16 clinicopathological and 13 CT imaging characteristics. A nomogram prediction model was developed and evaluated via receiver operating characteristic (ROC) and decision curve analyses (DCAs).

Results: Multivariate analysis identified several independent risk factors. Irregular nodule shape (OR = 1.817, 95% CI: 1.106-2.986, p = 0.018), irregular margin (OR = 2.050, 95% CI: 1.218-3.449, p = 0.007), lobulation (OR = 2.235, 95% CI: 1.336-3.739, p = 0.002), and vascular convergence (OR = 5.032, 95% CI: 2.050-12.349, p < 0.001) were significantly associated with an increased risk of STAS. Compared with a consolidation tumor ratio (CTR) = 0% (reference), a CTR of 75-100% (OR = 7.086, 95% CI: 2.542-19.750, p < 0.001) and a CTR = 100% (OR = 11.502, 95% CI: 4.752-27.840, p < 0.001) were significantly associated with an increased risk of STAS. The nomogram was developed and internally validated, demonstrating good predictive accuracy (AUC = 0.812, 95% CI: 0.761-0.863) and favorable clinical utility, with a sensitivity of 69.5% and a specificity of 80.2%.

Conclusion: The nomogram reliably predicts STAS preoperatively and may assist in guiding surgical decision-making.

Background: The aim of this study was to investigate the prediction value of metabolic response using gallium 68 (⁶⁸Ga) labeled fibroblast-activation protein inhibitor (⁶⁸Ga-FAPI) positron emission tomography-computed tomography (PET/CT) in Non-Hodgkin lymphoma (NHL) patients receiving (cyclophosphamide-doxorubicin HCl-vincristine[Oncovin]- prednisone) CHOP-like chemotherapy.

Method: This single-center prospective study was conducted in our hospital and enrolled participants who was initially diagnosed with NHL and received CHOP-like chemotherapy. ⁶⁸Ga-FAPI PET/CT was performed before chemotherapy. Metabolic response was assessed by fluorine 18 (¹⁸F) labeled fluorodeoxyglucose (¹⁸F-FDG) PET/CT. Quantitative analysis included measurement of the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), peak standardized uptake value (SUVpeak), metabolic tumor volume (MTV) and total lesion FAP (TLF). The SUVmax value of the lesion is divided by SUVmean of normal tissue to calculate the target-to-background ratio (TBRblood and TBRmuscle). Depending on the response, participants were categorized as responders and non-responders. Mann-Whitney U-test was used to compare the ⁶⁸Ga-FAPI PET/CT parameters of responders with that of non-responders. Logistic regression analyses were performed to determine the relationship between clinical characteristics, ⁶⁸Ga-FAPI PET/CT parameters, and efficacy of chemotherapy. Receiver operating characteristic curve analysis was used to identify the accuracy of ⁶⁸Ga-FAPI PET/CT parameters for response prediction.

Results: From October 2022 to May 2023, 18 participants (10 men and 8 women; median age: 56 years [interquartile range: 47-67 years]) with pathologically confirmed diagnosis of non-Hodgkin's lymphoma were recruited in our hospital and enrolled in this study. The mean values of SUVmax, TBRblood, and TBRmuscle were significantly higher in responders than those in non-responders (8.41[Formula: see text]3.90 vs. 3.98[Formula: see text]2.81 P=0.025; 7.93[Formula: see text]3.31 vs. 3.69[Formula: see text]2.36 P=0.035; 7.04[Formula: see text]3.22 vs. 3.09[Formula: see text]1.73 P = 0.025; respectively). The area under the curve (AUC) of SUVmax, TBRblood, and TBRmuscle were statistically significant (0.875, P = 0.025; 0.857, P=0.034; 0.875, P = 0.026, respectively). SUVmax (OR=0.592, P = 0.041) is a significant factor in the prognosis of these participants.

Conclusion: Low radiotracer uptake on ⁶⁸Ga-FAPI PET/CT indicated poor metabolic response of NHL patients received CHOP-like therapy. SUVmax could be used to screen sensitive patients.

Purpose: To evaluate the prognostic value of early post-treatment ¹⁸F-FDG PET/CT in diffuse large B-cell lymphoma (DLBCL) patients undergoing chimeric antigen receptor T-cell (CAR-T) therapy.

Methods: In this retrospective study, 159 patients referred for imaging prior to CAR-T therapy between January 2018 and May 2023 were reviewed. Of those, 51 with both baseline pre-infusion and one-month post-treatment ¹⁸F-FDG PET/CTs were included. ¹⁸F-FDG PET/CT parameters were derived, including standard uptake values (SUVs), metabolic tumour volume (MTV), total lesion glycolysis (TLG), and Dmax. Additionally, the delta changes from the baseline were calculated. Time to progression/death was documented. For progression-free survival (PFS) and overall survival (OS), univariate analysis was performed using the Kaplan-Meier method. The significance of the difference was measured using the Mantel-Cox log-rank test. Significant parameters entered the multiple Cox regression.

Results: Overall, 51 patients (mean age = 56y) entered the study. All had Deauville scores of 4 (14/51; 28%) or 5 (37/51; 72%) at baseline. At one month, 28% of patients showed a complete metabolic response, while 72% had ¹⁸F-FDG-avid significant residual disease. Investigating those with residual disease, SUVmax, SUVpeak, SUVmax-to-Liver ratio and MTV were significantly lower in the one-month post-treatment scan. For PFS evaluation, serum LDH, one-month post-treatment SUVmax-to-liver ratio, one-month post-treatment TLG, and baseline Dmax entered the multivariate analysis. The one-month post-treatment SUVmax-to-liver ratio (Hazard ratio [HR] = 5.21; p = 0.004) and baseline Dmax (HR = 13.8; p = 0.013) retained significance, being independent predictors of PFS. For OS, serum LDH, delta SUVmean-to-liver ratio, delta percentage TLG, and one-month post-treatment Dmax were included in the multivariate analysis. The delta percentage TLG (HR = 4.37; p = 0.023) remained significant as an independent predictor of OS.

Conclusion: Early post-treatment ¹⁸F-FDG PET/CT can provide valuable prognostic information for DLBCL patients receiving CAR-T. The most significant predictors of outcomes would be the baseline extent of the disease, one-month post-treatment avidity, and changes in the metabolic burden from baseline.