Objective:To evaluate the value of a combined model based on primary lesion 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT radiomics for predicting lymph node metastasis in non-small cell lung cancer (NSCLC) . Methods:A retrospective analysis was conducted on the clinical data of 203 NSCLC patients who underwent pre-treatment PET/CT imaging at Nanjing Drum Tower Hospital from June 2013 to July 2023. Patients were randomly assigned to the training set ( n=142) and the validation set ( n=61) at a ratio of 7∶3. A predictive model was developed in the training set, and its predictive performance and clinical application value were assessed in both the training and validation sets. Traditional PET/CT parameters and PET/CT radiomics features of the primary lesion were obtained by 3D-slicer software. Least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting were performed to extract features. Support vector machine was used to construct a radiomics score (Radscore). Univariate and multivariate logistic regression analysis was used to predict the influencing factors of lymph node metastasis in NSCLC patients and to establish models. Predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves and clinical application value was assessed by calibration curves and decision curve analysis (DCA) . Results:Among 203 NSCLC patients, 116 had lymph node metastasis, with 64 cases in the training set and 52 cases in the validation set. Three complementary classical machine learning methods were used for feature screening, and finally 10 radiomics features were obtained. The optimal threshold for Radscore-PET was 0.43 and the optimal threshold for Radscore-CT was 0.39. Univariate analysis showed that, sex ( OR=0.48, 95% CI: 0.24-0.95, P=0.036), tumor marker levels ( OR=3.81, 95% CI: 1.84-7.91, P<0.001), long diameter of tumor ( OR=2.56, 95% CI: 1.27-5.16, P=0.009), short diameter of tumor ( OR=3.73, 95% CI: 1.75-7.92, P=0.001), vacuolar sign ( OR=0.32, 95% CI: 0.12-0.86, P=0.024), ring-like metabolism ( OR=3.67, 95% CI: 1.33-10.13, P=0.012), maximum standardized uptake value (SUV max) ( OR=6.57, 95% CI: 3.03-14.25, P<0.001), metabolic tumor volume (MTV) ( OR=2.91, 95% CI: 1.43-5.92, P=0.003), total lesion glycolysis (TLG) ( OR=4.23, 95% CI: 2.08-8.59, P<0.001), Radscore-PET ( OR=21.93, 95% CI: 9.04-53.20, P<0.001) and Radscore-CT ( OR=13.72, 95% CI: 6.12-30.76, P<0.001) were all influencing factors for predicting lymph node metastasis in NSCLC patients. Multivariate analysis showed that, tumor marker levels ( OR=2.55, 95% CI: 1.11-5.90, P=0.028), vacuolar sign ( OR=0.26, 95% CI: 0.08-0.83, P=0.023), SUV max ( OR=5.94, 95% CI: 1.99-17.75, P=0.001), Radscore-PET ( OR=25.51, 95% CI: 5.92-110.22, P<0.001), and Radscore-CT ( OR=8.68, 95% CI: 2.73-27.61, P<0.001) were independent influencing factors for predicting lymph node metastasis in patients with NSCLC. Based on the above independent influencing factors, models were constructed: the traditional model (tumor marker levels, vacuolar sign, SUV max), the PET model (SUV max, Radscore-PET), the CT model (vacuolar sign, Radscore-CT), and the combined model (tumor marker levels, vacuolar sign, SUV max, Radscore-PET, Radscore-CT). ROC curve analysis showed that, the area under curve (AUC) of the traditional, PET, CT, and combined models in the training set were 0.75 (95% CI: 0.67-0.82), 0.90 (95% CI: 0.84-0.95), 0.85 (95% CI: 0.78-0.90), and 0.94 (95% CI: 0.88-0.97), respectively. The predictive value of the combined model was higher than that of the traditional model ( Z=5.01, P<0.001), the PET model ( Z=1.99, P=0.047), and the CT model ( Z=3.25, P=0.001). In the validation set, the AUCs for the traditional model, PET model, CT model, and combined model were 0.65 (95% CI: 0.52-0.77), 0.86 (95% CI: 0.74-0.93), 0.85 (95% CI: 0.73-0.93), and 0.90 (95% CI: 0.80-0.96), respectively. The predictive value of the combined model was superior to that of the traditional model ( Z=3.23, P=0.001). The sensitivity and specificity of the combined model in the training set were 84.37% and 91.03%, while in the validation set, the sensitivity and specificity were 82.61% and 94.74%, respectively. Calibration curves showed a good agreement between the predicted and actual probabilities in both the training and validation sets. DCA showed that the combined models had good discriminative ability in both the training and validation sets. Conclusions:Tumor marker levels, vacuolar sign, SUV max, Radscore-PET, and Radscore-CT are all independent influencing factors for predicting lymph node metastasis in patients with NSCLC. The combined model based on these factors demonstrates excellent predictive performance and clinical application value for predicting lymph node metastasis in NSCLC.

Objective:To evaluate the prognostic value of 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT metabolic parameters in small cell lung cancer (SCLC) . Methods:A retrospective analysis was conducted on the clinical and imaging data of 156 SCLC patients, who underwent 18F-FDG PET/CT imaging and were diagnosed by histopathological examination at Nanjing Drum Tower Hospital, Affiliated Hospital of Nanjing University Medical School from September 2013 to February 2024. The metabolic tumor volume (MTV), total lesion glycolysis (TLG), linear regression slope, area under the curve of cumulative standard uptake value (SUV) volume histogram (AUC-CSH), and coefficient of variation (CV) were calculated using LIFEx software with different SUV thresholds. Univariate and multivariate analyses were performed using Cox proportional hazards model. Patient stratification was based on the critical values determined by receiver operator characteristic (ROC) curve analysis. The survival curve was plotted using the Kaplan-Meier method and log-rank test was performed. Results:Univariate analysis showed that MTV 40% ( HR=2.91, 95% CI: 1.55-5.47, P=0.001), MTV 60% ( HR=2.31, 95% CI: 1.29-4.17, P=0.005), TLG 40% ( HR=2.07, 95% CI: 1.19-3.60, P=0.010), linear regression slope ( HR=0.45, 95% CI: 0.26-0.79, P=0.005), and CV 40% ( HR=0.27, 95% CI: 0.08-0.84, P=0.024) were factors affecting progression-free survival (PFS) in SCLC patients. MTV 40% ( HR=1.98, 95% CI: 1.22-3.22, P=0.005), MTV 60% ( HR=1.80, 95% CI: 1.12-2.88, P=0.015), MTV 80% ( HR=1.71, 95% CI: 1.08-2.74, P=0.024), TLG 40% ( HR=3.68, 95% CI: 1.59-8.49, P=0.002), linear regression slope ( HR=0.49, 95% CI: 0.30-0.80, P=0.004), and AUC-CSH 80% ( HR=0.44, 95% CI: 0.23-0.84, P=0.013) were found to be factors affecting overall survival (OS) in SCLC patients. Multivariate analysis revealed that MTV 40% ( HR=4.76, 95% CI: 1.11-20.50, P=0.036) was an independent factor influencing PFS, and TLG 40% ( HR=3.19, 95% CI: 1.02-9.92, P=0.046) was an independent factor influencing OS in SCLC patients. ROC curve analysis identified the optimal cutoff value for MTV 40% in predicting PFS as 5.5cm 3 and the optimal cutoff value for TLG 40% in predicting OS as 41.5 g in SCLC patients. Survival analysis showed that patients with MTV 40%≤5.5 cm 3 ( n=33) had a median PFS that was not reached, while patients with MTV 40%>5.5 cm 3 ( n=123) had a median PFS of 10.3 months, with a statistically significant difference ( χ2=12.09, P=0.001). For patients with TLG 40%≤41.5 g ( n=35), the median OS was not reached, whereas for TLG 40%>41.5 g ( n=121), the median OS was 31.6 months, with a statistically significant difference ( χ2=10.55, P=0.001) . Conclusions:The 18F-FDG PET/CT metabolic parameter MTV 40% is an independent factor influencing PFS, while TLG 40% is an independent factor influencing OS in SCLC patients. The above two parameters may serve as indicators for assessing the prognosis of SCLC patients.

Naval hospitals,the backbone of naval health service system,are the key to build a world-class naval health service system.On the basis of the requirements of military transformation and high-quality development of public hospitals,this paper summarized five aspects of high-quality development of naval hospitals,including directions and regulations,support and contribution of combats,efficiency,sustainable development momentum,and the expansion of service functions.It is very important to strengthen the top-level design and policy support for naval hospitals,to improve the level of governance and innovation,and to find the right target for the naval hospital construction in naval health service system reform.

Objective:To explore the prognostic value of a combined model of baseline 18F-FDG PET/CT tumor metabolic parameters and clinical factors for predicting progression-free survival (PFS) in Hodgkin′s lymphoma (HL). Methods:From January 2014 to May 2023, 171 HL patients (102 males, 69 females; median age 40 years) who underwent 18F-FDG PET/CT before treatment at the First Affiliated Hospital of Nanjing Medical University and Nanjing Drum Tower Hospital were retrospectively collected. HL patients from the First Affiliated Hospital of Nanjing Medical University were classified as the training set (101 patients) and HL patients from Nanjing Drum Tower Hospital were classified as the validation set (70 patients). Clinical factors and tumor metabolic parameters associated with PFS were determined by multivariate Cox regression analysis, and then the combined model and the independent model of each factor were constructed respectively. The consistency index (C-index) and AUC were used to evaluate the predictive efficacy of models, and nomogram was constructed based on the optimal model, and calibration curves were used to assess the goodness of fit of the models. The differences in Kaplan-Meier survival curves of the high-risk and low-risk groups were compared using log-rank test. Results:The multivariate Cox regression analysis indicated that the independent prognostic factors associated with PFS were the Lugano staging (hazard ratio ( HR)=3.10, 95% CI: 1.17-8.23, P=0.023), total metabolic tumor volume (TMTV) ( HR=2.65, 95% CI: 1.23-5.74, P=0.014), and maximum distance between tumors ( Dmax) ( HR=2.23, 95% CI: 1.02-4.85, P=0.044). These factors were used to construct the combined model, with the highest prognostic efficacy of the C-index for the training and validation sets of 0.692 and 0.653, and the AUC of 0.732 and 0.697, respectively. The calibration curves demonstrated that the predictions made by the combined model were in high agreement with the actual results in both the training and validation sets. The Kaplan-Meier analysis revealed a significantly lower PFS rate in the high-risk group compared to the low-risk group both in training and validation sets ( χ2 values: 5.88 and 4.52, P values: 0.015 and 0.033). Conclusion:The combined model incorporating tumor metabolic parameters and clinical factors improves prognostic efficacy in predicting PFS in HL patients.

Objective:To explore the value of baseline 18F-FDG PET/CT metabolic parameters and related clinical factors in the prognostic assessment of patients with angioimmunoblastic T-cell lymphoma (AITL). Methods:From July 2013 to December 2023, 70 patients with AITL (44 males, 26 females, age (63.9±9.6) years) from Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University (32 cases) as well as the First Affiliated Hospital of Nanjing Medical University (38 cases) who were diagnosed pathologically and underwent PET/CT imaging prior to treatment were retrospectively analyzed. PET/CT metabolic parameters (calculated using the 41%SUV max threshold method) and related clinical factors were collected. The optimal cut-off values of metabolic parameters were determined by using the ROC curve analysis. Cox proportional risk regression models were used for prognostic analyses, prediction models were constructed and efficacies were assessed by calibration curves and time-dependent ROC curves. Results:With the follow-up of 19.0(10.0, 33.3) months, disease progression or recurrence occurred in 51 patients, and 28 patients died. ROC curves showed that the optimal cut-off values on diagnosing AITL of total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), and SUV max were 767.1cm 3, 2159.6g and 13.0, respectively. TMTV (hazard ratio ( HR)=0.485, 95% CI: 0.252-0.935, P=0.031) and gender ( HR=0.441, 95% CI: 0.236-0.824, P=0.010) were independent risk factors for progression-free survival (PFS); TMTV ( HR=0.422, 95% CI: 0.178-0.997, P=0.049) and treatment regimen ( HR=0.346, 95% CI: 0.154-0.777, P=0.010) were independent risk factors for overall survival (OS). Time-dependent ROC curves indicated that the combined model of TMTV combining gender or treatment regimen had better prognostic results in predicting PFS (AUCs: 0.67-0.82) or OS (AUCs: 0.62-0.80) in patients with AITL. The calibration curve showed the predicted values of the combined models were in good consistency with the actual values. Conclusions:The metabolic parameter TMTV is an independent risk factor for PFS and OS in patients with AITL. The combined model of TMTV combining gender or treatment regimen can effectively improve the prognostic prediction efficacy of PFS or OS in patients with AITL.

Intravascular large B-cell lymphoma (IVLBCL) is a rare large B-cell lymphoma subtype. We report a patient who presented with "recurrent fever and pancytopenia." A 64-year-old female patient had previously been diagnosed with Waldenstrom’s macroglobulinemia and had received zanubrutinib treatment. In February 2023, the patient revisited due to "recurrent fever and pancytopenia." A positron emission tomography/computed tomography scan demonstrated significant enlargement of the bilateral adrenal glands. After an adrenal biopsy, she was diagnosed with diffuse large B-cell lymphoma, not otherwise specified. The patient received chemotherapy with the R-CHOP regimen (rituximab + cyclophosphamide + doxorubicin + vincristine + prednisone). After three treatment courses, a cranial magnetic resonance imaging examination indicated central nervous system infiltration of the lymphoma. After reviewing the pathology of the adrenal biopsy, the final diagnosis was revised as IVLBCL. Despite aggressive treatment, the disease continued to progress, and the patient died two months later. According to a multidisciplinary level, this article discusses the case from the perspective of a multidisciplinary team collaboration, involving imaging, pathology, dermatology, and lymphoma, to provide reference opinions for the clinical diagnosis and treatment of IVLBCL.

Intravascular large B cell lymphoma (IVLBCL) is a rare, aggressive subtype of diffuse large B cell lymphoma, with nasal turbinate involvement being uncommon. We report a 51-year-old woman with a 1-month history of fever of unknown origin. Laboratory findings showed cytopenia, hypertriglyceridemia, elevated ferritin, increased soluble CD25, and bone marrow hemophagocytosis. No infectious cause was identified. PET-CT revealed abnormal 18F-fluorodeoxyglucose (FDG) uptake in the nasal turbinates. Turbinate biopsy revealed tumor cells localized predominantly within vascular lumens, positive for CD20, BCL6, PAX5, and MUM1, with a Ki-67 index >60%, confirming a diagnosis of IVLBCL with hemophagocytic lymphohistiocytosis (HLH). The patient received one cycle of the DEP regimen (liposomal doxorubicin, etoposide, and methylprednisolone) for HLH, followed by five cycles of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) and consolidation with auto-HSCT, achieving sustained complete remission. IVLBCL outcomes are heterogeneous; early diagnosis and prompt treatment improve survival, and R-CHOP plus auto-HSCT may be an effective strategy.

Objective:To explore the prognostic value of a combined model of baseline 18F-FDG PET/CT tumor metabolic parameters and clinical factors for predicting progression-free survival (PFS) in Hodgkin′s lymphoma (HL). Methods:From January 2014 to May 2023, 171 HL patients (102 males, 69 females; median age 40 years) who underwent 18F-FDG PET/CT before treatment at the First Affiliated Hospital of Nanjing Medical University and Nanjing Drum Tower Hospital were retrospectively collected. HL patients from the First Affiliated Hospital of Nanjing Medical University were classified as the training set (101 patients) and HL patients from Nanjing Drum Tower Hospital were classified as the validation set (70 patients). Clinical factors and tumor metabolic parameters associated with PFS were determined by multivariate Cox regression analysis, and then the combined model and the independent model of each factor were constructed respectively. The consistency index (C-index) and AUC were used to evaluate the predictive efficacy of models, and nomogram was constructed based on the optimal model, and calibration curves were used to assess the goodness of fit of the models. The differences in Kaplan-Meier survival curves of the high-risk and low-risk groups were compared using log-rank test. Results:The multivariate Cox regression analysis indicated that the independent prognostic factors associated with PFS were the Lugano staging (hazard ratio ( HR)=3.10, 95% CI: 1.17-8.23, P=0.023), total metabolic tumor volume (TMTV) ( HR=2.65, 95% CI: 1.23-5.74, P=0.014), and maximum distance between tumors ( Dmax) ( HR=2.23, 95% CI: 1.02-4.85, P=0.044). These factors were used to construct the combined model, with the highest prognostic efficacy of the C-index for the training and validation sets of 0.692 and 0.653, and the AUC of 0.732 and 0.697, respectively. The calibration curves demonstrated that the predictions made by the combined model were in high agreement with the actual results in both the training and validation sets. The Kaplan-Meier analysis revealed a significantly lower PFS rate in the high-risk group compared to the low-risk group both in training and validation sets ( χ2 values: 5.88 and 4.52, P values: 0.015 and 0.033). Conclusion:The combined model incorporating tumor metabolic parameters and clinical factors improves prognostic efficacy in predicting PFS in HL patients.

Objective:To explore the value of baseline 18F-FDG PET/CT metabolic parameters and related clinical factors in the prognostic assessment of patients with angioimmunoblastic T-cell lymphoma (AITL). Methods:From July 2013 to December 2023, 70 patients with AITL (44 males, 26 females, age (63.9±9.6) years) from Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University (32 cases) as well as the First Affiliated Hospital of Nanjing Medical University (38 cases) who were diagnosed pathologically and underwent PET/CT imaging prior to treatment were retrospectively analyzed. PET/CT metabolic parameters (calculated using the 41%SUV max threshold method) and related clinical factors were collected. The optimal cut-off values of metabolic parameters were determined by using the ROC curve analysis. Cox proportional risk regression models were used for prognostic analyses, prediction models were constructed and efficacies were assessed by calibration curves and time-dependent ROC curves. Results:With the follow-up of 19.0(10.0, 33.3) months, disease progression or recurrence occurred in 51 patients, and 28 patients died. ROC curves showed that the optimal cut-off values on diagnosing AITL of total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), and SUV max were 767.1cm 3, 2159.6g and 13.0, respectively. TMTV (hazard ratio ( HR)=0.485, 95% CI: 0.252-0.935, P=0.031) and gender ( HR=0.441, 95% CI: 0.236-0.824, P=0.010) were independent risk factors for progression-free survival (PFS); TMTV ( HR=0.422, 95% CI: 0.178-0.997, P=0.049) and treatment regimen ( HR=0.346, 95% CI: 0.154-0.777, P=0.010) were independent risk factors for overall survival (OS). Time-dependent ROC curves indicated that the combined model of TMTV combining gender or treatment regimen had better prognostic results in predicting PFS (AUCs: 0.67-0.82) or OS (AUCs: 0.62-0.80) in patients with AITL. The calibration curve showed the predicted values of the combined models were in good consistency with the actual values. Conclusions:The metabolic parameter TMTV is an independent risk factor for PFS and OS in patients with AITL. The combined model of TMTV combining gender or treatment regimen can effectively improve the prognostic prediction efficacy of PFS or OS in patients with AITL.

Intravascular large B-cell lymphoma (IVLBCL) is a rare large B-cell lymphoma subtype. We report a patient who presented with "recurrent fever and pancytopenia." A 64-year-old female patient had previously been diagnosed with Waldenstrom’s macroglobulinemia and had received zanubrutinib treatment. In February 2023, the patient revisited due to "recurrent fever and pancytopenia." A positron emission tomography/computed tomography scan demonstrated significant enlargement of the bilateral adrenal glands. After an adrenal biopsy, she was diagnosed with diffuse large B-cell lymphoma, not otherwise specified. The patient received chemotherapy with the R-CHOP regimen (rituximab + cyclophosphamide + doxorubicin + vincristine + prednisone). After three treatment courses, a cranial magnetic resonance imaging examination indicated central nervous system infiltration of the lymphoma. After reviewing the pathology of the adrenal biopsy, the final diagnosis was revised as IVLBCL. Despite aggressive treatment, the disease continued to progress, and the patient died two months later. According to a multidisciplinary level, this article discusses the case from the perspective of a multidisciplinary team collaboration, involving imaging, pathology, dermatology, and lymphoma, to provide reference opinions for the clinical diagnosis and treatment of IVLBCL.