Extraperitoneal pelvic packing versus angiographic embolization for hemodynamically unstable pelvic fractures: a retrospective single-center analysis.

OBJECTIVE: To retrospectively analyze the clinical data and treatment procedures of angiographic embolization (AE) and extraperitoneal pelvic packing (EPP) for traumatic pelvic fractures in our center for the purpose of providing recommendations on the selection of treatment protocols. METHODS: We analyzed 110 patients with traumatic pelvic fractures treated with AE and EPP from January 2015 to May 2023. The patients were divided into the AE group (69 men, 41 women) and the EPP group (20 men, 12 women). The primary outcomes were the mortality rate and incidence of complications. RESULTS: The mortality rate was slightly lower in the AE than EPP group (7.3% vs. 9.4%). The overall blood transfusion volume was lower and the length of hospital stay was shorter in the AE than EPP group (7.79 ± 12.04 vs. 9.14 ± 14.21 units and 20.48 ± 11.32 vs. 22.14 ± 10.47 days). CONCLUSIONS: Both AE and EPP have good treatment effects. AE is preferred for patients in stable condition with severe hemorrhage. This study suggests that EPP should be the primary treatment and that AE should serve as a complementary treatment for critical patients.

Integration of quantitative diffusion kurtosis imaging and prostate specific antigen in differential diagnostic of prostate cancer.

ABSTRACT: This study aimed to evaluate the diagnostic performance of diffusion kurtosis imaging (DKI) and prostate-specific antigen (PSA) biomarkers in differentiating prostate cancer (PCa) and benign prostatic hyperplasia (BPH).A total of 43 cases of prostate diseases verified by pathology were enrolled in the present study. These cases were assigned to the BPH group (n = 20, 68.85±10.81 years old) and PCa group (n = 23, 74.13 ±â€Š7.37 years old). All patients underwent routine prostate magnetic resonance imaging and DKI examinations, and the mean diffusivity (MD), mean kurtosis (MK), and fractional anisotropy (FA) values were calculated. Three serum indicators (PSA, free PSA [fPSA], and f/t PSA) were collected. We used univariate logistic regression to analyze the above quantitative parameters between the 2 groups, and the independent factors were further incorporated into the multivariate logistic regression model. The area under the receiver operating characteristic curve (AUC) was used to evaluate the diagnostic efficacy of the single indicator and combined model.The difference in PSA, f/t PSA, MK, and FA between PCa and BPH was statistically significant (P < .05). The AUC for the combined model (f/t PSA, MK, and FA) of 0.972 (95% confidence interval [CI]: 0.928, 1.000) was higher than the AUC of 0.902 (95% CI: 0.801, 1.000) for f/t PSA, 0.833 (95% CI: 0.707, 0.958) for MK, and 0.807 (95% CI: 0.679, 0.934) for FA.The MK and FA values for DKI and f/t PSA effectively identify PCa and BPH, compared to the PSA indicators. Combining DKI and PSA derivatives can further improve the diagnosis efficiency and might help in the clinical setting.

An Illustrated Guide to the Imaging Evolution of COVID in Non-Epidemic Areas of Southeast China.

Purpose: By analyzing the CT manifestations and evolution of COVID in non-epidemic areas of southeast China, analyzing the developmental abnormalities and accompanying signs in the early and late stages of the disease, providing imaging evidence for clinical diagnosis and identification, and assisting in judging disease progression and monitoring prognosis. Methods: This retrospective and multicenter study included 1,648 chest CT examinations from 693 patients with laboratory-confirmed COVID-19 infection from 16 hospitals of southeast China between January 19 and March 27, 2020. Six trained radiologists analyzed and recorded the distribution and location of the lesions in the CT images of these patients. The accompanying signs include crazy-paving sign, bronchial wall thickening, microvascular thickening, bronchogram sign, fibrous lesions, halo and reverse-halo signs, nodules, atelectasis, and pleural effusion, and at the same time, they analyze the evolution of the abovementioned manifestations over time. Result: There were 1,500 positive findings in 1,648 CT examinations of 693 patients; the average age of the patients was 46 years, including 13 children; the proportion of women was 49%. Early CT manifestations are single or multiple nodular, patchy, or flaky ground-glass-like density shadows. The frequency of occurrence of ground-glass shadows (47.27%), fibrous lesions (42.60%), and microvascular thickening (40.60%) was significantly higher than that of other signs. Ground-glass shadows increase and expand 3-7 days after the onset of symptoms. The distribution and location of lesions were not significantly related to the appearance time. Ground-glass shadow is the most common lesion, with an average absorption time of 6.2 days, followed by consolidation, with an absorption time of about 6.3 days. It takes about 8 days for pure ground-glass lesions to absorb. Consolidation change into ground glass or pure ground glass takes 10-14 days. For ground-glass opacity to evolve into pure ground-glass lesions, it takes an average of 17 days. For ground-glass lesions to evolve into consolidation, it takes 7 days, pure ground-glass lesions need 8 days to evolve into ground-glass lesions. The average time for CT signs to improve is 10-15 days, and the first to improve is the crazy-paving sign and nodules; while the progression of the disease is 6-12 days, the earliest signs of progression are air bronchogram signs, bronchial wall thickening, and bronchiectasis. There is no severe patient in this study. Conclusion: This study depicts the CT manifestation and evolution of COVID in non-epidemic origin areas, and provides valuable first-hand information for clinical diagnosis and judgment of patient's disease evolution and prediction.

Study on diagnostic value of quantitative parameters of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in prostate cancer.

OBJECTIVE: To investigate the diagnostic value of quantitative parameters of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in prostate cancer. METHODS: From January 2019 to June 2020, 96 patients with prostatic tumor admitted in the department of urological surgery of our hospital were selected as subjects. Magnetic resonance imaging data of 48 cases of benign prostatic hyperplasia and 48 cases of prostate cancer were retrospectively analyzed. The patients included in this study received conventional MRI and IVIM-DWI examinations. Quantitative parameters of IVIM-DWI including D value, D* value, apparent diffusion coefficient (ADC) value and f value in lesions of prostatic tumor were calculated through the double exponential model fitting algorithm. D value, D* value, ADC value and f value were compared between benign prostatic hyperplasia (BPH) group and prostate cancer group. Quantitative parameters of IVIM-DWI were also compared among patients from different Gleason scores groups. The correlation of quantitative parameters of IVIM-DWI with Gleason scores and PSA concentration was analyzed. Diagnostic efficiency of quantitative parameters of IVIM-DWI for prostate cancer was evaluated by ROC curve. RESULTS: Compared with those in BPH group, D value, ADC value and f value in prostate cancer group were significantly lower, but D* value was obviously higher. With the Gleason score increased, D value, ADC value and f value gradually decreased, while D* value gradually increased. The diagnostic efficiency of parameters ADC and D was higher among other parameters. D value, ADC value and f value of prostate cancer were negatively correlated with Gleason score and PSA concentration, respectively (all P<0.05), while D* value was positively correlated with Gleason score and PSA concentration. CONCLUSIONS: Quantitative parameters of IVIM-DWI could be used for the diagnosis and evaluation of prostate cancer, and quantitative parameters of IVIM-DWI were associated with Gleason score and PSA concentration.

Temporal changes of COVID-19 pneumonia by mass evaluation using CT: a retrospective multi-center study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has widely spread worldwide and caused a pandemic. Chest CT has been found to play an important role in the diagnosis and management of COVID-19. However, quantitatively assessing temporal changes of COVID-19 pneumonia over time using CT has still not been fully elucidated. The purpose of this study was to perform a longitudinal study to quantitatively assess temporal changes of COVID-19 pneumonia. METHODS: This retrospective and multi-center study included patients with laboratory-confirmed COVID-19 infection from 16 hospitals between January 19 and March 27, 2020. Mass was used as an approach to quantitatively measure dynamic changes of pulmonary involvement in patients with COVID-19. Artificial intelligence (AI) was employed as image segmentation and analysis tool for calculating the mass of pulmonary involvement. RESULTS: A total of 581 confirmed patients with 1,309 chest CT examinations were included in this study. The median age was 46 years (IQR, 35-55; range, 4-87 years), and 311 (53.5%) patients were male. The mass of pulmonary involvement peaked on day 10 after the onset of initial symptoms. Furthermore, the mass of pulmonary involvement of older patients (>45 years) was significantly severer (P<0.001) and peaked later (day 11 vs. day 8) than that of younger patients (≤45 years). In addition, there were no significant differences in the peak time (day 10 vs. day 10) and median mass (P=0.679) of pulmonary involvement between male and female. CONCLUSIONS: Pulmonary involvement peaked on day 10 after the onset of initial symptoms in patients with COVID-19. Further, pulmonary involvement of older patients was severer and peaked later than that of younger patients. These findings suggest that AI-based quantitative mass evaluation of COVID-19 pneumonia hold great potential for monitoring the disease progression.

MRI and the pathology of breast invasive micropapillary carcinoma.

Diagnosis of breast invasive micropapillary carcinoma (IMPC) before surgery is of great value for determining the optimal treatment strategy. The aim of the present study was to investigate the magnetic resonance imaging (MRI) and pathological features of IMPC. MRI features of IMPC were characterized in relation to the patients' clinicopathological features. Clinical manifestations, mammography results and/or MRI findings of patients with IMPC were retrospectively analyzed. Parameters included morphology, plain T2-weighted imaging (T2WI) signal intensity, the apparent diffusion coefficient (ADC), the internal enhancement mode, early enhancement rates and time-intensity curve (TIC) types during dynamic enhanced scanning. A total of 10 lesions were detected by MRI in eight patients, with one case having three lesions with the mean diameter of 34.44 mm. In plain T2WI scanning, the lesions appeared inhomogeneous with a moderate or high signal intensity. When the b value was 800 sec/mm2, the average ADC value was 0.823±0.12×10-3 mm2/sec. A total of four cases exhibited mass-like enhancement, including an oval rim in one case (three lesions), irregular inhomogeneous enhancement in two cases and irregular uniform enhancement in one case. The margins were clear in one case (three lesions), irregular in two cases and spiculate in one case. Among the four cases with non-mass enhancement, the distribution was focal in two cases, linear in one case and regional in one case, and the internal enhancement mode was cluster-like in one case, heterogeneous in one case and uniform in two cases. The average early enhancement rate was 116.96±45.26%. TICs of type III were observed in all cases. In conclusion, MRI of IMPC demonstrated typical features of malignant tumors and lymphatic vessel infiltration, suggesting that MRI may exhibit guiding significance for the diagnosis and treatment planning of IMPC.

Magnetic resonance imaging in categorization of ovarian epithelial cancer and survival analysis with focus on apparent diffusion coefficient value: correlation with Ki-67 expression and serum cancer antigen-125 level.

BACKGROUND: To determine whether magnetic resonance (MR) imaging features combined with apparent diffusion coefficient (ADC) values could be used as a tool for categorizing ovarian epithelial cancer (OEC) and predicting survival, as well as correlating with laboratory tests (serum cancer antigen 125, serum CA-125) and tumor proliferative index (Ki-67 expression). METHODS AND MATERIALS: MRI examination was undertaken before invasive procedures. MRI features were interpreted and recorded on the picture archive communication system (PACS). ADC measurements were manually performed on post-process workstation. Clinical characteristics were individually retrieved and recorded through the hospital information system (HIS). Cox hazard model was used to estimate the effects of both clinical and MRI features on overall survival. RESULTS: Both clinical and MRI features differed significantly between Type I and Type II cancer groups (p < 0.05). The mean ADC value was inversely correlated with Ki-67 expression in Type I cancer (ρ = - 0.14, p < 0.05). A higher mean ADC value was more likely to suggest Type I ovarian cancer (Odds Ratio (OR) = 16.80, p < 0.01). Old age and an advanced International Federation of Gynecology and Obstetrics (FIGO) stage were significantly related to Type II ovarian cancer (OR = 0.22/0.02, p < 0.05). An advanced FIGO stage, solid components, and old age were significantly associated with poor survival (Hazard Ratio (HR) = 23.54/3.69/2.46, p < 0.05). Clear cell cancer type had a poorer survival than any other pathological subtypes of ovarian cancer (HR = 13.6, p < 0.01). CONCLUSIONS: MR imaging features combined with ADC value are helpful in categorizing OEC. ADC values can reflect tumor proliferative ability. A solid mass may predict poor prognosis for OEC patients.

Optimizing prostate cancer accumulating model: combined PI-RADS v2 with prostate specific antigen and its derivative data.

BACKGROUND: To establish a new accumulating model to enhance the accuracy of prostate cancer (PCa) diagnosis by incorporating prostate-specific antigen (PSA) and its derivative data into the Prostate Imaging-Reporting and Data System version 2 (PI-RADS v2). METHODS: A total of 357 patients who underwent prostate biopsy between January 2014 and December 2017 were included in this study. All patients had 3.0 T multiparametric magnetic resonance imaging (MRI) and complete laboratory examinations. PI-RADS v2 was used to assess the imaging. PSA, PSA density (PSAD), the free/total PSA ratio (f/t PSA) and the Gleason score (GS) were classified into four-tiered levels, and optimal weights were pursued on these managed levels to build a PCa accumulating model. A receiver operating characteristic curve was generated. RESULTS: In all, 174 patients (48.7%) had benign prostatic hyperplasia, and 183 (51.3%) had PCa, among whom 149 (81.4%, 149/183) had clinically significant PCa. The established model 6 (PI-RADS v2 + level of PSAD + level of f/t PSA+ level of PSA) had a sensitivity and specificity of 81.4 and 84.5%, respectively, at the cut-off point of 11 in PCa diagnosis. Correspondingly, at the 12 cut-off point, the sensitivity and specificity were 87.7 and 83.0%, respectively, in diagnosing clinically significant PCa. The score of the new accumulating system was significantly different among the defined GS groups (p < 0.001). The mean values and 95% confidence intervals for GS 1-4 groups were 10.20 (9.63-10.40), 12.03 (11.19-12.87), 14.12 (13.60-14.64) and 15.44 (15.09-15.79). CONCLUSIONS: A new PCa accumulating model may be useful in improving the accuracy of the primary diagnosis of PCa and helpful in the clinical decision to perform a biopsy when MRI results are negative.

Magnetic resonance imaging radiomics in categorizing ovarian masses and predicting clinical outcome: a preliminary study.

PURPOSE: To evaluate the ability of MRI radiomics to categorize ovarian masses and to determine the association between MRI radiomics and survival among ovarian epithelial cancer (OEC) patients. METHOD: A total of 286 patients with pathologically proven adnexal tumor were retrospectively included in this study. We evaluated diagnostic performance of the signatures derived from MRI radiomics in differentiating (1) between benign adnexal tumors and malignancies and (2) between type I and type II OEC. The least absolute shrinkage and selection operator method was used for radiomics feature selection. Risk scores were calculated from the Lasso model and were used for survival analysis. RESULT: For the classification between benign and malignant masses, the MRI radiomics model achieved a high accuracy of 0.90 in the leave-one-out (LOO) cross-validation cohort and an accuracy of 0.87 in the independent validation cohort. For the classification between type I and type II subtypes, our method made a satisfactory classification in the LOO cross-validation cohort (accuracy = 0.93) and in the independent validation cohort (accuracy = 0.84). Low-high-high short-run high gray-level emphasis and low-low-high variance from coronal T2-weighted imaging (T2WI) and eccentricity from axial T1-weighted imaging (T1WI) images had the best performance in two classification tasks. The patients with higher risk scores were more likely to have poor prognosis (hazard ratio = 4.1694, p = 0.001). CONCLUSION: Our results suggest radiomics features extracted from MRI are highly correlated with OEC classification and prognosis of patients. MRI radiomics can provide survival estimations with high accuracy. KEY POINTS: • The MRI radiomics model could achieve a higher accuracy in discriminating benign ovarian diseases from malignancies. • Low-high-high short-run high gray-level emphasis, low-low-high variance from coronal T2WI, and eccentricity from axial T1WI had the best performance outcomes in various classification tasks. • The ovarian cancer patients with high-risk scores had poor prognosis.

Massive localized malignant pleural mesothelioma (LMPM): manifestations on computed tomography in 6 cases.

OBJECTIVE: Our study analyzed the clinical symptoms and computed tomography (CT) manifestations of massive localized malignant pleural mesothelioma (LMPM) patients to improve the knowledge and diagnosis of this disease. METHODS: Our study collected 6 massive LMPM patients pathologically confirmed by CT in the department of Radiology of the People's Hospital of Yuyao, Zhejiang Province, from January, 2007 to June, 2013; data of patients were also collected. The clinical symptoms, clinicopathological characteristics, CT manifestations, treatments and prognosis of enrolled patients were analyzed. RESULTS: Our study enrolled 6 LMPM patients (2 males; 4 females) classified to epitheliated type (n = 4) and sarcomatous type (n = 2) with mean age of 62.7 ± 7.4, and 5 of them had a history of asbestos exposure. CT manifestations revealed that large soft-tissue mass close to pleura, which was smooth and lobulated, was discovered in all patients with maximum diameter of 10~15 cm and mean diameter of 13.67 ± 1.15 cm; The mean value of CT was 36.29 ± 2.62 HU; after enhancement, the mean value was increased to 76.36 ± 7.73 HU; patients showed zones of small patchy necrosis and large patchy necrosis. The following presentations were founded: enlargement of tumor vessel which showed arborization (2 patients), mass wrap around the descending aorta in left lower chest (1 patient), strips of fat density in mediastinum superior (1 patient), pleural tail sign (3 patients). Among 6 patients, pleural effusion (n = 4), mediastinal lymph node enlargement (n = 3), invasion and destruction of local ribs (n = 2). Median survival time of patients were 20 months (2 cases conducted operation), 24 (2 cases chose combined radiotherapy and chemotherapy) and less than 6 months (2 cases underwent chemotherapy). CONCLUSION: To sum up, CT showed important diagnostic values on massive LMPM patients; patients with a history of asbestos exposure, large soft-tissue mass of pleura with an abundant blood supply and wrap around large vessels might increase the risk of massive LMPM.