Objective:To explore the value of conventional magnetic resonance imaging (MRI), diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI) sequence and pathological examination in predicting the efficacy of neoadjuvant chemotherapy (NAC) in advanced breast cancer.Methods:The clinical data of 65 cases of advanced breast cancer with NAC confirmed by pathology in the Affiliated Hospital of Jining Medical University from March 2022 to May 2023 were retrospectively analyzed, including 20 cases in the pathological complete remission (pCR) group and 45 cases in the non pCR group; All patients underwent routine MRI, DWI, DKI examinations and pathological analysis. The clinical pathological data, routine MRI features, apparent diffusion coefficient (ADC) values, mean kurtosis coefficient (MK), and mean diffusion coefficient (MD) between the two groups were analyzed; We compared the differences in various parameters between two groups and plotted receiver operating characteristic (ROC) curves to compare their diagnostic efficacy of NAC in breast cancer.Results:There were significant differences in molecular typing, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (Her-2) and Ki-67 between pCR group and non pCR group (all P<0.05). In pCR group, Her-2 overexpression type and triple negative breast cancer (TNBC) type breast cancer were more common. ER and PR were mostly negative, Her-2 was mostly positive, and Ki 67 was mainly positive. The difference in tumor T2WI signal between the pCR group and the non pCR group was statistically significant ( P<0.05), with the pCR group showing mostly moderate/low T2WI signal. The ADC and MD values of the pCR group were lower than those of the non pCR group, while the MK value of the pCR group was higher than that of the non pCR group, and the differences were statistically significant (all P<0.001). The area under the ROC curve (AUC) for predicting the efficacy of NAC using a clinical pathological model was 0.829, which was higher than the AUC of molecular subtypes, ER, PR, Her-2, and Ki-67 ( Z=3.008, 2.697, 2.815, 2.131, 2.376, all P<0.05); The AUC of the DKI+ DWI predicting the efficacy of NAC was 0.934, which was higher than that of the DWI single sequence model, and the difference in type was statistically significant ( Z=2.396, P=0.017). The diagnostic efficacy of the DKI+ DWI model was higher than that of the single parameter ADC, MD, and MK, and the differences were statistically significant ( Z=2.396, 2.219, 2.161, all P<0.05); The AUC of the combined imaging and pathology model was 0.983, and its diagnostic efficacy was higher than that of the conventional MRI feature model, pathology model, DWI model, and DKI model, with statistically significant differences ( Z=5.877, 2.961, 3.240, 2.264, all P<0.05). Conclusions:The results of pathology, conventional MRI, DWI and DKI parameters of pCR and non pCR breast cancer patients are significantly different, and the combined model is better than the single model in predicting the efficacy of NAC.

Objective:To develop and verify a predictive model for hip fracture risk in the aged patients with knee osteoarthritis (KOA) on the basis of analysis of the risk factors associated with the hip fracture.Methods:A retrospective study was conducted to analyze the 701 patients who had been diagnosed with KOA (Kellgren-Lawrence grades 1 to 4) at Dongyang Hospital affiliated to Wenzhou Medical University from September 2013 to September 2023. The cohort consisted of 275 males and 426 females with an age of (76.5±8.4) years. The patients were divided into a fracture group ( n=145) and a fracture-free group ( n=556) based on whether a hip fracture occurred during the follow-up period. The 2 groups were compared in terms of age, gender, comorbidities, albumin level, absolute lymphocyte count, and Kellgren-Lawrence grade, etc. The items with P<0.05 were analyzed by a multivariate logistic regression model to identify the risk factors for hip fracture in the aged KOA patients. A clinical prediction model based on the above risk factors was constructed and validated for hip fracture risk in the aged KOA patients. Results:Multivariate logistic regression analysis identified the following as independent risk factors for hip fracture in the aged KOA patients: female ( OR=2.009, 95% CI: 1.280 to 3.154, P=0.002), age ≥75 years ( OR=2.313, 95% CI: 1.493 to 3.583, P=0.001), Kellgren-Lawrence grades of 3-4 ( OR=2.348, 95% CI: 1.533 to 3.596, P=0.001), an albumin level <35 g/L ( OR=0.316, 95% CI: 0.191 to 0.522, P=0.001), and an absolute lymphocyte count <0.8×10 9/L ( OR=0.133, 95% CI: 0.069 to 0.253, P=0.001). The area under the ROC curve (AUC) for the model developed by this study was 0.753 in the training set and 0.815 in the validation set ( P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed that the consistency between the predicted risk and the actual risk was good in the training and validation sets ( P<0.05). The calibration curves for both the training and validation sets closely aligned with the ideal curve. The clinical decision curve analysis showed that the nomogram model had a good net benefit rate and a good predictive potential. Conclusions:Female, age ≥75 years, Kellgren-Lawrence grades of 3-4, an albumin level <35 g/L, and an absolute lymphocyte count <0.8×10 9/L are independent risk factors for hip fracture in the aged KOA patients. Since the nomogram prediction model based on these risk factors is satisfactory in discrimination and calibration, it shows a certain predictive ability and application value in clinic.

Objective:To develop and verify a predictive model for hip fracture risk in the aged patients with knee osteoarthritis (KOA) on the basis of analysis of the risk factors associated with the hip fracture.Methods:A retrospective study was conducted to analyze the 701 patients who had been diagnosed with KOA (Kellgren-Lawrence grades 1 to 4) at Dongyang Hospital affiliated to Wenzhou Medical University from September 2013 to September 2023. The cohort consisted of 275 males and 426 females with an age of (76.5±8.4) years. The patients were divided into a fracture group ( n=145) and a fracture-free group ( n=556) based on whether a hip fracture occurred during the follow-up period. The 2 groups were compared in terms of age, gender, comorbidities, albumin level, absolute lymphocyte count, and Kellgren-Lawrence grade, etc. The items with P<0.05 were analyzed by a multivariate logistic regression model to identify the risk factors for hip fracture in the aged KOA patients. A clinical prediction model based on the above risk factors was constructed and validated for hip fracture risk in the aged KOA patients. Results:Multivariate logistic regression analysis identified the following as independent risk factors for hip fracture in the aged KOA patients: female ( OR=2.009, 95% CI: 1.280 to 3.154, P=0.002), age ≥75 years ( OR=2.313, 95% CI: 1.493 to 3.583, P=0.001), Kellgren-Lawrence grades of 3-4 ( OR=2.348, 95% CI: 1.533 to 3.596, P=0.001), an albumin level <35 g/L ( OR=0.316, 95% CI: 0.191 to 0.522, P=0.001), and an absolute lymphocyte count <0.8×10 9/L ( OR=0.133, 95% CI: 0.069 to 0.253, P=0.001). The area under the ROC curve (AUC) for the model developed by this study was 0.753 in the training set and 0.815 in the validation set ( P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed that the consistency between the predicted risk and the actual risk was good in the training and validation sets ( P<0.05). The calibration curves for both the training and validation sets closely aligned with the ideal curve. The clinical decision curve analysis showed that the nomogram model had a good net benefit rate and a good predictive potential. Conclusions:Female, age ≥75 years, Kellgren-Lawrence grades of 3-4, an albumin level <35 g/L, and an absolute lymphocyte count <0.8×10 9/L are independent risk factors for hip fracture in the aged KOA patients. Since the nomogram prediction model based on these risk factors is satisfactory in discrimination and calibration, it shows a certain predictive ability and application value in clinic.

Objective To investigate the clinical and pathological features of Uurich congenital muscular dystrophy (UCMD). Methods The clinical aspects of 3 patients with UCMD, 2 with Duchenne muscular dystrophy (DMD) and 1 with congenital muscular dystrophy 1A (MDC1A) were analyzed. And the muscle specimens from these patients were studied using immunohistochemistry and immunofluorescence staining. Results UCMD was clinically characterized by neonatal hypotonia with proximal contracturos and distal hyperlaxity at birth or early infancy. Histochemical staining revealed muscle frber hypoplasia andinterstitium proliferation. Immunohistochemistry staining with anti-collagen Ⅵ antibody revealed complete(1/3) or partial (2/3) deficiency of collagen Ⅵ in the sarcolemma and interstitial matrix. Partial deficiency was better demonstrated by immunofluorescence staining. Conclusions The proximal contractures and distal hyperlaxity is the clinical hallmark of UCMD. Collagen Ⅵ immunolabelling can confirm the diagnosis of UCMD.