Noninvasive identification of HER2-low-positive status by MRI-based deep learning radiomics predicts the disease-free survival of patients with breast cancer.

OBJECTIVE: This study aimed to establish a MRI-based deep learning radiomics (DLR) signature to predict the human epidermal growth factor receptor 2 (HER2)-low-positive status and further verified the difference in prognosis by the DLR model. METHODS: A total of 481 patients with breast cancer who underwent preoperative MRI were retrospectively recruited from two institutions. Traditional radiomics features and deep semantic segmentation feature-based radiomics (DSFR) features were extracted from segmented tumors to construct models separately. Then, the DLR model was constructed to assess the HER2 status by averaging the output probabilities of the two models. Finally, a Kaplan‒Meier survival analysis was conducted to explore the disease-free survival (DFS) in patients with HER2-low-positive status. The multivariate Cox proportional hazard model was constructed to further determine the factors associated with DFS. RESULTS: First, the DLR model distinguished between HER2-negative and HER2-overexpressing patients with AUCs of 0.868 and 0.763 in the training and validation cohorts, respectively. Furthermore, the DLR model distinguished between HER2-low-positive and HER2-zero patients with AUCs of 0.855 and 0.750, respectively. Cox regression analysis showed that the prediction score obtained using the DLR model (HR, 0.175; p = 0.024) and lesion size (HR, 1.043; p = 0.009) were significant, independent predictors of DFS. CONCLUSIONS: We successfully constructed a DLR model based on MRI to noninvasively evaluate the HER2 status and further revealed prospects for predicting the DFS of patients with HER2-low-positive status. CLINICAL RELEVANCE STATEMENT: The MRI-based DLR model could noninvasively identify HER2-low-positive status, which is considered a novel prognostic predictor and therapeutic target. KEY POINTS: • The DLR model effectively distinguished the HER2 status of breast cancer patients, especially the HER2-low-positive status. • The DLR model was better than the traditional radiomics model or DSFR model in distinguishing HER2 expression. • The prediction score obtained using the model and lesion size were significant independent predictors of DFS.

Renal histology of Fanconi syndrome associated with adefovir dipivoxil: A case report.

A sporadic occurrence of Fanconi syndrome associated with adefovir dipivoxil (ADV) has been reported, particularly when confirmed by renal biopsy. This study presents the case of a 53-year-old man who had been taking ADV 10 mg daily for 10 years to treat chronic hepatitis B (CHB) and subsequently developed Fanconi syndrome. The clinical manifestations included hypophosphatemic osteomalacia, glucosuria, renal tubular acidosis, low-molecular-weight proteinuria, and renal insufficiency. Renal biopsy revealed significant injury to proximal tubular epithelial cells, including vacuolar degeneration and regeneration of tubular epithelial cells. The ultrastructural pathology indicated severe morphological abnormalities of mitochondria, such as densely packed and enlarged mitochondria, with loss, blunting, and disordered arrangement of cristae. Following discontinuation of ADV and supplementation with oral phosphate, hypophosphatemia, glucosuria, and proteinuria were resolved. These findings support the previous hypothesis that ADV-induced nephrotoxicity may involve mitochondrial injury.

Deciphering essential druggable genes reveals potential immune-inflammatory axis in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a malignant tumor with a high mortality rate and poor prognosis in patients. Its pathogenesis is a complex process of multi-factors and multi-steps. However, the etiology and exact molecular mechanism are not completely clear. METHODS: Here, we constructed a specific-expressed network based on RNA sequencing data. Gene and miRNA expression profiles and clinical evidence were integrated to detect hepatocellular carcinoma survival modules. Finally, we attempted to identify potential key biomarkers and drug targets by integrating drug sensitivity analysis and immune infiltration analysis. RESULTS: A total of 42 prognostic modules for hepatocellular carcinoma were detected. The prognostic modules were significantly enriched with known cancer-related molecules and 12.93 % molecules of prognostic modules had been found were the targets of small molecule drug. In addition, we found that 38 of 42 (90.48 %) essential genes were associated with the proportions of at least one of the 7 immune cell types. CONCLUSION: We integrated clinical prognosis information, RNA sequencing data, and drug activity data to explore risk modules of hepatocellular carcinoma. Through drug sensitivity analysis and immune infiltration analysis, we assessed the value of hub genes in the modules as potential biomarkers and drug targets for hepatocellular carcinoma. The protocol provides new insight into parsing the molecular mechanism and theoretical basis of hepatocellular carcinoma.

Vascular, valvular and kidney calcification manifested in mouse models of adenine-induced chronic kidney disease.

BACKGROUND: Ectopic calcification (EC) involves multiple organ systems in chronic kidney disease (CKD). Previous CKD-animal models primarily focused on a certain histological abnormality but did not show the correlation with calcified development among various tissues. This study compared calcified deposition in various tissues during CKD progression in mice. METHODS: Male 8-week-old C57BL/6J mice were randomly allocated to the seven groups: a basic, adenine, high-phosphorus, or adenine and high-phosphorus diet for 12-16 weeks (Ctl16, A12, P16, or AP16, respectively); an adenine diet for 4-6 weeks; and a high-phosphorus or adenine and high-phosphorus diet for 10-12 weeks (A6 + P10, A4 + P12, or A4 + AP12, respectively). RESULTS: Compared to the Ctl16 mice, the P16 mice only displayed a slight abnormality in serum calcium and phosphorus; the A12 mice had the most serious kidney impairment; the A4 + P12 and A6 + P10 mice had similar conditions of CKD, mineral abnormalities, and mild calcification in the kidney and aortic valves; the A4 + AP12 and AP16 groups had severe kidney impairment, mineral abnormalities and calcification in the kidneys, aortic valves and aortas. Furthermore, calcium-phosphate particles were deposited not only in the tubulointerstitial compartment but in the glomerular and tubular basement membrane. The elemental composition of EC in various tissues matched the calcification of human cardiovascular tissue as determined by energy dispersive spectroscopy. CONCLUSIONS: The severity of CKD was unparalleled with the progression of mineral metabolism disorder and EC. Calcification was closely related in different tissues and observed in the glomerular and tubular basement membranes.

Previous CKD-animal models primarily focused on a certain histological abnormality but lacked investigations of the interplay of EC in various tissues. This study compared calcified deposition in several tissues during CKD progression in mice, which was closely related. The severity of CKD was unparalleled with the development of ectopic calcification. Glomerular and tubular basement membrane calcification was detected in CKD mice, which has been considered extremely rare in clinical.

Multiparametric mapping by cardiovascular magnetic resonance imaging in cardiac tumors.

BACKGROUND: There is a paucity of quantitative measurements of cardiac tumors and myocardium using parametric mapping techniques. This study aims to explore quantitative characteristics and diagnostic performance of native T1, T2, and extracellular volume (ECV) values of cardiac tumors and left ventricular (LV) myocardium. METHODS: Patients with suspected cardiac tumors who underwent cardiovascular magnetic resonance (CMR) between November 2013 and March 2021 were prospectively enrolled. The diagnoses of primary benign or malignant tumors were based on pathologic findings if available, comprehensive medical history evaluations, imaging, and long-term follow-up data. Patients with pseudo-tumors, cardiac metastasis, primary cardiac diseases, and prior radiotherapy or chemotherapy were excluded. Multiparametric mapping values were measured on both cardiac tumors and the LV myocardium. Statistical analyses were performed using independent-samples t-test, receiver operating characteristic, and Bland-Altman analyses. RESULTS: A total of 80 patients diagnosed with benign (n = 54), or primary malignant cardiac tumors (n = 26), and 50 age and sex-matched healthy volunteers were included. Intergroup differences in the T1 and T2 values of cardiac tumors were not significant, however, patients with primary malignant cardiac tumors showed significantly higher mean myocardial T1 values (1360 ± 61.4 ms) compared with patients with benign tumors (1259.7 ± 46.2 ms), and normal controls (1206 ± 44.0 ms, all P < 0.05) at 3 T. Patients with primary malignant cardiac tumors also showed significantly higher mean ECV (34.6 ± 5.2%) compared with patients with benign (30.0 ± 2.5%) tumors, and normal controls (27.3 ± 3.0%, all P < 0.05). For the differentiation between primary malignant and benign cardiac tumors, the mean myocardial native T1 value showed the highest efficacy (AUC: 0.919, cutoff value: 1300 ms) compared with mean ECV (AUC: 0.817) and T2 (AUC: 0.619) values. CONCLUSION: Native T1 and T2 of cardiac tumors showed high heterogeneity, while myocardial native T1 values in primary malignant cardiac tumors were elevated compared to patients with benign cardiac tumors, which may serve as a new imaging marker for primary malignant cardiac tumors.

Effects of hypoxia-inducible factor-prolyl hydroxylase inhibitors vs. erythropoiesis-stimulating agents on iron metabolism in non-dialysis-dependent anemic patients with CKD: A network meta-analysis.

Objective: To compare the effects of five hypoxia-inducible factor-prolyl hydroxylase domain inhibitors (HIF-PHIs), two erythropoiesis-stimulating agents (ESAs), and placebo on iron metabolism in renal anemia patients with non-dialysis-dependent chronic kidney disease (NDD-CKD). Method: Five electronic databases were searched for studies. Randomized controlled clinical trials comparing HIF-PHIs, ESAs, and placebo in NDD-CKD patients were selected. The statistical program used for network meta-analysis was Stata/SE 15.1. The main outcomes were the change in hepcidin and hemoglobin (Hb) levels. The merits of intervention measures were predicted by the surface under the cumulative ranking curve method. Results: Of 1,589 original titles screened, data were extracted from 15 trials (3,228 participants). All HIF-PHIs and ESAs showed greater Hb level-raising ability than placebo. Among them, desidustat demonstrated the highest probability of increasing Hb (95.6%). Hepcidin [mean deviation (MD) = -43.42, 95%CI: -47.08 to -39.76], ferritin (MD= -48.56, 95%CI: -55.21 to -41.96), and transferrin saturation (MD = -4.73, 95%CI: -5.52 to -3.94) were decreased, while transferrin (MD = 0.09, 95%CI: 0.01 to 0.18) and total iron-binding capacity (MD = 6.34, 95%CI: 5.71 to 6.96) was increased in HIF-PHIs versus those in ESAs. In addition, this study observed heterogeneity in the ability of HIF-PHIs to decrease hepcidin. Compared with darbepoetin, only daprodustat (MD = -49.09, 95% CI: -98.13 to -0.05) could significantly reduce hepcidin levels. Meanwhile, daprodustat also showed the highest hepcidin-lowering efficacy (84.0%), while placebo was the lowest (8.2%). Conclusion: For NDD-CKD patients, HIF-PHIs could ameliorate functional iron deficiency by promoting iron transport and utilization, which may be achieved by decreasing hepcidin levels. Interestingly, HIF-PHIs had heterogeneous effects on iron metabolism. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=242777, Identifier CRD42021242777.

Prevalence and Clinical Characteristics of Calciphylaxis in Chinese Hemodialysis Patients.

Background: Calciphylaxis is a grievous life-threatening vascular disease that commonly affects dialysis population. This is the first epidemiological survey of calciphylaxis initiated in China. Methods: In the cross-sectional survey, a stratified sampling method was used to select 24 dialysis centers in Jiangsu Province. The participants were all adult patients in each center who had been on hemodialysis for more than 6 months. Calciphylaxis patients were uniformly diagnosed based on characteristic skin lesions and histopathological features. Results: A total of 3,867 hemodialysis patients (average age of 55.33 ± 13.89 years; 61.81% of males) were included. Forty eight cases were diagnosed with calciphylaxis, and prevalence was 1.24%. Among calciphylaxis patients, 33 cases were male, and the average age and median dialysis duration were 53.85 ± 15.17 years and 84.00 (48.00, 138.75) months, respectively. Skin biopsy was performed in 70.83% of calciphylaxis patients, and positive rate was 64.71%. Meanwhile, the positive rate of bone scintigraphy in the diagnosis of calciphylaxis was 62.5%. The prevalence of hyperparathyroidism in case group was as high as 72.92% with longer duration, and 42.86% had undergone parathyroidectomy. Multivariate analysis indicated that increased BMI, prolonged dialysis duration, warfarin therapy, hyperparathyroidism, diabetes, tumors, low serum albumin and high serum alkaline phosphatase levels were high-risk factors for calciphylaxis. Conclusions: The prevalence of calciphylaxis in Chinese hemodialysis patients was 1.24% according to regional epidemiological survey, but its actual prevalence would be presumably far beyond present data. It's urgent to improve clinical understanding of calciphylaxis, and multifaceted diagnostic methods should be applied for early screening.

Deep learning radiomic analysis of DCE-MRI combined with clinical characteristics predicts pathological complete response to neoadjuvant chemotherapy in breast cancer.

Objective: The aim of this study was to develop and validate a deep learning-based radiomic (DLR) model combined with clinical characteristics for predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer. For early prediction of pCR, the DLR model was based on pre-treatment and early treatment dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data. Materials and methods: This retrospective study included 95 women (mean age, 48.1 years; range, 29-77 years) who underwent DCE-MRI before (pre-treatment) and after two or three cycles of NAC (early treatment) from 2018 to 2021. The patients in this study were randomly divided into a training cohort (n=67) and a validation cohort (n=28) at a ratio of 7:3. Deep learning and handcrafted features were extracted from pre- and early treatment DCE-MRI contoured lesions. These features contribute to the construction of radiomic signature RS1 and RS2 representing information from different periods. Mutual information and least absolute shrinkage and selection operator regression were used for feature selection. A combined model was then developed based on the DCE-MRI features and clinical characteristics. The performance of the models was assessed using the area under the receiver operating characteristic curve (AUC) and compared using the DeLong test. Results: The overall pCR rate was 25.3% (24/95). One radiomic feature and three deep learning features in RS1, five radiomic features and 11 deep learning features in RS2, and five clinical characteristics remained in the feature selection. The performance of the DLR model combining pre- and early treatment information (AUC=0.900) was better than that of RS1 (AUC=0.644, P=0.068) and slightly higher that of RS2 (AUC=0.888, P=0.604) in the validation cohort. The combined model including pre- and early treatment information and clinical characteristics showed the best ability with an AUC of 0.925 in the validation cohort. Conclusion: The combined model integrating pre-treatment, early treatment DCE-MRI data, and clinical characteristics showed good performance in predicting pCR to NAC in patients with breast cancer. Early treatment DCE-MRI and clinical characteristics may play an important role in evaluating the outcomes of NAC by predicting pCR.

Radiomics-based method for diagnosis of calciphylaxis in patients with chronic kidney disease using computed tomography.

Calciphylaxis is a rare, life-threatening condition that affects patients with chronic kidney disease (CKD) undergoing dialysis. Skin biopsy as the gold standard causes ulceration, bleeding, or infection. This study aimed to develop radiomic methods using CT as a noninvasive method for calciphylaxis diagnosis. The confirmed calciphylaxis patients (Group I), pathologically confirmed non-calciphylaxis patients (Group II), and CKD patients (Group III) from October 1, 2017, to November 30, 2019, were enrolled. Training: 70% of patients of Group I and all Group III. Test: 30% of patients of Group I and all Group II. ROI was set at the skin lesion including the soft tissue. First-order and texture features were extracted from each lesion unit. CT-based radiomic models were on the basis of logistic regression (LR) and support vector machine (SVM). Additionally, model performance was evaluated in the test dataset and compared with the plain radiography and bone scintigraphy. In total, 124 lesions and 38 lesions were identified in training and test datasets. Radiomic models were effective in detecting calciphylaxis in patients with CKD, with AUCs of 0.93 (95% CI: 0.924-0.953) and 0.93 (95% CI: 0.921-0.953) (SVM and LR) in test. The SVM model manifested a sensitivity and specificity of 0.89 and 0.8, and 0.78 and 0.90, at high-sensitivity and high-specificity operating points, respectively. Similar performance was found in the LR model. Radiomic models were more effective than plain radiography and bone scintigraphy (Delong test, P<0.05). Verification studies showed the features which manifested the real variability of lesions. In this research, it primarily developed a radiomic method for noninvasive detection of calciphylaxis in patients with CKD. Through this method, calciphylaxis can be detected when invasive procedures are not feasible.

Differential and prognostic value of cardiovascular magnetic resonance derived scoring algorithm in cardiac tumors.

OBJECTIVES: To establish a scoring algorithm based on cardiovascular magnetic resonance (CMR) parameters for differentiating between benign and malignant cardiac tumors and for predicting outcome. METHODS: Patients referred for CMR for suspected cardiac tumors were prospectively enrolled. Tumors were categorized as benign or malignant based on pathology, imaging, and clinical information. The CMR protocol included cine, T1-weighted, T2-weighted, first-pass perfusion, and late gadolinium enhancement (LGE) sequences. Variables independently associated with malignancy in the multivariable logistic analysis were used to construct the scoring algorithm, and receiver operating characteristic analyses were used to assess the ability to discriminate malignant from benign tumors. The ability of the score to predict outcome (all-cause mortality) was also assessed by Kaplan-Meier survival analysis. RESULTS: Among the 105 enrolled patients, 74 had benign and 31 had malignant tumors. In multivariable analysis, the independent predictors of malignant tumors were invasiveness (odds ratio, OR = 11.4, 2 points), irregular border (OR = 5.8, 1 point), and heterogenous LGE (OR 10.6, 2 points). The area under curves (AUC) of the scoring algorithm was 0.912 (cut-off score of 5) and showed significantly higher AUCs than individual variables (all P < 0.05) in differentiating benign and malignant tumors. After median follow-up of 18.2 months, mortality was significantly higher in patients with a score of 5 than in patients with score ≤ 4. CONCLUSIONS: The scoring algorithm based on CMR-detected invasiveness, irregularity of border, and heterogenous LGE is an effective method for differentiating malignant from benign cardiac tumors and for predicting outcome.

Calcitriol attenuates renal tubular epithelial cells apoptosis via inhibiting p38MAPK signaling in diabetic nephropathy.

AIMS: To observe the effect of calcitriol on tubular epithelial cells apoptosis in diabetic nephropathy (DN) and to explore the possible mechanism of its renal protection. METHODS: In vivo, DN rats established by streptozocin (STZ) were treated with or without calcitriol by gavage. Rats were killed at 18 weeks after treatment. In vitro, HK-2 cells were cultured in high glucose with or without 1,25-dihydroxyvitamin D3. In some experiments, P38MAPK activator anisomycin was applied to incubate HK-2 cells. Cell apoptosis was detected by TUNEL or Annexin V-FITC/PI staining with flow cytometry. Immunohistochemical staining was used to observe the expression of VDR in kidney. Protein expression of cleaved caspase-3, Bax, Bcl-2, VDR, pp38MAPK and p38MAPK was assessed by western blotting. RESULT: Calcitriol treatment ameliorated the severity of proteinuria and reduced renal tubular epithelial cells apoptosis in DN rats. In addition, calcitriol treatment significantly increased renal VDR expression and reduced the expression of p-p38MAPK in rats. In vitro, 1,25-dihydroxyvitamin D3 decreased the apoptotic rate of HK-2 cells induced by high glucose. In accord with the results from animal study, 1,25-dihydroxyvitamin D3 increased VDR expression, but decreased p-p38MAPK expression in HK-2 cells. Moreover, P38MAPK activator anisomycin blocked the anti-apoptotic effect of 1,25-dihydroxyvitamin D3 on HK-2 cells. CONCLUSIONS: Calcitriol attenuates renal tubular cells apoptosis via VDR activation which inhibits p38MAPK signaling in DN rats.