In this study, the diagnostic performance of histogram features of APT, DTI and DSC in predicting IDH mutation and MGMT promoter methylation status of gliomas was compared. Secondly, the histogram parameters from the signal-time intensity curve of DSC significantly improved the predictive performance of DSC model. Most importantly, the combined logistic regression model combined with APT, DTI and DSC can evaluate the tumor nature of glioma more comprehensively and obtain better diagnostic performance, which is expected to become an imaging molecular marker for the prediction of glioma genotyping in the future.
Abstract Background: “Wait-and-see”, has been proposed as a possible method of treatment in patients with locally advanced rectal cancer (LARC) after chemoradiotherapy (CRT), MR is important to predict the pathological tumor regression grade(TRG) to preoperative CRT. This study aims to evaluate the diagnostic value of signal intensity (SI) and volume (V) change rate in magnetic resonance imaging (MR) and determine which ones perform best as a potential biomarker for predicting pathological TRG to preoperative CRT in patients with LARC. Methods: A retrospective analysis of 82 patients with LARC, for whom clinical and imaging data were retrieved from our institute was conducted between Oct 2017and Oct 2019. Patients underwent pre- and post-CRT T2-weighted (T2W), diffusion-weighted (DW)/apparent diffusion coefficient (ADC) and contrast-enhanced T1-weighted (ceT1W). V, difference of volume between pre-CRT and post-CRT tumor (△V), V of tumor reduction rate (%△V), as well as SI of tumor (SIt), SI of muscle (SIm), relative SI ratio of tumor/muscle (SIR), changed difference SIR between pre- and post-CRT SIR (△SIR), SIR of tumor changed rate (%△SIR) on T2W, ADC and ceT1W were measured. All of LARC after CRT were confirmed pathologically and classifed into histologic TRG: TRG 0 (complete response), TRG 1 (moderate response), TRG 2 (minimal response), TRG 3 (poor response). Descriptive statistics and areas under the receiver operating characteristic curves (ROC) were generated to compare performance of %△V and %△SIR on T2W, DW, ceT1W for distinguishing between different pathological TRG. Result: Of the 82 patients, TRG 0 (16), TRG 1 (15), TRG 2 (35), TRG 3 (16).Except for ADC-%△SIR, the remaining %△V and %△SIR on T1W, ADC/DWI, ceT1W showed statistics significance between four groups. There was not distinguishable between TRG 1 and TRG 2, TRG 2 and TRG 3 by %△V and/ or %△SIR, the remaining different TRG all were identified by %△V and/ or %△SIR on T2W, ADC/DWI, ceT1W. Compared with other individual %△V or %△SIR, the combination of DW-%△V and T2W-%△SIR (DW-%△V * T2W-%△SIR) yielded higher AUCs to predict TRG 0 from TRG 2 (AUCs: 0.954, sensitivity: 93.75%, specificity: 97.14%) and TRG 3 (AUCs: 1.000, sensitivity: 100%, specificity: 100%), although AUC of all had not significant differences between TRG groups. there was statistically significant differences in post-CRT T restage and ypT stage between fours groups, respectively, but the agreement between post-CRT T restage and ypT is low ( kappa=0.191). Conclusions: V and/or SIR change rate on T2W, DW, ceT1W with high diagnostic performance could be useful in differentiating complete response from non-complete response; SIR change rate could be useful for distinguishing between moderate response and poor response.
To discuss the feasibility of low-dose whole-pancreas imaging utilizing 640-slice dynamic volume CT.80 patients (40 cases of normal pancreas and 40 patients supposed of having pancreatic carcinoma or focal pancreatic space-occupying lesions were mainly refered) referred for CT pancreas perfusion were enrolled in the study. 80 patients randomly assigned to 3 groups: Group ① (whole sequence). Group ② (odd number sequence). Group ③ (even number group)(Compared to ①, the scanning times and effective radiate dose of ② and ③ decreased about 50% respectively). The head, body, tail of each normal pancreas without any pancreatic disease, lesion and lesion-surrounding areas of each pancreatic cancer were selected as ROI, and tissue peak, blood flow are measured.According to pathology and clinical materials, 27 patients were diagnosed as pancreatic cancer; 40 patients were diagnosed as normal pancreas. The tissue peak and blood flow of the head, body, tail of normal pancreas without any pancreatic disease are 109.63 ± 16.60 and 131.90 ± 41.61, 104.38 ± 19.39 and 127.78 ± 42.52, 104.55 ± 15. 44 and 123.50 ± 33.44 respectively. The tissue peak and blood flow of pancreatic cancer is 59.59 ± 18.20 and 60.00 ± 15.36. For and between each group, there is no significant statistical difference for the tissue peak and blood flow of normal areas of the head, body, tail of normal pancreas. There is statistical difference for the tissue peak and blood flow of lesion and lesion-surrounding areas of pancreatic cancer in each group. However, there is no statistical difference for the tissue peak and blood flow of normal and diseasing areas between 3 groups.Low-dose whole-pancreas perfusion with 640-slice dynamic volume CT is feasible.
This study aimed to evaluate the diagnostic performances of dual-layer CT (DLCT) for the identification of positive lymph nodes (LNs) in patients with lymphoma and retrospectively included 1165 LNs obtained by biopsy from 78 patients with histologically proven lymphoma, who underwent both pretreatment DLCT and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). According to 18F-FDG PET/CT findings as a reference standard, cases were categorized into the LN-negative and LN-positive groups. LNs were then randomly divided at a ratio of 7:3 into the training (n = 809) and validation (n = 356) cohorts. The patients' clinical characteristics and quantitative parameters including spectral curve slope (λHU), iodine concentration (IC) on arterial phase (AP) and venous phase (VP) images were compared between the LN-negative and LN-positive groups using Chi-square test, t-test or Mann-Whitney U test for categorical variables or quantitative parameters. Multivariate logistic regression analysis with tenfold cross-validation was performed to establish the most efficient predictive model in the training cohort. The area under the curve (AUC) was used to evaluate the diagnostic value of the predictive model, and differences in AUC were determined by the DeLong test. Moreover, the predictive model was validated in the validation cohort. Repeatability analysis was performed for LNs using intraclass correlation coefficients (ICCs). In the training cohort, long diameter (LD) had the highest AUC as an independent factors compared to other parameter in differentiating LN positivity from LN negativity (p = 0.006 to p < 0.001), and the AUC of predictive model jointly involving LD and λHU-AP was significantly elevated (AUC of 0.816, p < 0.001). While the AUC of predictive model in the validation cohort was 0.786. Good to excellent repeatability was observed for all parameters (ICC > 0.75). The combination of DLCT with morphological and functional parameters may represent a potential imaging biomarker for detecting LN positivity in lymphoma.
Leaf stripe disease, a seed-borne fungal disease caused by Pyrenophora graminea, poses a significant threat to hulless barley (Hordeum vulgare var. nudum) production on the Qinghai-Tibet Plateau. This study aimed to identify genetic factors conferring resistance to leaf stripe by analyzing an F3 population derived from a cross between the resistant landrace Teliteqingke and the susceptible landrace Dulihuang. Genetic analysis revealed that resistance in Teliteqingke was governed by two dominant genes. Using bulked segregant analysis combined with SNP array (BSA-SNP) and RNA-seq, we identified two candidate regions on chromosomes 3H and 7H. Further analysis focused on chromosome 3H, which revealed a candidate genomic region containing seven potential disease-resistance genes. Among these, RT-qPCR experiments demonstrated that HORVU.MOREX.r3.3HG0232110.1 (encoding a RING/U-box superfamily protein) and HORVU.MOREX.r3.3HG0232410.1 (encoding a bZIP transcription factor) showed significant expression induction following inoculation with P. graminea. These genes can be candidate genes involved in resistance mechanism against leaf stripe in Teliteqingke. These results provide a foundation for functional validation of these genes and offer valuable insights for breeding disease-resistant hulless barley.
Radiation exposure in the CT diagnostic imaging process is a conspicuous concern in pediatric patients. This study aimed to evaluate whether 60-keV virtual monoenergetic images of the pediatric cranium in dual-layer CT can reduce the radiation dose while maintaining image quality compared with conventional images.
MATERIALS AND METHODS:
One hundred six unenhanced pediatric head scans acquired by dual-layer CT were retrospectively assessed. The patients were assigned to 2 groups of 53 and scanned with 250 and 180 mAs, respectively. Dose-length product values were retrieved, and noise, SNR, and contrast-to-noise ratio were calculated for each case. Two radiologists blinded to the reconstruction technique used evaluated image quality on a 5-point Likert scale. Statistical assessment was performed with ANOVA and the Wilcoxon test, adjusted for multiple comparisons.
RESULTS:
Mean dose-length product values were 717.47 (SD, 41.52) mGy×cm and 520.74 (SD, 42) mGy×cm for the 250- and 180-mAs groups, respectively. Irrespective of the radiation dose, noise was significantly lower, SNR and contrast-to-noise ratio were significantly higher, and subjective analysis revealed significant superiority of 60-keV virtual monoenergetic images compared with conventional images (all P < .001). SNR, contrast-to-noise ratio, and subjective evaluation in 60-keV virtual monoenergetic images were not significantly different between the 2 scan groups (P > .05). Radiation dose parameters were significantly lower in the 180-mAs group compared with the 250-mAs group (P < .001).
CONCLUSIONS:
Dual-layer CT 60-keV virtual monoenergetic images allowed a radiation dose reduction of 28% without image-quality loss in pediatric cranial CT.
This study aims to emphasise the importance of imaging in the diagnosis and treatment decision-making in Zinner syndrome and provide a classification for seminal vesicle cysts. The data of six patients with Zinner syndrome in a single institution were collected. All patients underwent a contrast-enhanced computed tomography (CT) exam. Among these patients, five patients also underwent an magnetic resonance imaging (MRI). These results were combined with the review of available literature to classify the seminal vesicle cysts. Among these patients, two patients had urinary urgency and frequency, while four patients had no urinary symptoms. No reproductive-system symptoms were revealed. The imaging revealed left-sided involvement in two patients and right-sided involvement in four patients. The associated features included ipsilateral renal agenesis, seminal vesicle cyst or agenesis, and ejaculatory duct obstruction. Either an ipsilateral ureterocele or an ipsilateral small testis was noted. The seminal vesicle cysts demonstrated varying attenuation or intensity in the imaging. Imaging (CT and especially MRI) can be critical in the noninvasive diagnosis of Zinner syndrome and in allowing aberrant anatomy to be displayed for possible surgery. The proposed seminal vesicle cyst imaging classification could potentially contribute to clinical decision-making.
Abstract Background: Tumor regression grade (TRG) correlates with prognosis in patients with locally advanced rectal cancer (LARC), but there is controversy regarding the use of magnetic resonance imaging (MRI) for determining TRG. This study to evaluate the diagnostic value of change rate in signal intensity (SI) and volume (V) from MRI to TRG following preoperative chemoradiotherapy (CRT) in patiens with LARC. Materials and methods: This retrospective analysis examined 82 LARC patients who were admitted to our institution between Oct 2017 and Oct 2019. Patients underwent pre- and post-CRT T2-weighted (T2W), diffusion-weighted (DW)/apparent diffusion coefficient (ADC), and contrast-enhanced T1-weighted (ceT1W) MRI. Change rate of volume and relative SI ratio(%△V and %△SIR) from each sequence were determined. All LARCs were confirmed pathologically and classified into TRG 0, 1, 2 and 3. Descriptive statistics and receiver operating characteristic (ROC) analysis, with calculation of area under the curve (AUC), were used to compare the diagnostic performances. Results: Sixteen patients had TRG-0, 15 had TRG-1, 35 had TRG-2, and 16 had TRG-3. Except for ADC-%△SIR, the remaining%△V and %△SIR on T1W, DWI, and ceT1W had significant differences among the four groups. %△V and/or %△SIR did not distinguish TRG-1 from TRG-2 nor TRG-2 from TRG-3, but differences between other TRGs were identified by %△V and/or %△SIR on T2W, DWI, and ceT1W. The combined use of DW-%△V and T2W-%△SIR provided the best diagnostic performance in distinguishing of TRG-0 from TRG-2 (AUC: 0.954) and from TRG-3 (AUC: 1.000). Conclusions: Preoperative MRI of LARC patients can determine TRG and may improve selection of the preoperative therapy.
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