Noninvasive Prediction of Sperm Retrieval Using Diffusion Tensor Imaging in Patients with Nonobstructive Azoospermia.

Microdissection testicular sperm extraction (mTESE) is the first-line treatment plan for nonobstructive azoospermia (NOA). However, studies reported that the overall sperm retrieval rate (SRR) was 43% to 63% among men with NOA, implying that nearly half of the patients fail sperm retrieval. This study aimed to evaluate the diagnostic performance of parameters derived from diffusion tensor imaging (DTI) in predicting SRR in patients with NOA.

A glycosylation signature for predicting the progression and immunotherapeutic response of prostate cancer.

Background: Glycosylation has been proposed as a new cancer hallmark. However, focusing on specific glycans or glycoproteins may lose much data relevant to glycosylation alterations. The present study aimed to first comprehensively investigate the expression and mutation profiles of glycosylation-related genes (GRgenes) in prostate cancer (PCa) and then develop a glycosylation signature and explore its role in predicting the progression and immunotherapeutic response of PCa.

Contrasts Between Diffusion-Weighted Imaging and Dynamic Contrast-Enhanced MR in Diagnosing Malignancies of Breast Nonmass Enhancement Lesions Based on Morphologic Assessment.

Background: Nonmass enhancement (NME) breast lesions are considered to be the leading cause of unnecessary biopsies. Diffusion-weighted imaging (DWI) or dynamic contrast-enhanced (DCE) sequences are typically used to differentiate between benign and malignant NMEs. It is important to know which one is more effective and reliable.

Prevention of alloimmune rejection using XBP1-deleted bone marrow-derived dendritic cells in heart transplantation.

Background: Genetically modified dendritic cells (DCs) modulate the alloimmunity of T lymphocytes by regulating antigen presentation.

Methods: We generated mice with specific deletion of the X-box-binding protein 1 (XBP1) allele in bone marrow cells and cultured bone marrow-derived DCs (Xbp1 BMDCs) from these animals. We then tested the phenotype of Xbp1 BMDCs, evaluated their capability to activate allogeneic T cells and investigated their mechanistic actions.

A potential biomarker based on clinical-radiomics nomogram for predicting survival and adjuvant chemotherapy benefit in resected node-negative, early-stage lung adenocarcinoma.

Background: We aimed to construct a clinical-radiomics nomogram to predict disease-free survival (DFS) and the added survival benefit of adjuvant chemotherapy (ACT) for node-negative, early-stage (I-II) lung adenocarcinoma (ADC).

Methods: In this retrospective study including 310 patients from two independent cohorts, the CT-derived radiomics features were selected by least absolute shrinkage and selection operator Cox regression to generate a radiomics signature associated with DFS. The radiomics signature was incorporated to construct a clinical-radiomics nomogram along with the independent clinical risk predictors.

Discriminating malignant from benign testicular masses using machine-learning based radiomics signature of appearance diffusion coefficient maps: Comparing with conventional mean and minimum ADC values.

Purpose: To develop a machine-learning-based radiomics signature of ADC for discriminating between benign and malignant testicular masses and compare its classification performance with that of minimum and mean ADC.

Methods: A total of ninety-seven patients with 101 histopathologically confirmed testicular masses (70 malignancies, 31 benignities) were evaluated in this retrospective study. Eight hundred fifty-one radiomics features were extracted from the preoperative ADC map of each lesion.

Long-term chest CT follow-up in COVID-19 Survivors: 102-361 days after onset.

Background: The aim of this study was to evaluate long-term longitudinal changes in chest computed tomography (CT) findings in coronavirus disease 2019 (COVID-19) survivors and their correlations with dyspnea after discharge.

Methods: A total of 337 COVID-19 survivors who underwent CT scan during hospitalization and between 102 and 361 days after onset were retrospectively included. Subjective CT findings, lesion volume, therapeutic measures and laboratory parameters were collected.

Prediction of Pathological Upgrading at Radical Prostatectomy in Prostate Cancer Eligible for Active Surveillance: A Texture Features and Machine Learning-Based Analysis of Apparent Diffusion Coefficient Maps.

Objective: To evaluate a combination of texture features and machine learning-based analysis of apparent diffusion coefficient (ADC) maps for the prediction of Grade Group (GG) upgrading in Gleason score (GS) ≤6 prostate cancer (PCa) (GG1) and GS 3 + 4 PCa (GG2).

Materials And Methods: Fifty-nine patients who were biopsy-proven to have GG1 or GG2 and underwent MRI examination with the same MRI scanner prior to transrectal ultrasound (TRUS)-guided systemic biopsy were included. All these patients received radical prostatectomy to confirm the final GG.

Value of Intra-Perinodular Textural Transition Features from MRI in Distinguishing Between Benign and Malignant Testicular Lesions.

Purpose: To compare the performance of histogram analysis and intra-perinodular textural transition (Ipris) for distinguishing between benign and malignant testicular lesions.

Patients And Methods: This retrospective study included 76 patients with 80 pathologically confirmed testicular lesions (55 malignant, 25 benign). All patients underwent preoperative T2-weighted imaging (T2WI) on a 3.

Noninvasive Differentiation of Obstructive Azoospermia and Nonobstructive Azoospermia Using Multimodel Diffusion Weighted Imaging.

Rationale And Objectives: To evaluate the diagnostic performance of parameters derived from multimodel diffusion weighted imaging (monoexponential, stretched-exponential diffusion weighted imaging and diffusion kurtosis imaging [DKI]) from noninvasive magnetic resonance imaging in distinguishing obstructive azoospermia (OA) from nonobstructive azoospermia (NOA).

Materials And Methods: Forty-six patients with azoospermia were prospectively enrolled and classified into two groups (21 OA patients and 25 NOA patients). The multimodel parameters of diffusion-weighted imaging (DWI; apparent diffusion coefficient [ADC], distributed diffusion coefficient [DDC], diffusion heterogeneity [α], diffusion kurtosis diffusivity [D], and diffusion kurtosis coefficient [K]) were derived.

Discrimination between benign and malignant testicular lesions using volumetric apparent diffusion coefficient histogram analysis.

Purpose: This study aimed to evaluate the role of volumetric apparent diffusion coefficient (ADC) histogram analysis in discriminating between benign and malignant testicular masses.

Methods: In this retrospective study, fifty-nine patients with 61 pathologically confirmed testicular masses were consecutively enrolled, including 18 benign lesions and 43 malignant lesions. All patients conducted preoperative magnetic resonance imaging (MRI) with diffusion-weighted imaging.

T2-Weighted Image-Based Radiomics Signature for Discriminating Between Seminomas and Nonseminoma.

To evaluate the performance of a T2-weighted image (T2WI)-based radiomics signature for differentiating between seminomas and nonseminomas. In this retrospective study, 39 patients with testicular germ-cell tumors (TGCTs) confirmed by radical orchiectomy were enrolled, including 19 cases of seminomas and 20 cases of nonseminomas. All patients underwent 3T magnetic resonance imaging (MRI) before radical orchiectomy.

Validation of SE-EPI-based T2 mapping for characterization of prostate cancer: a new method compared with the traditional CPMG method.

Purpose: We aim to compare the results of spin echo-echo planar imaging (SE-EPI)-based T2 mapping with those of the conventional Carr-Purcell-Meiboom-Gill (CPMG) method and to investigate the potential validity of SE-EPI-T2 mapping for the characterization of prostate cancer (PCa).

Methods: Our retrospective study included 42 PCa patients and 42 noncancer patients who underwent 3.0T MRI with b values ranging from 0 to 2000 s/mm and echo times (TEs) ranging from 32 to 100 ms before biopsies.