Preliminary Exploration of the Sequence of Nerve Fiber Bundles Involvement for Idiopathic Normal Pressure Hydrocephalus: A Correlation Analysis Using Diffusion Tensor Imaging

The study preliminarily explored the sequence and difference of involvement in different neuroanatomical structures in idiopathic normal pressure hydrocephalus (INPH). We retrospectively analyzed the differences in diffusion tensor imaging (DTI) parameters in 15 ROIs [including the bilateral centrum semiovale (CS), corpus callosum (CC) (body, genu, and splenium), head of the caudate nucleus (CN), internal capsule (IC) (anterior and posterior limb), thalamus (TH), and the bilateral frontal horn white matter hyperintensity (FHWMH)] between 27 INPH patients and 11 healthy controls and the correlation between DTI indices and clinical symptoms, as evaluated by the INPH grading scale (INPHGS), the Mini-Mental State Examination (MMSE), and the timed up and go test (TUG-t), before and 1 month after shunt surgery. Significant differences were observed in DTI parameters from the CS (pFA1 = 0.004, pADC1 = 0.005) and the genu (pFA2 = 0.022; pADC2 = 0.001) and body (pFA3 = 0.003; pADC3 = 0.002) of the CC between the groups. The DTI parameters from the CS were strongly correlated with the MMSE score both pre-operatively and post-operatively. There was association between apparent diffusion coefficient (ADC) values of anterior and posterior limbs of the IC and MMSE. The DTI parameters of the head of the CN were correlated with motion, and the ADC value was significantly associated with the MMSE score. The FA value from TH correlated with an improvement in urination after shunt surgery. We considered that different neuroanatomical structures are affected differently by disease due to their positions in neural pathways and characteristics, which is further reflected in clinical symptoms and the prognosis of shunt surgery.

Magnetic Resonance Imaging Images under Deep Learning in the Identification of Tuberculosis and Pneumonia

This work aimed to explore the application value of deep learning-based magnetic resonance imaging (MRI) images in the identification of tuberculosis and pneumonia, in order to provide a certain reference basis for clinical identification. In this study, 30 pulmonary tuberculosis patients and 27 pneumonia patients who were hospitalized were selected as the research objects, and they were divided into a pulmonary tuberculosis group and a pneumonia group. MRI examination based on noise reduction algorithms was used to observe and compare the signal-to-noise ratio (SNR) and carrier-to-noise ratio (CNR) of the images. In addition, the apparent diffusion coefficient (ADC) value for the diagnosis efficiency of lung parenchymal lesions was analyzed, and the best b value was selected. The results showed that the MRI image after denoising by the deep convolutional neural network (DCNN) algorithm was clearer, the edges of the lung tissue were regular, the inflammation signal was higher, and the SNR and CNR were better than before, which were 119.79 versus 83.43 and 12.59 versus 7.21, respectively. The accuracy of MRI based on a deep learning algorithm in the diagnosis of pulmonary tuberculosis and pneumonia was significantly improved (96.67% vs. 70%, 100% vs. 62.96%) ( P < 0.05 ). With the increase in b value, the CNR and SNR of MRI images all showed a downward trend ( P < 0.05 ). Therefore, it was found that the shadow of tuberculosis lesions under a specific sequence was higher than that of pneumonia in the process of identifying tuberculosis and pneumonia, which reflected the importance of deep learning MRI images in the differential diagnosis of tuberculosis and pneumonia, thereby providing reference basis for clinical follow-up diagnosis and treatment.

High-Resolution DWI with Simultaneous Multi-Slice Readout-Segmented Echo Planar Imaging for the Evaluation of Malignant and Benign Breast Lesions

To investigate the feasibility and effectiveness of high-resolution readout-segmented echo planar imaging (rs-EPI), diffusion-weighted imaging (DWI) is used simultaneously with multi-slice (SMS) imaging (SMS rs-EPI) for the differentiation of breast malignant and benign lesions in comparison to conventional rs-EPI on a 3T MR scanner. A total of 102 patients with 113 breast lesions underwent bilateral breast MRI using a prototype SMS rs-EPI sequence and a conventional rs-EPI sequence. Subjective image quality was assessed using a 5-point Likert scale (1 = poor, 5 = excellent). Signal-to-noise ratio (SNR), lesion contrast-to-noise ratio (CNR) and apparent diffusion coefficients (ADC) value of the lesion were measured for comparison. Receiver operating characteristic curve analysis was performed to evaluate the diagnosis performance of ADC, and the corresponding area under curve (AUC) was calculated. The image quality scores in anatomic distortion, lesion conspicuity, sharpness of anatomical details and overall image quality of SMS rs-EPI were significantly higher than those of conventional rs-EPI. CNR was enhanced in the high-resolution SMS rs-EPI acquisition (6.48 ± 1.71 vs. 4.23 ± 1.49; p < 0.001). The mean ADC value was comparable in SMS rs-EPI and conventional rs-EPI (benign 1.45 × 10−3 vs. 1.43 × 10−3 mm2/s, p = 0.702; malignant 0.91 × 10−3 vs. 0.89 × 10−3 mm2/s, p = 0.076). The AUC was 0.957 in SMS rs-EPI and 0.983 in conventional rs-EPI. SMS rs-EPI technique allows for higher spatial resolution and slight reduction of scan time in comparison to conventional rs-EPI, which has potential for better differentiation between malignant and benign lesions of the breast.

Percent change in apparent diffusion coefficient and plasma EBV DNA after induction chemotherapy identifies distinct prognostic response phenotypes in advanced nasopharyngeal carcinoma

Background To evaluate the prognostic value of the apparent diffusion coefficient (ADC) derived from diffusion-weighted magnetic resonance imaging (MRI) and monitor the early treatment response to induction chemotherapy (IC) with plasma EBV DNA in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). Results A total of 307 stage III-IVb NPC patients were prospectively enrolled. All patients underwent MRI examinations to calculate ADC and plasma EBV DNA measurements pretreatment and post-IC. The participants’ ADC value of 92.5% (284/307) increased post-IC. A higher percent change in ADC value (ΔADC%high group) post-IC was associated with a higher 5-year OS rate (90.7% vs 74.9%, p < 0.001) than those in the ΔADC%low group. Interestingly, ΔADC% was closely related to the response measured by RECIST 1.1 (p < 0.001) and plasma EBV DNA level (p = 0.037). The AUC significantly increased when post-IC plasma EBV DNA was added to ΔADC% to predict treatment failure. Thus, based on ΔADC% and plasma EBV DNA, we further divided the participants into three new prognostic response phenotypes (early response, intermediate response, and no response) that correlated with disparate risks of death (p = 0.001), disease progression (p < 0.001), distant metastasis (p < 0.001), and locoregional relapse (p < 0.001). Conclusion The percentage change in ADC post-IC is indicative of treatment response and clinical outcome. ΔADC% and plasma EBV DNA-based response phenotypes may provide potential utility for early termination of treatment and allow guiding risk-adapted therapeutic strategies for LA-NPC.

Feasibility of diffusion-weighted magnetic resonance imaging in evaluation of early therapeutic response after CT-guided microwave ablation of inoperable lung neoplasms

Objective To determine the early treatment response after microwave ablation (MWA) of inoperable lung neoplasms using the apparent diffusion coefficient (ADC) value calculated 24 h after the ablation. Materials and methods This retrospective study included 47 patients with 68 lung lesions, who underwent percutaneous MWA from January 2008 to December 2017. Evaluation of the lesions was done using MRI including DWI sequence with ADC value calculation pre-ablation and 24 h post-ablation. DWI-MR was performed with b values (50, 400, 800 mm2/s). The post-ablation follow-up was performed using chest CT and/or MRI within 24 h following the procedure; after 3, 6, 9, and 12 months; and every 6 months onwards to determine the local tumor response. The post-ablation ADC value changes were compared to the end response of the lesions. Results Forty-seven patients (mean age: 63.8 ± 14.2 years, 25 women) with 68 lesions having a mean tumor size of 1.5 ± 0.9 cm (range: 0.7–5 cm) were evaluated. Sixty-one lesions (89.7%) showed a complete treatment response, and the remaining 7 lesions (10.3%) showed a local progression (residual activity). There was a statistically significant difference regarding the ADC value measured 24 h after the ablation between the responding (1.7 ± 0.3 × 10−3 mm2/s) and non-responding groups (1.4 ± 0.3 × 10−3 mm2/s) with significantly higher values in the responding group (p = 0.001). A suggested ADC cut-off value of 1.42 could be used as a reference point for the post-ablation response prediction (sensitivity: 66.67%, specificity: 84.21%, PPV: 66.7%, and NPV: 84.2%). No significant difference was reported regarding the ADC value performed before the ablation as a factor for the prognosis of treatment response (p = 0.86). Conclusion ADC value assessment following ablation may allow the early prediction of treatment efficacy after MWA of inoperable lung neoplasms. Key Points • ADC value calculated 24 h post-treatment may allow the early prediction of MWA efficacy as a treatment of pulmonary tumors and can be used in the early immediate post-ablation imaging follow-up. • The pre-treatment ADC value of lung neoplasms is not different between the responding and non-responding tumors.

Predicting axillary response to neoadjuvant chemotherapy: the role of diffusion weighted imaging

Objective: The aim of this study is to investigate whether the primary tumour response to neoadjuvant chemotherapy (NAC), based on the increase in the ADC-values (apparent diffusion coefficient) within the breast lesion, could help to predict axillary complete response. Methods: We retrospectively included 74 patients who were treated with NAC followed by surgery at Lucus Augusti Hospital between January 2015 and September 2020. Simple logistic regression was used to evaluate the factors associated with axillary pathological complete response, including the changes in breast tumour ADC-values due to the treatment. Results: Axillary complete response was correlated with negative oestrogen receptor status, Her2 positivity and response of primary tumour. It was achieved in 31% of the patients. In addition, the increase in the tumour ADC-values with NAC was higher for responders. Among the tumours that demonstrated an increase in ADC-value >0.92 ×10−3 mm2/s, 42.8% (15/35) showed axillary complete response. Eight (20.5%) breast cancers with an increase in ADC below the cut-off value were found to have no metastatic nodes after treatment (p = 0.038). Conclusion: Our results suggest that the performance of models predicting axillary response to NAC can be improved by adding the tumour response determined also using diffusion-weighted imaging. Advances in knowledge: For the fist time, we investigate the relation between tumour response to NAC, assessed using diffusion-weighted imaging, and axillary pathologic complete response.

Role of DWI in evaluation of HCC after radiofrequency ablation compared to dynamic MRI using MRI (3 T)

Background The purpose of this study was to investigate the diagnostic performance of diffusion weight imaging (DWI), apparent diffusion coefficient (ADC) map, normalized ADC liver, and normalized ADC spleen compared to the dynamic contrast-enhanced MRI (DCE-MRI) in the evaluation of residual hepatocellular carcinoma (HCC) after radiofrequency ablation (RFA) using 3 T (T) magnetic resonance imaging (MRI). Results A prospective study was performed on 40 patients with radiofrequency-ablated HCC, and 15 (37.5%) patients had viable lesion post-RFA, while 25 (62.5%) had non-viable lesions. DCE-MRI had a sensitivity, specificity, and accuracy of 100%, 100%, and 100%, respectively, compared to DWI which had a sensitivity, specificity, and accuracy of 80%, 88%, and 85%, respectively, for identifying post-RFA viable HCC. The sensitivity, specificity, and accuracy of ADC at a cutoff value of 1.01 × 10−3 mm2/s were 80%, 100%, and 97.1%, respectively. The optimal cutoff value of normalized ADC liver was 0.81 with a sensitivity of 73.3%, specificity of 96%, and accuracy of 92.8%. The sensitivity, specificity, and accuracy of normalized ADC spleen at a cutoff value of 1.22 were 80%, 92%, and 91.1%, respectively. Conclusions DWI-MRI is a reliable technique for assessing HCC after radiofrequency ablation. DWI-MRI with ADC may be used as an alternate sequence for assessing radiofrequency-ablated lesions in individuals who have a contraindication to the contrast media, and the normalized ADC value may be of additional benefit.

Apparent diffusion coefficient can predict therapy response of hepatocellular carcinoma to transcatheter arterial chemoembolization

Aim: The goal of this meta-analysis was to assess the apparent diffusion coefficient (ADC) as a pre- and posttreatment (ΔADC) predictive imaging biomarker of response to transcatheter arterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC). Methods: SCOPUS database, EMBASE database and MEDLINE library were scanned for connections between pre- and posttreatment ADC values of HCC and response to TACE. Six studies qualified for inclusion. The following parameters were collected: authors, publication year, study design, number of patients, drugs for TACE, mean ADC value, standard deviation, measure method, b-values and Tesla-strength. The QUADAS-2 instrument was employed to check the methodological quality of each study. The meta-analysis was performed by utilizing RevMan 5.3 software. DerSimonian and Laird random-effects models with inverse-variance were used to regard heterogeneity. Mean ADC values and 95% confidence intervals were computed. Results: Six studies (n=271 patients with 293 HCC nodules) were included. The pretreatment mean ADC in the responder group was 1.20 x 10-3 mm2/s (0.98, 1.42) and 1.14 x 10-3 mm2/s (0.89, 1.39) in the non-responder group. The analysis of post TACE ADC value changes (ΔADC) revealed a threshold of ≥ 20% to identify treatment responders. No suitable pretreatment ADC threshold to predict therapy response or discriminate between responders and non-responders before therapy could be discovered. Conclusion: ΔADC can facilitate early objective response evaluation through post-therapeutic ADC alterations ≥ 20%. Pretreatment ADC cannot predict response to TACE.

MRI grading for the prediction of prostate cancer aggressiveness

Objectives T o evaluate the value of multiparametric MRI (mpMRI) for the prediction of prostate cancer (PCA) aggressiveness. Methods In this single center cohort study, consecutive patients with histologically confirmed PCA were retrospectively enrolled. Four different ISUP grade groups (1, 2, 3, 4–5) were defined and fifty patients per group were included. Several clinical (age, PSA, PSAD, percentage of PCA infiltration) and mpMRI parameters (ADC value, signal increase on high b-value images, diameter, extraprostatic extension [EPE], cross-zonal growth) were evaluated and correlated within the four groups. Based on combined descriptors, MRI grading groups (mG1–mG3) were defined to predict PCA aggressiveness. Results In total, 200 patients (mean age 68 years, median PSA value 8.1 ng/ml) were analyzed. Between the four groups, statistically significant differences could be shown for age, PSA, PSAD, and for MRI parameters cross-zonal growth, high b-value signal increase, EPE, and ADC (p < 0.01). All examined parameters revealed a significant correlation with the histopathologic biopsy ISUP grade groups (p < 0.01), except PCA diameter (p = 0.09). A mixed linear model demonstrated the strongest prediction of the respective ISUP grade group for the MRI grading system (p < 0.01) compared to single parameters. Conclusions MpMRI yields relevant pre-biopsy information about PCA aggressiveness. A combination of quantitative and qualitative parameters (MRI grading groups) provided the best prediction of the biopsy ISUP grade group and may improve clinical pathway and treatment planning, adding useful information beyond PI-RADS assessment category. Due to the high prevalence of higher grade PCA in patients within mG3, an early re-biopsy seems indicated in cases of negative or post-biopsy low-grade PCA. Key Points • MpMRI yields relevant pre-biopsy information about prostate cancer aggressiveness. • MRI grading in addition to PI-RADS classification seems to be helpful for a size independent early prediction of clinically significant PCA. • MRI grading groups may help urologists in clinical pathway and treatment planning, especially when to consider an early re-biopsy.

Role of diffusion-weighted MRI in evaluation of pediatric musculoskeletal soft tissue masses

Background In pediatric patients, soft tissue masses encompass a wide heterogeneous group of benign and malignant lesions. MRI is a powerful diagnostic tool in the workup of soft tissue tumors in children, and it helps in characterization of lesion and evaluation of the extent of the lesion. However, conventional MRI techniques are not specific in differentiating benign from malignant lesions. So to improve characterization of tumors, DWI was added to MRI techniques as it increases sensitivity and specificity by detecting the micro-diffusion changes of water into intra- and extracellular spaces. The aim of this work was to highlight the diagnostic value of DWI in detection and characterization of different musculoskeletal soft tissue masses in pediatrics. Results There was a statistically significant difference regarding the mean ADC value of benign and malignant masses (P value = 0.001*). The mean ADC value for all benign masses (n = 41) was 1.495 ± 0.55 SD × 10–3 mm2/s, while the mean ADC value for all malignant masses (n = 21) was 0.449 ± 0.27 SD × 10–3 mm2/s. The cutoff ADC value between benign and malignant masses was 0.88 × 10–3 mm2/s. This cutoff ADC value has sensitivity of 100.0%, specificity of 92.3%, PPV of 66.7%, NPV of 100.0% and diagnostic accuracy of 93.3%. Conclusion In pediatric patients, DWI is an innovative valuable noninvasive imaging technique for characterization of musculoskeletal soft tissue masses and discrimination between benign and malignant masses.