Combination Of Diffusion-weighted Imaging Research Articles

Assessment of Tubo-Ovarian Abscess Using Diffusion-Weighted Magnetic Resonance Imaging

Aim: To evaluate systematically the magnetic resonance imaging (MRI) features of tubo-ovarian abscess (TOA), the efficacy of diffusion-weighted imaging (DWI) in the assessment of TOA, and the differentiation of TOA from ovarian masses. Material and methods: PubMed/MEDLINE, Web of Science, and ResearchGate were searched with keywords: Tubo-ovarian abscess and Diffusion-weighted magnetic resonance imaging. No restrictions regarding the language or publication year were applied. Inclusion criteria regarded research papers evaluating the role of MRI and DWI in the assessment of TOA, and the differentiation of TOA from ovarian tumours. Studies appearing to meet inclusion criteria were reviewed in full. Results: A total of 14 studies were included. TOA is usually presented as a multilocular, cystic, pelvic mass with a heterogeneously high signal on T2-weighted (T2W) and low signal on T1-weighted (T1W) images with the “penumbra sign” on T1W images. Following contrast administration, septal and thick wall rim enhancement could be visualized. TOA usually demonstrated hyperintensity on DWI and hypointensity on ADC maps with lower ADC values of cystic, and higher ADC values of solid components compared to ovarian malignancy. TOA was smaller in size, and invasion into adjacent organs and tubal dilatation were more frequent in TOA than in ovarian neoplasms. In comparison to other methods, DWI possessed the highest sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in differentiating TOA from adnexal tumours. Conclusions: The addition of DWI with ADC values improves the detection, characterization, and overall diagnostic accuracy of TOA and its distinction from ovarian malignancy. The combination of DWI with MRI in the assessment of TOA is obligatory.

Comparing the Efficacy of a Combination of Diffusion-Weighted Imaging and T2-STIR (Short Tau Inversion Recovery) Imaging With Contrast-Enhanced MRI in the Evaluation of Perianal Fistula.

Perianal fistula is clinically diagnosed and commonly characterized using magnetic resonance imaging (MRI). Diffusion-weighted imaging (DWI) and T2-weighted imaging are emerging techniques that can obviate the need for contrast injection in cases where contrast administration is not feasible or contraindicated. The main objective of our study was to compare the efficacy of the combination of DWI and T2 STIR (short tau inversion recovery) imaging with contrast-enhanced MRI for the diagnosis and characterization of perianal fistula. Sixty-nine patients with clinical perianal fistula with at least one external opening were evaluated with DWI, T2 STIR, and contrast MRI. A comparative cross-sectional study was conducted in the Department of Radiodiagnosis and Imaging, All India Institute of Medical Sciences, Bhopal, India. The chi-square test was done to find the association between categorical variables. The Kappa test was done to estimate the agreement between two different tests in measuring the outcome. The validity of tests was measured using sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. The combination of DWI and T2 STIR is equivalent to contrast-enhanced MRI in the evaluation of primary and complicated perianal fistula. The combination of DWI and T2 STIR is superior to DWI alone in the classification and characterization of perianal fistula. However, DWI is superior to T2 STIR in differentiating perianal inflammation with abscess from perianal inflammation without abscess and can be used as an alternative to post-contrast fat-suppressed T1-WI in the detection of perianal abscesses and disease activity. DWI can be used as an adjunct to T2 STIR, and the combination of DWI and T2 STIR can replace the post-contrast fat-suppressed T1 MRI sequence in the classification and characterization of perianal fistula.

Evaluating Mediastinal Lymph Node Metastasis of Non-Small Cell Lung Cancer Using Mono-exponential, Bi-exponential, and Stretched-exponential Models of Diffusion-weighted Imaging.

To explore and compare the diagnostic values of mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted imaging (DWI) parameters of primary lesions and lymph nodes (LNs) to predict mediastinal LN metastasis in patients with non-small cell lung cancer. Sixty-one patients with non-small cell lung cancer underwent preoperative magnetic resonance imaging, including multiple b -value DWI. The DWI parameters, including apparent diffusion coefficient (ADC) from a mono-exponential model, true diffusion (D) coefficient, pseudo-diffusion (D*) coefficient, and perfusion fraction (f) from a bi-exponential model, distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index (α) from a stretched-exponential model of primary tumors and LNs and the size characteristics of LNs, were measured and compared. Multivariate logistic regression analysis was used to establish models for predicting mediastinal LN metastasis. Receiver operating characteristic analysis was applied to evaluate diagnostic performances. The DWI parameters of primary tumors showed no statistical significance between LN metastasis-positive and LN metastasis-negative groups. Nonmetastatic LNs had significantly higher ADC, D, DDC, and α values compared with metastatic LNs (all P < 0.05). The short-dimension, long-dimension, and short-long dimension ratio of metastatic LNs was significantly larger than those of nonmetastatic ones (all P < 0.05). The D value showed the best diagnostic performance among all DWI-derived single parameters, and the short dimension of LNs performed the same among all the size variables. Furthermore, the combination of DWI parameters (ADC and D) and the short dimension of LNs can significantly improve diagnostic efficiency. The ADC, D, DDC, and α from the mono-exponential, bi-exponential, and stretched-exponential models were demonstrated efficient in differentiating benign from metastatic LNs, and the combination of ADC, D, and short dimension of LNs may have a better diagnostic performance than DWI or size-derived parameters either in combination or individually.

Diagnostic MR imaging features of hypomyelination of early myelinating structures: A case report.

Hypomyelination of early myelinating structures (HEMS) has recently been defined as a new genetic disorder accompanied by clinical and MR imaging characteristics. However, no studies have focused on diffusion-weighted imaging (DWI) findings of HEMS. We would like to propose a "sheep sign," which is formed by DWI hyperintensity in the medial medullary lamina along with alternating high-low-high (HLH) intensity stripes in the posterior limb of the internal capsule. We believe the presence of the "sheep sign" on DWI in combination with alternating HLH intensity stripes may be a valuable tool for diagnosing HEMS.

Magnetic resonance imaging analysis of embryonal rhabdomyosarcoma of the prostate.

Rhabdomyosarcoma (RMS) is a highly malignant tumor that originates from myogenic progenitor cells. To investigate the magnetic resonance imaging (MRI) characteristics of prostate embryonal rhabdomyosarcoma (ERMS). We retrospectively analyzed the clinical and MRI imaging data of 9 cases of prostate ERMS that were confirmed pathologically. The patients were aged between 14∼49 years with a median age of 27 years, and they all underwent MRI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI (DCE-MRI). The MRI scan of the lesions showed an irregular shape, mixed signals, uneven equal/long T1 signal and an equal/long T2 signal, cystic necrosis in 9 cases and hemorrhage in 6 cases; DWI and ADC images showed a mixed high/low signal, and the tumor parenchyma showed ADC low signal, with an average ADC value of 0.666 × 10-3 mm2/s. There were 5 cases of DCE-MRI TIC type II and 4 cases of DCE-MRI TIC type I. The average value of Tpeak was 120 s and the average value of MCER was 172.3%. After the enhancement, the signal of tumor enhancement was uneven, and showed patchy and reticular enhancement, however, the cyst degeneration, necrosis area, and hemorrhage focus were not enhanced. There were 3 cases with multiple pelvic lymph nodes and 1 case with multiple bone metastases. The MRI manifestations of prostate ERMS have certain characteristics, and the combination of DWI and DCE-MRI are helpful in the diagnosis.

Deep Learning Framework with Multi-Head Dilated Encoders for Enhanced Segmentation of Cervical Cancer on Multiparametric Magnetic Resonance Imaging.

T2-weighted magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) are essential components of cervical cancer diagnosis. However, combining these channels for the training of deep learning models is challenging due to image misalignment. Here, we propose a novel multi-head framework that uses dilated convolutions and shared residual connections for the separate encoding of multiparametric MRI images. We employ a residual U-Net model as a baseline, and perform a series of architectural experiments to evaluate the tumor segmentation performance based on multiparametric input channels and different feature encoding configurations. All experiments were performed on a cohort of 207 patients with locally advanced cervical cancer. Our proposed multi-head model using separate dilated encoding for T2W MRI and combined b1000 DWI and apparent diffusion coefficient (ADC) maps achieved the best median Dice similarity coefficient (DSC) score, 0.823 (confidence interval (CI), 0.595-0.797), outperforming the conventional multi-channel model, DSC 0.788 (95% CI, 0.568-0.776), although the difference was not statistically significant (p > 0.05). We investigated channel sensitivity using 3D GRAD-CAM and channel dropout, and highlighted the critical importance of T2W and ADC channels for accurate tumor segmentation. However, our results showed that b1000 DWI had a minor impact on the overall segmentation performance. We demonstrated that the use of separate dilated feature extractors and independent contextual learning improved the model's ability to reduce the boundary effects and distortion of DWI, leading to improved segmentation performance. Our findings could have significant implications for the development of robust and generalizable models that can extend to other multi-modal segmentation applications.

Role of combined clinical-radiomics model based on contrast-enhanced MRI in predicting the malignancy of breast non-mass enhancements without an additional diffusion-weighted imaging sequence.

In our previous study, we developed a combined diagnostic model based on time-intensity curve (TIC) types and radiomics signature on contrast-enhanced magnetic resonance imaging (CE-MRI) for non-mass enhancement (NME). The model had a high diagnostic ability for differentiation without the additional diffusion-weighted imaging (DWI) sequence. In this study, we aimed to compare the diagnostic performance of the combined clinical-radiomics model based on CE-MRI and DWI in discriminating Breast Imaging-Reporting and Data System (BI-RADS) 4 NME breast lesions, ductal carcinoma in situ (DCIS), and invasive carcinoma. This retrospective study enrolled 364 NME lesions (343 patients). Of these, 183 malignant and 84 benign breast lesions classified as BI-RADS 4 NMEs by the initial diagnosis were reclassified based on the combined clinical-radiomics model and DWI, respectively. The nomogram score (NS) values for malignancy risk derived from the combined clinical-radiomics model and the minimal apparent diffusion coefficient (ADC) values from DWI were calculated and compared. The percentage of false positives were estimated in comparison with the original classification. Receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic value of the NS and minimal ADC values in distinguishing benign and malignant lesions, DCIS, and invasive breast carcinoma. An ablation experiment was used to test the value of the additional DWI sequence. The diagnostic value of the NS values [area under curve (AUC) =0.843; 95% CI: 0.789-0.896] for discriminating the 267 NME breast lesions categorized as BI-RADS 4 was significantly higher than the minimal ADC values (AUC =0.662; 95% CI: 0.590-0.735). The NS values showed higher sensitivity, specificity, and accuracy compared with the minimal ADC values (sensitivity: 80.3% vs. 65.6%; specificity: 79.8% vs. 65.5%; accuracy: 80.1% vs. 65.5%). The NS values and minimal ADC values did not achieve high diagnostic accuracy in discriminating between DCIS and invasive cancer. However, the diagnostic performance of the combined NS-ADC model (AUC =0.731; 95% CI: 0.655-0.806) was higher than that of the NS values alone (P=0.008) and comparable to that of the minimal ADC values (P=0.440). The combined clinical-radiomics model based on CE-MRI could improve the diagnostic performance in discriminating the BI-RADS 4 NME lesions without an additional DWI sequence. However, DWI may improve the diagnostic performance in discriminating DCIS from invasive cancer.

Changes in serial multiparametric MRI and FDG-PET/CT functional imaging during radiation therapy can predict treatment response in patients with head and neck cancer

ObjectivesTo test if tumour changes measured using combination of diffusion-weighted imaging (DWI) MRI and FDG-PET/CT performed serially during radiotherapy (RT) in mucosal head and neck carcinoma can predict treatment response.MethodsFifty-five patients from two prospective imaging biomarker studies were analysed. FDG-PET/CT was performed at baseline, during RT (week 3), and post RT (3 months). DWI was performed at baseline, during RT (weeks 2, 3, 5, 6), and post RT (1 and 3 months). The ADCmean from DWI and FDG-PET parameters SUVmax, SUVmean, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were measured. Absolute and relative change (%∆) in DWI and PET parameters were correlated to 1-year local recurrence. Patients were categorised into favourable, mixed, and unfavourable imaging response using optimal cut-off (OC) values of DWI and FDG-PET parameters and correlated to local control.ResultsThe 1-year local, regional, and distant recurrence rates were 18.2% (10/55), 7.3% (4/55), and 12.7% (7/55), respectively. ∆Week 3 ADCmean (AUC 0.825, p = 0.003; OC ∆ > 24.4%) and ∆MTV (AUC 0.833, p = 0.001; OC ∆ > 50.4%) were the best predictors of local recurrence. Week 3 was the optimal time point for assessing DWI imaging response. Using a combination of ∆ADCmean and ∆MTV improved the strength of correlation to local recurrence (p ≤ 0.001). In patients who underwent both week 3 MRI and FDG-PET/CT, significant differences in local recurrence rates were seen between patients with favourable (0%), mixed (17%), and unfavourable (78%) combined imaging response.ConclusionsChanges in mid-treatment DWI and FDG-PET/CT imaging can predict treatment response and could be utilised in the design of future adaptive clinical trials.Clinical relevance statementOur study shows the complementary information provided by two functional imaging modalities for mid-treatment response prediction in patients with head and neck cancer.Key Points•FDG-PET/CT and DWI MRI changes in tumour during radiotherapy in head and neck cancer can predict treatment response.•Combination of FDG-PET/CT and DWI parameters improved correlation to clinical outcome.•Week 3 was the optimal time point for DWI MRI imaging response assessment.

Discrimination Between Glioblastoma and Solitary Brain Metastasis Using Conventional MRI and Diffusion-Weighted Imaging Based on a Deep Learning Algorithm.

This study aims to develop and validate a deep learning (DL) model to differentiate glioblastoma from single brain metastasis (BM) using conventional MRI combined with diffusion-weighted imaging (DWI). Preoperative conventional MRI and DWI of 202 patients with solitary brain tumor (104 glioblastoma and 98 BM) were retrospectively obtained between February 2016 and September 2022. The data were divided into training and validation sets in a 7:3 ratio. An additional 32 patients (19 glioblastoma and 13 BM) from a different hospital were considered testing set. Single-MRI-sequence DL models were developed using the 3D residual network-18 architecture in tumoral (T model) and tumoral + peritumoral regions (T&P model). Furthermore, the combination model based on conventional MRI and DWI was developed. The area under the receiver operating characteristic curve (AUC) was used to assess the classification performance. The attention area of the model was visualized as a heatmap by gradient-weighted class activation mapping technique. For the single-MRI-sequence DL model, the T2WI sequence achieved the highest AUC in the validation set with either T models (0.889) or T&P models (0.934). In the combination models of the T&P model, the model of DWI combined with T2WI and contrast-enhanced T1WI showed increased AUC of 0.949 and 0.930 compared with that of single-MRI sequences in the validation set, respectively. And the highest AUC (0.956) was achieved by combined contrast-enhanced T1WI, T2WI, and DWI. In the heatmap, the central region of the tumoral was hotter and received more attention than other areas and was more important for differentiating glioblastoma from BM. A conventional MRI-based DL model could differentiate glioblastoma from solitary BM, and the combination models improved classification performance.

Differentiating active from Inactive Sacroiliitis in ankylosing spondylitis by combination of DWI and Magnetization Transfer Imaging.

To evaluate lesions of sacroiliac joint (SIJ) by combination of diffusion-weighted imaging (DWI) and magnetization transfer (MT). A retrospective study was used in this study. Forty-nine ankylosing spondylitis (AS) patients admitted to The China Academy of Chinese Medical Sciences Xiyuan Hospital from May 2020 to October 2020 were collected into active and inactive groups. Twenty-two healthy volunteers were recruited. Apparent diffusion coefficient (ADC) values for bone marrow edema (BME), sclerosis area, fat deposit area, and normal-appearing bone marrow (NABM) (both patients and healthy volunteers) and the magnetization transfer (MT) rate of the cartilage (MTRc) were analyzed in the groups. The above five parameters (ADC (NABM), ADC (BME) and ADC (fat deposit) and MTRc) between the active group and the inactive group were compared. The effectiveness of each parameter in diagnosing sacroiliac arthritis of ankylosing spondylitis were analyzed, and the predictive value of the parameters was compared. ADC(BME), ADC(NABM) and MTRc showed statistically significant differences between the active and inactive groups (P <0.05). ADC (BME) and ADC (NABM) could predict the activity of AS sacroiliac arthritis (P <0.01). ADC (NABM) and MTRc were significantly different between healthy volunteers and the active group (P <0.01). The areas under the ROC curve (AUCs) of ADC (BME)_ADC(NABM), ADC(NABM)_MTR, and ADC(BME)_MTRc were 0.885 (cut-off value=0.69), 0.849 (cut-off value=0.56) and 0.864 (cut-off value=0.60), respectively. The predictive ability of the combined index ADC (BME)_MTRc and ADC(NABM)_MTRc was increased. The ability to diagnose and predict AS might be improved by the combination of diffusion-weighted imaging (DWI) and magnetization transfer (MT).

DWI Combined With Hepatobiliary-Phase Enhanced Imaging Can Better Differentiate Cholangiocarcinoma From Atypical Liver Abscesses

ObjectiveTo investigate the value of diffusion-weighted imaging (DWI) combined with the hepatobiliary phase (HBP) Gd-BOPTA enhancement in differentiating intrahepatic mass-forming cholangiocarcinoma (IMCC) from atypical liver abscess.Materials and MethodsA retrospective analysis was performed on 43 patients with IMCCs (IMCC group) and 25 patients with atypical liver abscesses (liver abscess group). The DWI signal, the absolute value of the contrast noise ratio (│CNR│) at the HBP, and visibility were analyzed.ResultsA relatively high DWI signal and a relatively high peripheral signal were presented in 29 patients (67.5%) in the IMCC group, and a relatively high DWI signal was displayed in 15 patients (60.0%) in the atypical abscess group with a relatively high peripheral signal in only one (6.7%) patient and a relatively high central signal in 14 (93.3%, 14/15). A significant (P<0.001) difference existed in the pattern of signal between the two groups of patients. On T2WI, IMCC was mainly manifested by homogeneous signal (53.5%), whereas atypical liver abscesses were mainly manifested by heterogeneous signal and relatively high central signal (32%, and 64%), with a significant difference (P<0.001) in T2WI imaging presentation between the two groups. On the HBP imaging, there was a statistically significant difference in peripheral │CNR│ (P< 0.001) and visibility between two groups. The sensitivity of the HBP imaging was significantly (P=0.002) higher than that of DWI. The sensitivity and accuracy of DWI combined with enhanced HBP imaging were significantly (P=0.002 and P<0.001) higher than those of either HBP imaging or DWI alone.ConclusionIntrahepatic mass-forming cholangiocarcinoma and atypical liver abscesses exhibit different imaging signals, and combination of DWI and hepatobiliary-phase enhanced imaging has higher sensitivity and accuracy than either technique in differentiating intrahepatic mass-forming cholangiocarcinoma from atypical liver abscesses.

Differentiation between High Grade Glioma and Solitary Brain Metastasis Using Combined Diffusion-Weighted Imaging and Diffusion Tensor Imaging

Background: High-grade gliomas (HGGs) and brain metastases (BMs) can display similar imaging characteristics on conventional MRI. In HGGs, the peritumoral edema is infiltrated by the malignant cells, which was not observed in BMs. Our study aims to determine whether the fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values could differentiate HGGs from BMs. Results: Twenty patients with provisional MRI diagnosis of high grade gliomas WHO grade III &amp; IV versus metastatic brain tumors, examination was done on 1.5 tesla scanner, patients were divided into two groups based on pathology results, the fraction anisotropy (FA) was measured in the enhancing tumor parts and immediate peri-tumoral edema. The minimum and mean ADC in the enhancing tumor (ADCmin, ADCmean) and the minimum ADC in the peritumoral region (ADCedema) were measured from ADC maps. Values of FA and ADC measured in the peri-tumoral edema were significantly high in the metastatic than primary high malignant glial tumors, yet no significant differences in the values of FA and ADC measured in the enhancing tumor parts of the two groups. According to ROC curve analysis, a cutoff value of 0.119 for the FA measured in the peri-tumoral edema with sensitivity (100%) and specificity (75%) and a cutoff value of 1.7 x 10-3 for the ADCedema with sensitivity (87.5%) and specificity (75%) generated the best combination of for distinguishing between HGGs and BMs. Conclusion: FA and ADC values were found to distinguish between HGGs and solitary BMs. The peritumoral FA and ADC values are better than the intratumoral FA and ADC values in predicting the tumor type.

Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas

ObjectivesTo explore the efficacy of diffusion weighted imaging (DWI)-derived metrics under different models as surrogate indicators for molecular biomarkers and tumor microenvironment in gliomas.MethodsA retrospective study was performed for 41 patients with gliomas. The standard apparent diffusion coefficient (ADCst) and ADC under ultra-high b values (ADCuh) (b values: 2500 to 5000 s/mm2) were calculated based on monoexponential model. The fraction of fast diffusion (f), pseudo ADC (ADCfast) and true ADC (ADCslow) were calculated by bi-exponential model (b values: 0 to 2000 s/mm2). The apparent diffusional kurtosis (Kapp) was derived from the simplified diffusion kurtosis imaging (DKI) model (b values: 200 to 3000 s/mm2). Potential correlations between DWI parameters and immunohistological indices (i.e. Aquaporin (AQP)1, AQP4, AQP9 and Ki-67) were investigated and DWI parameters were compared between high- and low-grade gliomas, and between tumor center and peritumor. Receiver operator characteristic (ROC) curve and area under the curve (AUC) were calculated to determine the performance of independent or combined DWI parameters in grading gliomas.ResultsThe ADCslow and ADCuh at tumor center showed a stronger correlation with Ki-67 than other DWI metrics. The ADCst, ADCslow and ADCuh at tumor center presented correlations with AQP1 and AQP4 while AQP9 did not correlate with any DWI metric. Kapp showed a correlation with Ki-67 while no significant correlation with AQPs. ADCst (p < 0.001) and ADCslow (p = 0.001) were significantly lower while the ADCuh (p = 0.006) and Kapp (p = 0.005) were significantly higher in the high-grade than in the low-grade gliomas. ADCst, f, ADCfast, ADCslow, ADCuh, Kapp at the tumor center had significant differences with those in peritumor when the gliomas grade became high (p < 0.05). Involving ADCuh and Kapp simultaneously into an independent ADCst model (AUC = 0.833) could further improve the grading performance (ADCst+ADCuh+Kapp: AUC = 0.923).ConclusionDifferent DWI metrics fitted within different b-value ranges (low to ultra-high b values) have different efficacies as a surrogate indicator for molecular expression or microstructural complexity in gliomas. Further studies are needed to better explain the biological meanings of these DWI parameters in gliomas.

The Value of Combination of Dynamic Contrast-Enhanced Magnetic Resonance Imaging and Diffusion-Weighted Imaging in the Evaluation of Breast Masses

Aim of the study: The aim was to characterize benign and malignant breast lesions on the basis of their magnetic resonance imaging (MRI) morphology and dynamic contrast enhancement in combination with the diffusion-weighted imaging (DWI) and their apparent diffusion coefficient (ADC) values at 1.5 T MRI, along with histopathological correlation. Patients and Methods: In this prospective study, 56 patients with suspicious breast mass who underwent 1.5 T MRI and proved by histopathology were included. Morphology was studied depending on the MRI signal intensity and dynamic contrast-enhanced imaging plus kinetic curve of enhancement of breast lesions. DWI and ADC values were calculated at b values of 0, 600, and 850 s/mm. The ADC value and histopathology correlation were analyzed. Results: Out of the 56 lesions, 27 lesions were histologically malignant (48.2%) and 29 were histologically benign (51.8%), with age range between 25 and 75 years, with a mean of 54.1 years, and with a standard deviation of ±12.69 years. The MRI results found a sensitivity (SN) of 85.2%, a specificity (SP) of 72.4%, a positive predictive value (PPV) of 74.2%, a negative predictive value (NPV) of 84%, and an accuracy of 78.6%. The DWI findings were as follows: 100% SN, 82.8% SP, 84.4% PPV, 100% NPV, and 85.3% accuracy. The combined MRI interpretation and DWI and ADC findings were as follows: 100% SN, 92.1% SP, 71.1% PPV, 100% NPV, and 86.4% accuracy. All malignant lesions showed restriction at DWI, while only 17.2% of the benign lesions are restricted at DWI. The mean of ADC value was higher in benign cases as compared to the malignant lesions (0.815 vs. 1.287 × 10−3) with statistically significant difference (P = 0.001). Conclusions: The combination of contrast-enhanced breast MRI with DWI and ADC value increases the diagnostic accuracy and SP in the characterization of benign and malignant breast lesions.

High-Resolution Diffusion-Weighted Imaging for Evaluation of Extramural Tumor Invasion in Primary Rectal Cancer.

The aim of this study was to determine the added value of high-resolution diffusion-weighted imaging (DWI) to T2-weighted imaging (T2WI) for evaluation of extramural tumor invasion (EMTI) in patients with primary rectal cancer. Seventy-eight patients who had undergone 3.0-T magnetic resonance imaging including DWI (b = 0, 1000 s/mm2, 2 mm iso-voxel) and subsequent surgery were included. Two blinded radiologists independently read the T2WI first and then the combined DWI set. They recorded their confidence level using a 5-point scale. The diagnostic accuracy was calculated by receiver operating characteristic curve analysis based on the histopathological results as the reference. The study population consisted of EMTI positive (n = 44) and negative (n = 34). The area under the curve was not significantly increased after adding DWI to T2WI (reader 1, 0.868-0.856, P = 0.5618; reader 2, 0.848-0.865, P = 0.4539). Adding DWI to T2WI showed no additional diagnostic value for the evaluation of EMTI in patients with primary rectal cancer.

Young Woman with Sudden-Onset Neck Pain and Quadriplegia: a Case Report

IntroductionSudden-onset quadriplegia is a neurologic emergency that requires immediate management. Anterior spinal artery syndrome (ASAS) is rare, but can cause sudden-onset quadriplegia. Magnetic resonance imaging (MRI) is an essential imaging modality for diagnosing ASAS.Case PresentationA 31-year-old woman without previous medical history was transferred to our facility for further workup of sudden-onset neck pain with quadriplegia. Diffusion-weighted imaging (DWI) revealed hyperintense signals predominantly in grey matter with a decreased apparent diffusion coefficient (ADC). These findings strongly suggested ASAS with spinal cord infarction. Edaravone, heparin, and aspirin with steroid pulse therapy were immediately initiated. Twelve days in an intensive care unit was required for dyspnea. Symptoms gradually resolved with rehabilitation, but the patient was wheelchair-bound without bladder control and was transferred to a rehabilitation facility on hospital day 48.ConclusionA combination of DWI with ADC mapping of the spine should proceed as soon as possible to ensure appropriate management. Early treatment with edaravone, aspirin, and steroid pulse therapy may prove beneficial for ASAS.

Breast Lesion Characterisation with Diffusion Weighted Imaging Versus Dynamic Contrast Enhanced-MRI: A Prospective Observational Study in a Tertiary Care Hospital

Purpose: Dynamic contrast-enhanced (DCE)-MRI has a promising role in breast cancer detection and lesion characterisation. Diffusion-weighted imaging (DWI) acts as an adjunct in the differentiation between benign and malignant lesions. The purpose of the study was to evaluate the efficacy of DCE-MRI and DWI in differentiating benign and malignant lesions. Methods: In a prospective study conducted between March 2019 and February 2020, 60 patients with breast lesions underwent DWI combined with DCE-MRI of the breast. The time–intensity curves were plotted. Lesions were classified according to the latest American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS; 5th edition). The results were compared with the histopathological diagnosis. The sensitivity and specificity of DWI, DCE-MRI, and combined DWI and DCE-MRI were calculated for detection of benign and malignant breast lesions. Results: Sixty patients underwent breast MRI in which 78 lesions were detected, out of which 28 were benign and 50 were malignant. Quantitative apparent diffusion coefficient measurement revealed 96% sensitivity and 82% specificity, with a positive predictive value of 92% and negative predictive value of 96%, for differentiating benign from malignant lesions. DCE-MRI findings showed 96% sensitivity and 78.5% specificity. The sensitivity of combined DWI and DCE-MRI was 98% and specificity was 86%, which was higher than DWI and DCE-MRI alone. Conclusion: Multiparametric MRI of the breast has very high sensitivity for detecting and characterising breast lesions as benign or malignant lesions. DWI had higher specificity than DCE-MRI, and the combined use of DWI and DCE-MRI had greater efficacy than DWI and DCE-MRI alone.

Improved Detectability of Brain Stem Ischemia by Combining Axial and Coronal Diffusion-Weighted Imaging.

To evaluate the benefit of a coronal diffusion-weighted imaging (DWI) in addition to standard axial DWI for the detection of brain stem infarctions. A retrospective analysis of patients with symptoms consistent with acute and subacute brain stem infarction who received magnetic resonance imaging, including axial and coronal DWI. Diffusion restrictions were identified by 2 independent raters blinded for the final clinical diagnosis in 3 separate reading steps: axial DWI, coronal DWI, and combined axial and coronal DWI. Lesion location and certainty level were both documented for each reading step. In cases of reader disagreement, an additional consensus reading was performed. Two hundred thirty-nine patients were included. Of these, 124 patients (51.9%) were clinically diagnosed with brain stem infarction. Sensitivity, specificity, positive, and negative predictive values were best for combined DWI assessment (90.3%, 99.1%, 99.1%, and 90.5%) compared with axial (85.5%, 94.9%, 94.6%, and 85.8%) and coronal DWI alone (87.9%, 96.5%, 96.5%, and 88.1%). Diffusion restriction on combined DWI was diagnosed in 112/124 patients compared with 106/124 on axial DWI and 109/124 on coronal DWI. Interobserver agreement for the detection of brain stem lesions was the highest in the combined rating step (Cohen κ coefficient=0.94). Coronal DWI sequences might improve the detection rate of brain stem infarction compared with standard axial DWI. The combined coronal and axial DWI provides the best detection rate while minimally increasing scan times.

Application of Magnetic Resonance Diffusion Tensor Imaging in the Clinical Diagnosis of Disc Herniation after Lumbar Spine Injury.

Magnetic resonance diffusion-weighted imaging (DTI) provides a unique perspective on the pathophysiological and microstructural changes during spinal cord injury, with high spatial specificity; meanwhile, NM reflects the conduction and integrity of neuroelectrical signals in spinal cord fiber tracts, with time-specific and dynamic evaluation effects. The fractional anisotropy (FA) value, SEP amplitude, and neurological function score or improvement rate are correlated. The combination of DTI and NM can more reliably quantify the spinal cord function, evaluate the effectiveness of treatment, and determine the patient's prognosis, which can provide reference for clinical decision making and future research for SCI patients. That is, the lower the preoperative FA value and the lower the SEP amplitude, the worse the preoperative and postoperative neurological function, the lower the improvement rate, and the worse the prognosis of patients. Therefore, we believe that spinal cord function can be graded according to JOA scores to find the corresponding FA and SEP amplitude ranges and that, by measuring FA and SEP amplitude in the future, we can reverse the assessment of spinal cord function, expected postoperative improvement, and long-term prognosis. At the same time, FA values can also help determine the nature of the lesion to some extent.

Comparison of Differential Diagnosis of Lung Cancer by Diffuse Weighted Imaging and Sagittal Imaging with Short Inversion Recovery Sequence

The differential diagnosis of advanced lung cancer is difficult in clinical practice. Our study aims to compare the value of diffusion weighted imaging (DWI) with short-term inversion recovery sequence (STIR) for sagittal imaging in the differential diagnosis of lung cancer. 149 patients with non-small cell lung carcinoma (NSCLC) were enrolled and underwent DWI and STIR sagittal imaging. To quantify cancer types, we evaluated the apparent diffusion coefficient (ADC) value on DWI and the contrast ratio (CRs) on sagittal imaging. The ADC values of subclasses in NSCLC were significantly higher than small cell lung carcinoma (SCLC) (p &lt;0.01). The mean CRs were 1.59 for SCLC and 1.30 for NSCLC with a significant difference (p &lt; 0.01). Large cell carcinomas (LCC) and adenocarcinomas have significant differences compared to small cell carcinomas (SCC) without difference between squamous cell carcinomas (p &gt; 0.05); this is also the case for CRs. Squamous cell carcinoma and adenocarcinoma have significant differences compared to SCC without difference in LCC (p &gt; 0.05). Qualitative evaluation of the feasible thresholds DWI and STIR showed that the thresholds were 0.9810−3 mm2/s and 1.37 respectively. The specificity and accuracy was 78.5% is 85.3% for DWI, which was significantly higher than STIR (56.3% and 61.0%). The combination of DWI and STIR sequences was superior to DWI alone with an accuracy rate of 94.3%. DWI is more helpful than STIR in differentiating SCLC and NSCLC, and their combined use can significantly improve diagnosis accuracy.