Diffusion-weighted Imaging Sequences Research Articles

The significance of PI-RADS v2.1 score combined with quantitative parameters of DWI and DCE-MRI in differentiating between benign prostatic hyperplasia and prostate cancer

This study investigates the efficacy of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) score combined with quantitative metrics from Diffusion Weighted Imaging (DWI) and Dynamic Contrast Enhancement Magnetic Resonance Imaging (DCE-MRI) in differentiating between benign prostatic hyperplasia (BPH) and prostate cancer (PCa). The data of 65 patients with prostate diseases were retrospectively analyzed, and they were divided into a BPH group (n = 34) and a PCa group (n = 31). All patients underwent a multiparametric MRI (mpMRI) examination, which included conventional MRI, DWI and DCE-MRI scans. Variables analyzed included the PI-RADS v2.1 score, apparent diffusion coefficient (ADC), volume transfer constant (Ktrans), rate constant (Kep) and extravascular space volume ratio (Ve). The diagnostic performance of the PI-RADS v2.1 score, DWI, DCE-MRI and their combined metrics in differentiating BPH from PCa was assessed using Receiver Operating Characteristic (ROC) curve analysis. The results demonstrated that the PI-RADS v2.1 scores, Ktrans and Kep values of the PCa group were significantly higher than those of the BPH group (p < 0.001), while the ADC value of the PCa group was significantly lower than the BPH group (p < 0.001). No significant difference was observed in the Ve value between the two groups (p = 0.596). ROC analysis indicated that the area under the curve (AUC) values for the PI-RADS v2.1 score, ADC, Ktrans, Kep, Ve and their combination parameters were 0.824, 0.916, 0.903, 0.904, 0.625 and 0.990, respectively, with the combined parameters showing higher sensitivity and specificity than any single parameter. These findings suggest that the PI-RADS v2.1 score, along with DWI and DCE-MRI sequences, are valuable tools for differentiating BPH from PCa. The quantitative parameters, including ADC, Ktrans and Kep values, offer significant imaging references for clinical assessment, and the combination parameters can significantly enhance diagnostic accuracy.

Role of Diffusion-weighted Magnetic Resonance Imaging in Differentiating Cholesteatoma from Chronic Suppurative Otitis Media: A Cross-sectional Study

Introduction: Radiological imaging, such as High-resolution Computed Tomography (HRCT) of the temporal bone, has always held significant importance in diagnosing and staging Chronic Suppurative Otitis Media (CSOM). In preoperative cases of CSOM and cholesteatoma, HRCT describes the disease’s extent to aid in surgical approach, while diffusion-weighted Magnetic Resonance Imaging (MRI) sequences can differentiate cholesteatoma from other common inflammatory middle ear diseases. Aim: To determine the role of Diffusion-weighted Magnetic Resonance Imaging (DW-MRI) in differentiating between granulation tissue and cholesteatoma using histopathological findings as a reference standard. Materials and Methods: A hospital-based cross-sectional study was conducted in the Department of Radiodiagnosis, Sri Manakula Vinayagar Medical College, Puducherry, India, from November 2018 to April 2020. A total of 40 patients who underwent HRCT of the temporal bone for preoperative evaluation of CSOM underwent diffusion sequence MRI, and their findings were compared with intraoperative and postoperative histopathological results. Findings such as soft-tissue masses with scutum and erosion of ear ossicles were analysed in HRCT, while diffusion restriction was observed in DW-MRI in cases of cholesteatoma. Data were collected using a prescribed proforma and analysed using Statistical Package for Social Sciences (SPSS) software version 24.0. Results: The mean±Standard Deviation (SD) age of the patients was 43±20.41 years (27 males, 13 females). The most common presentations in this study were mucopurulent discharge and conductive hearing loss (20 out of 40 patients). Among the 16 patients diagnosed with cholesteatoma through histopathological examination, all (100%) were reported to have diffusion restriction present in the MRI. The sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) of DWI were all found to be 100% in diagnosing cholesteatoma. The sensitivity of HRCT was 81.25% and the specificity was 83.3%. Conclusion: High-resolution computed tomography provides a surgical roadmap indicating the extent of involvement and bony structures, while DW-MRI imaging helps in differentiating cholesteatoma from CSOM. A combined preoperative approach using HRCT and DW-MRI imaging can aid in diagnosing cholesteatoma effectively.

Possible clinical and radiological predictors of haemorrhagic transformation in acute stroke patients undergoing dual antiplatelet therapy: a clinical study.

The predictors of intracranial haemorrhagic transformation (HT) in acute ischaemic stroke (AIS) patients undergoing dual antiplatelet therapy (DAPT) are not well known. The aim of this study is to identify the possible clinical and radiological predictors of HT in patients, irrespective of clinical indication for this treatment. This study is a monocentric cohort retrospective study. We enrolled consecutive AIS patients, from our prospective register, admitted to Stroke Unit between June 2021 and June 2023 undergoing DAPT with Acetylsalicylic Acid and Clopidogrel within 72 h from symptoms onset. According to current guidelines, DAPT indication was for patients with a minor stroke, symptomatic intracranial artery stenosis and carotid angioplasty stenting. We collected clinical, demographical and radiological data. We used ABC/2 method to measure stroke volume in magnetic resonance imaging (MRI)/Diffusion-weighted imaging (DWI) sequences performed within 48 h. The primary outcome was the presence of HT at non-contrast brain computed tomography, performed 7 days after commencing DAPT. One hundred ninety-four patients were included. Twenty-eight (14.4%) presented HT. Higher NIH Stroke Scale (NIHSS) and MRI/DWI lesion volume related to increased risk of HT (p < 0.001). Reperfusion therapy and mechanical thrombectomy (MT), stent placement and a loading dose (LD) of dual antiplatelet or Clopidogrel were associated with a higher occurrence of HT (p < 0.05). Furthermore, we individuated an NIHSS cut-off value >4 (area under the curve (AUC) 0.80, sensitivity 0.82, specificity 0.65) and a volume cut-off value >8.2 ml (AUC 0.82, sensitivity 0.79, specificity 0.80) associated with an increased risk of HT (respectively, adjusted odds ratio (adj. OR) 6.5, confidence interval (CI) 1.3-32.7, p = 0.024 and adj. OR 11.0, CI 3.1-39.2, p < 0.001). In clinical practice, MT treatment, antiplatelet LD administration, stent placement and clinical severity may relate to a higher risk of HT in patients with AIS and DAPT in the acute phase. In particular, we found that lesion volume cut-off could help to identify patients at greater risk of HT, regardless of the indication for DAPT.

Feature-enhanced multi-sequence MRI-based fusion mechanism for breast tumor segmentation

Multi-sequence MRI plays a crucial role in the effective segmentation of breast tumors, contributing to accurate clinical diagnosis and treatment. However, the problem of missing certain sequence images may occur in clinical practice, leading to a potential impact on network performance. In medical imaging tasks, researchers are prone to ignore the correlation between different sequences, resulting in lack of expression of the extracted features. To address these problems, we propose the Feature-enhanced Multi-sequence Feature Fusion Network (FMFF-Net), which fuses information from dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) sequences to improve the accuracy of breast tumor segmentation. Utilizing an attention mechanism and adversarial learning, FMFF-Net identifies potential mappings and relationships between sequences, generating features for missing sequences and enhancing feature representation. The network incorporates a High-Frequency Edge Attention Block (HFAB) to accentuate tumor edge details, leading to more precise segmentation. Tested on a dataset of 98 high-risk breast cancer MRI images, FMFF-Net demonstrated superior performance, with a Dice Similarity Coefficient (DSC) of 83.6%, Intersection over Union (IoU) of 73.4%, F1 score of 88.1%, and Sensitivity of 74.1%. Comparative analysis against mainstream segmentation methods revealed that our proposed FMFF-Net exhibits a competitive edge in the field of breast tumor segmentation.

Exploring Radial Asymmetry in MR Diffusion Tensor Imaging and Its Impact on the Interpretation of Glymphatic Mechanisms.

Diffusion imaging holds great potential for the non-invasive assessment of the glymphatic system in humans. One technique, diffusion tensor imaging along the perivascular space (DTI-ALPS), has introduced the ALPS-index, a novel metric for evaluating diffusivity within the perivascular space. However, it still needs to be established whether the observed reduction in the ALPS-index reflects axonal changes, a common occurrence in neurodegenerative diseases. To determine whether axonal alterations can influence change in the ALPS-index. Retrospective. 100 participants (78 cognitively normal and 22 with mild cognitive impairments) aged 50-90 years old. 3T; diffusion-weighted single-shot spin-echo echo-planar imaging sequence, T1-weighted images (MP-RAGE). The ratio of two radial diffusivities of the diffusion tensor (i.e., λ2/λ3) across major white matter tracts with distinct venous/perivenous anatomy that fulfill (ALPS-tracts) and do not fulfill (control tracts) ALPS-index anatomical assumptions were analyzed. To investigate the correlation between λ2/λ3 and age/cognitive function (RAVLT) while accounting for the effect of age, linear regression was implemented to remove the age effect from each variable. Pearson correlation analysis was conducted on the residuals obtained from the linear regression. Statistical significance was set at p < 0.05. λ2 was ~50% higher than λ3 and demonstrated a consistent pattern across both ALPS and control tracts. Additionally, in both ALPS and control tracts a reduction in the λ2/λ3 ratio was observed with advancing age (r = -0.39, r = -0.29, association and forceps tract, respectively) and decreased memory function (r = 0.24, r = 0.27, association and forceps tract, respectively). The results unveil a widespread radial asymmetry of white matter tracts that changes with aging and neurodegeration. These findings highlight that the ALPS-index may not solely reflect changes in the diffusivity of the perivascular space but may also incorporate axonal contributions. 3 TECHNICAL EFFICACY: Stage 2.

Prediction of locally advanced rectal cancer response to neoadjuvant chemoradiation therapy using volumetric multiparametric MRI-based radiomics.

To assess the role of pretreatment multiparametric (mp)MRI-based radiomic features in predicting pathologic complete response (pCR) of locally advanced rectal cancer (LARC) to neoadjuvant chemoradiation therapy (nCRT). This was a retrospective dual-center study including 98 patients (M/F 77/21, mean age 60years) with LARC who underwent pretreatment mpMRI followed by nCRT and total mesorectal excision or watch and wait. Fifty-eight patients from institution 1 constituted the training set and 40 from institution 2 the validation set. Manual segmentation using volumes of interest was performed on T1WI pre-/post-contrast, T2WI and diffusion-weighted imaging (DWI) sequences. Demographic information and serum carcinoembryonic antigen (CEA) levels were collected. Shape, 1st and 2nd order radiomic features were extracted and entered in models based on principal component analysis used to predict pCR. The best model was obtained using a k-fold cross-validation method on the training set, and AUC, sensitivity and specificity for prediction of pCR were calculated on the validation set. Stage distribution was T3 (n = 79) or T4 (n = 19). Overall, 16 (16.3%) patients achieved pCR. Demographics, MRI TNM stage, and CEA were not predictive of pCR (p range 0.59-0.96), while several radiomic models achieved high diagnostic performance for prediction of pCR (in the validation set), with AUCs ranging from 0.7 to 0.9, with the best model based on high b-value DWI demonstrating AUC of 0.9 [95% confidence intervals: 0.67, 1], sensitivity of 100% [100%, 100%], and specificity of 81% [66%, 96%]. Radiomic models obtained from pre-treatment MRI show good to excellent performance for the prediction of pCR in patients with LARC, superior to clinical parameters and CEA. A larger study is needed for confirmation of these results.

Peranan Sekuen Diffusion Weighted Imaging (DWI) Pada Pemeriksaan MRI Soft Tissue Leher Kasus Kanker Nasofaring (Studi Literatur)

The aim of this research is to determine the role of the Diffusion Weighted Imaging (DWI) sequence in Soft Tissue MRI examinations of the neck in cases of nasopharyngeal cancer and to determine the advantages of using the Diffusion Weighted Imaging (DWI) sequence in MRI Soft Tissue examinations of the neck in cases of nasopharyngeal cancer. The research method used was a descriptive qualitative research method with a literature study method. The results of the literature review research showed: 1) Nasopharyngeal cancer, especially squamous cell carcinoma, can be treated with radiation therapy where treatment failure is still a serious problem, especially in advanced cases. DWI and ADC are imaging methods that utilize the movement of water inside. DWI provides additional information regarding response to treatment in hard-to-reach cases of nasopharyngeal cancer. plays an important role in detection, evaluation of response to treatment, and early monitoring of chemoradiotherapy therapy. DWI also provides information that helps distinguish between tissue experiencing post-RTH fibrosis and areas that may contain active cancer cells. DWI and ADC are also useful in tumor staging, delineation of target volumes, and detection of tumor recurrence. Elevated ADC may be indicative of a favorable response to therapy, whereas low pretreatment ADC values ​​may predict a favorable response. In the diagnosis of nasopharyngeal cancer, DWI and ADC also help differentiate squamous cell carcinoma subtypes, predict response to chemoradiation therapy, and determine the appropriate time for alternative treatment regimens. 2) DWI and ADC provide advantages in the diagnosis and monitoring of nasopharyngeal cancer. DWI can image restrictions on water diffusion within tissue, helping to detect areas of high cell density associated with tumors. Its advantages include sensitivity to microenvironmental changes and the ability to early identify recurrence or secondary cancer post-radiation therapy.

Prognostic Value of Tumor Volume, Tumor Volume Reduction Rate and Magnetic Resonance Tumor Regression Grade in Rectal Cancer.

Background and Objectives: Rectal cancer poses significant treatment challenges, especially in advanced stages. Radiologic assessment, particularly with MRI, is critical for surgeons and oncologists to understand tumor dynamics and tailor treatment strategies to improve patient outcomes. The purpose of this study was to correlate MRI-based tumor volumetric and tumor regression grade analysis in patients with advanced rectal cancer, assessing the impact of preoperative chemotherapy (CT) alone or chemoradiotherapy (CRT) on surgical technique choices. Materials and Methods: Between 2015 and 2022, a prospective study was enrolled, including a cohort of 89 patients diagnosed with rectal cancer at stage II or III. The participants were divided into two distinct therapy groups, ensuring an equal distribution with a ratio of 1:1. The initial group was treated with the contemporary preoperative chemotherapy protocol FOLFOX4. In contrast, the alternative group received conventional preoperative chemoradiotherapy. Before surgery, each patient underwent a rectal MRI scan at 1.5 T, including T2-weighted and diffusion-weighted imaging (DWI) sequences. Results: The CT group showed a 36.52% tumor volume reduction rate (TVRR), and the CRT group showed 54.87%, with varying magnetic resonance and pathological tumor regression grades (mrTRG and pTRG). Analysis revealed a significant interaction between mrTRG and tumor volumetrics (volume and VRR) in both groups, especially CRT, underscoring the complexity of tumor response. Both treatment groups had similar initial tumor volumes, with CRT displaying a higher TVRR, particularly in higher pathological TRG (3/4) cases. This interaction and the strong correlation between mrTRG and pTRG suggest mrTRG's role as a non-invasive predictor for treatment response, highlighting the need for personalized treatment plans. Conclusions: Rectal tumor volume, volume reduction rate, and mrTRG are not just abstract measures; they are concrete indicators that have a direct and practical impact on surgical decision-making, planning, and prognosis, ultimately influencing the quality of care and life expectancy of patients with rectal cancer.

Radiomics nomogram for predicting disease-free survival after partial resection or radical cystectomy in patients with bladder cancer.

To create a MRI-derived radiomics nomogram that combined clinicopathological factors and radiomics signature (Rad-score) for predicting disease-free survival (DFS) in patients with bladder cancer (BCa) following partial resection (PR) or radical cystectomy (RC), including lymphadenectomy (LAE). Finally, 80 patients with BCa after PR or RC with LAE were enrolled. Patients were randomly split into training (n = 56) and internal validation (n = 24) cohorts. Radiomic features were extracted from T2-weighted, dynamic contrast-enhanced, diffusion-weighted imaging, and apparent diffusion coefficient sequence. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was applied to choose the valuable features and construct the Rad-score. The DFS prediction model was built using the Cox proportional hazards model. The relationship between the Rad-score and DFS was assessed using Kaplan-Meier analysis. A radiomics nomogram that combined the Rad-score and clinicopathological factors was created for individualized DFS estimation. In both the training and validation cohorts, the Rad-score was positively correlated with DFS (P < .001). In the validation cohort, the radiomics nomogram combining the Rad-score, tumour pathologic stage (pT stage), and lymphovascular invasion (LVI) achieved better performance in DFS prediction (C-index, 0.807; 95% CI, 0.713-0.901) than either the clinicopathological (C-index, 0.654; 95% CI, 0.467-0.841) or Rad-score-only model (C-index, 0.770; 95% CI, 0.702-0.837). The Rad-score was an independent predictor of DFS for patients with BCa after PR or RC with LAE, and the radiomics nomogram that combined the Rad-score, pT stage, and LVI achieved better performance in individual DFS prediction. This study provided a non-invasive and simple method for personalized and accurate prediction of DFS in BCa patients after PR or RC.

Accelerating acquisition of readout-segmented echo planar imaging (rs-EPI) with a simultaneous multislice (SMS) technique for diffusion-weighted (DW) breast MRI: Evaluation of image quality factors

PurposeThis study aims to compare the image quality, apparent diffusion coefficient (ADC), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) values, and scan time between readout-segmented echo planar imaging (rs-EPI) and simultaneous multislice (SMS) rs-EPI sequences. MethodsA total of 80 consecutive women who underwent breast diffusion-weighted imaging (DWI) were included, and two rs-EPI DWI sequences with and without SMS were acquired and compared. Qualitative analysis involved three radiologists independently scoring image quality and radiologist preference. For quantitative comparison, the radiologists independently measured the ADC values in patients, while SNR, CNR, and ADC values were measured on a phantom. ResultsThe acquisition time was 5:47 min for rs-EPI and 3:20 min for SMS rs-EPI. In terms of image quality, scores were similar between rs-EPI and SMS rs-EPI sequences in the pooled data set, with the exception of skin-line distinction (p = 0.001) and background noise (p < 0.001). All radiologists considered SMS rs-EPI as equal or superior to rs-EPI in more than 70 % of cases. SMS rs-EPI demonstrated significantly higher ADC values than rs-EPI by all radiologists (p ≤ 0.002). For the phantom measurement, ADC (SMS: 1.26 ± 0.68 and RS: 1.26 ± 0.68, p = 0.198), SNR (SMS: 540.6 ± 342.1 and RS: 558.8 ± 523.2, p = 0.927), and CNR (SMS: 235.5 ± 38.9 and RS: 252.8 ± 108.0, p = 0.784) values did not significantly differ between the two sequences. ConclusionSMS rs-EPI exhibited comparable image quality and similar ADC, SNR, and CNR values to rs-EPI while reducing the scan time by 42%.

Stroke in a young adult: looking beyond the diffusion-weighted imaging sequence.

A 37-year-old migrainous woman was referred several hours after a sudden dysarthria lasting less than 1min. Brain MRI undertaken a few hours later showed no acute cerebral infarction on the diffusion-weighted imaging (DWI) sequence. However, an intraluminal thrombus within a distal branch of the middle cerebral artery (MCA) was seen on the T2*-weighted gradient echo images as well as hyperintense vessels related to slow flow beyond the occlusion's site. Control MRI 24h later confirmed the presence of a small infarct affecting the distal portion of the MCA territory but the thrombus was no longer visible. A comprehensive etiologic workup revealed the presence of a patent foramen ovale, as the underlying cause of the patient's stroke. Though the sensitivity of DWI sequence for acute ischemia is high, false negative exist particularly in cases of transient ischemic attack, brainstem or lacunar strokes. A careful brain MRI examination or the use of perfusion weighted imaging sequences are useful to avoid misdiagnosis particularly in young patients.

Papel de la resonancia magnética de difusión en el diagnóstico inicial de los tumores de partes blandas

BackgroundSoft tissue tumours (STT) constitute a heterogeneous group of lesions frequently studied by Magnetic Resonance Imaging (MRI). It has not yet been clearly established whether the inclusion of apparent diffusion coefficient (ADC) diffusion-weighted imaging (DWI) maps would better determine tumour aggressiveness. PurposeTo assess the diagnostic value of quantitative ADC DWI maps in the initial diagnosis of STT; and to determine whether the inclusion of DWI provides more valuable information than conventional sequences alone. Material and methodsRetrospective study of patients with histologically proven STT. Conventional morphological MRI sequences and the DWI sequence were analysed. The ADC was quantified using a region of interest (ROI) that covered the largest sectional area (global ADC) and another that selected the area of greatest restriction (selected ADC). Differences in ADC values were analysed between both benign and malignant lesions and high and low-grade sarcomas. A multivariate analysis was performed to determine the ability of ADC to adequately diagnose the nature of STTs when associated with other morphological characteristics. Results84 patients with STT, of which 40 were benign and 44 malignant. The malignant group included 10 low-grade sarcomas, 23 high-grade sarcomas, 4 non-sarcomatous neoplasms and 7 sarcomas with no histological grading. The ADC values were significantly higher in benign lesions for the selected ADC. Significantly higher selected ADC values were also obtained in low-grade sarcomas. In the multivariate analysis, the highest diagnostic precision values were obtained when morphological features and ADC were included, with a sensitivity, specificity, and area under the curve (AUC) of 84, 75 and 91%, respectively. ConclusionThe inclusion of ADC DWI values improves the diagnostic accuracy of MRI for STTs, especially when used in combination with conventional MRI sequences.

Role of diffusion-weighted MR imaging in the initial diagnosis of soft tissue tumours

BackgroundSoft tissue tumours (STT) constitute a heterogeneous group of lesions frequently studied by Magnetic Resonance Imaging (MRI). It has not yet been clearly established whether the inclusion of apparent diffusion coefficient (ADC) diffusion-weighted imaging (DWI) maps would better determine tumour aggressiveness. PurposeTo assess the diagnostic value of quantitative ADC DWI maps in the initial diagnosis of STT; and to determine whether the inclusion of DWI provides more valuable information than conventional sequences alone. Material and methodsRetrospective study of patients with histologically proven STT. Conventional morphological MRI sequences and the DWI sequence were analysed. The ADC was quantified using a region of interest (ROI) that covered the largest sectional area (global ADC) and another that selected the area of ​​greatest restriction (selected ADC). Differences in ADC values ​​were analysed between both benign and malignant lesions and high and low-grade sarcomas. A multivariate analysis was performed to determine the ability of ADC ​​to adequately diagnose the nature of STTs when associated with other morphological characteristics. Results84 patients with STT, of which 40 were benign and 44 malignant. The malignant group included 10 low-grade sarcomas, 23 high-grade sarcomas, 4 non-sarcomatous neoplasms and 7 sarcomas with no histological grading. The ADC values ​​were significantly higher in benign lesions for the selected ADC. Significantly higher selected ADC values ​​were also obtained in low-grade sarcomas. In the multivariate analysis, the highest diagnostic precision values were obtained when morphological features and ADC were included, with a sensitivity, specificity, and area under the curve (AUC) of 84, 75 and 91%, respectively. ConclusionThe inclusion of ADC DWI values ​​improves the diagnostic accuracy of MRI for STTs, especially when used in combination with conventional MRI sequences.

Analysis of Diffusion-Weighted and T2-Weighted Imaging in the Prediction of Distinct Granulation Patterns of Somatotroph Adenomas

ObjectiveThe heterogeneity of the somatotroph adenomas, especially for SG and DG subtypes, has attracted great attention in identifying the imaging biomarker of them. The purpose of current study was to compare the diagnostic performance of diffusion-weighted and T2-weighted MRI sequences for preoperatively distinguishing the granulation patterns of somatotroph adenomas. Methods32 patients with clinical diagnosis of somatotroph adenomas from October 2018 to March 2023 were included in this study. Coronal diffusion-weighted imaging (DWI) and T2-weighted MRI sequences data was collected from 3.0T MRI and compared between SG and DG groups. The immunohistochemistry (IHC) was used to confirm the EM pathological subtypes and Ki67 expression levels of somatotroph adenomas postoperatively. ResultsPatients in the SG group had significantly higher signal intensity (SI) ratio of DWI (rDWI) (P<0.001), lower SI ratio of apparent diffusion coefficient (ADC) (rADC) (P<0.001), and higher SI ratio of T2-weighted imaging (rT2) (P=0.011). The combined diagnose index of rDWI and rADC had the highest diagnostic efficiency predicting SG adenomas (sensitivity, 93.3%; specificity, 88.2%; P < 0.001). The rDWI and rADC value had positive and negative correlations with Ki67 index and tumor maximum diameter, respectively. Lower rADC×103 was an independent predictor for SG adenomas. ConclusionsOur results indicated that compared with previously used T2-weighted imaging, the DWI sequence, especially the combined diagnosis index of rDWI and rADC could more efficiently distinguish the granulation patterns of somatotroph adenomas preoperatively.

Preoperative Noninvasive Evaluation of Tumor Budding in Rectal Cancer Using Multiparameter MRI Radiomics

To assess the value of a multiparametric magnetic resonance imaging (MRI)-based model integrating radiomics features with clinical and MRI semantic features for preoperative evaluation of tumor budding (TB) in rectal cancer. A total of 120 patients with pathologically confirmed rectal cancer were retrospectively analyzed. The patients were randomized into training and validation cohorts in a 6:4 ratio. Radiomics features were extracted and selected from preoperative T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted imaging (T1CE) sequences, after which the corresponding radiomics score (RS) was calculated, and the radiomics models (T2WI model, DWI model, and T1CE model) were constructed. Logistic regression analysis was selected to develop a combined model integrated RST2WI, RSDWI, RST1CE, and clinical and MRI semantic features. The efficacy of each model in diagnosing TB grade was observed by the receiver operating characteristic (ROC) curve. Decision curve analysis (DCA) was used to assess the clinical benefits of the models. Seven features were extracted and selected from each T2WI, DWI, and T1CE sequence to calculate the corresponding RS and construct the corresponding radiomics model. MRI reported N stagewas an independent risk factor for TB. The area under the ROC curveof the combined model was 0.961 and 0.891 in the training and validation cohorts, respectively. The combined model showed better performance than the other models. DCA showed that the net benefit of the combined model was better than that of the other models in the vast majority of threshold probabilities. A combined model integrating radiomics features and MRI semantic features allows for noninvasive preoperative evaluation of TB grading in patients with rectal cancer.

Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate cancer.

In recent years, magnetic resonance imaging (MRI) has shown excellent results in the study of the prostate gland. MRI has indeed shown to be advantageous in the prostate cancer (PCa) detection, as in guiding targeting biopsy, improving its diagnostic yield. Although current acquisition protocols provide for multiparametric acquisition, recent evidence has shown that biparametric protocols can be non-inferior in PCa detection. Diffusion-weighted imaging (DWI) sequence, in particular, plays a key role, particularly in the peripheral zone which accounts for the larger part of the prostate. High b-values are generally recommended, although with the possibility of obtaining non-Gaussian diffusion effects, which requires a more sophisticated model for the analysis, namely through the diffusion kurtosis imaging (DKI). Purpose of this narrative review was to analyze the current applications and clinical evidence regarding the use of DKI with a main focus on PCa detection, also in comparison with DWI. This narrative review synthesized the findings of literature retrieved from main researches, narrative and systematic reviews, and meta-analyses obtained from PubMed. DKI analyses the non-Gaussian water diffusivity and describe the effect of signal intensity decay related to high b-value through two main metrics (Dapp and Kapp). Differently from DWI-apparent diffusion coefficient (DWI-ADC) which reflects only water restriction outside of cells, DKI metrics are supposed to represent also the direct interaction of water molecules with cell membranes and intracellular compounds. This review describes current evidence on ADC and DKI metrics in clinical imaging, and finally collect the results derived from the main articles focused on DWI and DKI models in detecting PCa. DKI advantages, compared to conventional ADC analysis, still remain controversial. Wider application and greater technical knowledge of DKI, however, may help in proving its intrinsic validity in the field of oncology and therefore in the study of clinically significant PCa. Finally, a deep understanding of DKI is important for radiologists to better understand what Kapp and Dapp mean in the context of different cancer and how these metrics may vary specifically in PCa imaging.

Multisequence MRI-based radiomics analysis for early prediction of the risk of T790M resistance in new brain metastases.

Predicting whether T790M emerges early is crucial to the adjustment of targeted drugs for non-small cell lung cancer (NSCLC) patients. This study aimed to evaluate the risk of T790M resistance in progressive new brain metastases (BMs) based on multisequence magnetic resonance imaging (MRI) radiomics. This retrospective study included 405 consecutive patients (training cohort: 294 patients; testing cohort: 111 patients) with proven NSCLC with disease progression of new BM. The radiomics features were separately extracted from T2-weighted imaging (T2WI), T2 fluid-attenuated inversion recovery (T2-FLAIR), diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted imaging (T1-CE) sequence of baseline MRI. Then, we calculated radiomics scores (rad-score) of the 4 sequences respectively and established predictive models (lesion- or patient-level) to evaluate T790M resistance within up to 14 months using random forest classifier. Receiver operating characteristic (ROC) curves and F1 scores were used to validate the performance of two models in both the training and testing cohort. There were significant differences in rad-scores of the four sequences between T790M-positive and negative groups whether in the training or testing cohort (P<0.05). The lesion-level model consisting of rad-scores showed excellent discrimination, with an area under the curve (AUC) and F1-score of 0.879 and 0.798 in the training cohort, and 0.834 and 0.742 in the testing cohort, respectively. The patient-level model also showed a favorable discriminatory ability with an AUC and F1 score of 0.851 and 0.837, which was confirmed with an AUC and F1 score of 0.734 and 0.716 in the testing cohort. The MRI-based radiomics signatures may be new markers to identify patients at high risk of developing resistance in the early period.

Whole tumor based texture analysis of magnetic resonance diffusion imaging for colorectal liver metastases: A prospective study for diffusion model comparison and early response biomarker

PurposeTo evaluate and compare the diagnostic value of diffusion-related texture analysis parameters obtained from various magnetic resonance diffusion models as early predictors of the clinical response to chemotherapy in patients with colorectal liver metastases (CRLM). MethodsPatients (n = 145) with CRLM were prospectively and consecutively enrolled and scanned using diffusion-weighted imaging (DWI)-magnetic resonance imaging (MRI)/intravoxel incoherent motion (IVIM)/diffusion kurtosis imaging (DKI) before (baseline) and two–three weeks after (follow-up) commencing chemotherapy. Therapy response was evaluated based on the Response Evaluation Criteria in Solid Tumors (RECIST, version 1.1). The histogram and texture parameters of each diffusion-related parametric map were analysed between the responding and non-responding groups, screened using LASSO, and fitted with binary logistic regression models. The diagnostic efficacy of each model in the early prediction of CRLM was analysed, and the corresponding receiver operating characteristic (ROC) curve was drawn. The area under the curve (AUC) and 95% confidence intervals (CI) were calculated. ResultsOf the 145 analysed patients, 69 were in the responding group and 76 were in the non-responding group. Among all models, the difference value based on the histogram and texture features of the DKI-derived parameters performed best for the early prediction of CRLM treatment efficacy. The AUC of the DKI model in the validation set reached 0.795 (95% CI 0.652–0.938). Among the IVIM-derived parameters, the difference model based on D and D* performed best, and the AUC in the validation set reached 0.737 (95% CI 0.586–0.889). Finally, in the DWI sequence, the model comprising baseline features performed the best, with an AUC of 0.699 (95% CI 0.537–0.86) in the validation set. ConclusionsBaseline DWI parameters and follow-up changes in IVIM and DKI parameters predicted the chemotherapeutic response in patients with CRLM. In addition, as very early predictors, DKI-derived parameters were more effective than DWI- and IVIM-related parameters, in which changes in D-parameters performed best.

NIMG-21. SERIAL QUANTITATIVE MRI RADIOMICS SIGNATURE FOR PREDICTION OF SURVIVAL IN GLIOBLASTOMA – A PILOT STUDY

Abstract INTRODUCTION Radiomics in glioblastoma (GBM) imaging incorporates mathematical and statistical quantification of complex imaging features as surrogate biomarkers of tumour physiology. Delta-radiomics extends this capability by monitoring changes in these features over time. This study aims to evaluate selected radiomic and delta-radiomic features of diffusion-weighted imaging (DWI) as potential early predictors of overall survival (OS) in GBM patients undergoing adjuvant chemo-radiotherapy (aCRT). METHODS Imaging and data from n=12 newly diagnosed GBM patients prospectively recruited at Liverpool Hospital, New South Wales, were retrospectively analysed. Patients underwent serial MRI via 3.0T Siemens Magnetom-Skyra scanner, including anatomical and DWI sequences, before aCRT (baseline), and at 3 (FU1) and 6 weeks (FU2) post aCRT commencement. Gross tumour volume (GTV) was manually segmented on contrast-enhanced T1-weighted images. Four first-order histogram radiomic features (mean, skewness, entropy and 10th-percentile) and volume were extracted from the GTV on DWI sequences at each timepoint. Delta-radiomic features were calculated from the difference between measurements at baseline and each follow-up. Linear correlation between OS versus baseline and delta-radiomic features were calculated with Pearson’s coefficient (r). Statistically significant correlations were tested on an external validation dataset of n=8 GBM cases from The Cancer Imaging Archive (ACRIN-FMISO-Brain and ACRIN-DSC-MR-Brain datasets). RESULTS A significant positive correlation was found between OS and delta-entropy at FU2 (r = 0.639, p = 0.02). No significant correlation was found between OS and baseline or delta mean, skewness, or 10th percentile (p &amp;gt; 0.05). No significant correlation was found between OS and delta-volume at FU1 (r = 0.134, p = 0.68) or FU2 (r = 0.100, p = 0.76). CONCLUSION Our results indicate a potential utility of delta-entropy for prediction of overall survival. RESULTS will be validated on an external dataset. Further evaluation of radiomic and delta-radiomic features on a larger sample size is warranted.

Association Between MRI Radiomics and Intratumoral Tertiary Lymphoid Structures in Intrahepatic Cholangiocarcinoma and Its Prognostic Significance.

Tertiary lymphoid structures (TLSs) have prognostic value in intrahepatic cholangiocarcinoma (ICC) patients. Noninvasive tool to preoperatively evaluate TLSs is still lacking. To explore the association between TLSs status of ICC and preoperative MRI radiomics analysis. Retrospective. One hundred and ninety-two patients with ICC, divided into training (T = 105), internal validation groups (V1 = 46), and external validation group (V2 = 41). Coronal and axial single-shot fast spin-echo T2-weighted, diffusion-weighted imaging, T1-weighted, and T1WI fat-suppressed spoiled gradient-recall echo LAVA sequence at 3.0 T. The VOIs were drawn manually within the visible borders of the tumors using ITK-SNAP version 3.8.0 software in the axial T2WI, DWI, and portal vein phase sequences. Radiomics features were subjected to least absolute shrinkage and selection operator regression to select the associated features of TLSs and construct the radiomics model. Univariate and multivariate analyses were used to identify the clinical radiological variables associated with TLSs. The performances were evaluated by the area under the receiver operator characteristic curve (AUC). Logistic regression analysis, ROC and AUC, Hosmer-Lemeshow test, Kaplan-Meier method with the log-rank test, calibration curves, and decision curve analysis. P < 0.05 was considered statistically significant. The AUCs of arterial phase diffuse hyperenhancement were 0.59 (95% confidence interval [CI], 0.50-0.67), 0.52 (95% CI, 0.43-0.61), and 0.66 (95% CI, 0.52-0.80) in the T, V1, and V2 cohorts. The AUCs of Rad-score were 0.85 (95% CI, 0.77-0.92), 0.81 (95% CI, 0.67-0.94), and 0.84 (95% CI, 0.71-0.96) in the T, V1, and V2 cohorts, respectively. In cohort T, low-risk group showed significantly better median recurrence-free survival (RFS)than that of the high-risk group, which was also confirmed in cohort V1 and V2. A preoperative MRI radiomics signature is associated with the intratumoral TLSs status of ICC patients and correlate significantly with RFS. 3 TECHNICAL EFFICACY: Stage 2.