Does volumetric measurement of ADC values achieve higher diagnostic performance in bladder cancer MRI?

BACKGROUND

Apparent diffusion coefficient (ADC) value is an important part of bladder cancer magnetic resonance imaging (MRI) assessment and can predict the aggressive and invasive potentials. There is growing interest in whole tumor volume measurements.

PURPOSE

To investigate if the volumetric ADC measurement method will significantly exceed the diagnostic performance of the selected region of interest (ROI) method in everyday practice.

MATERIAL AND METHODS

A prospective evaluation was carried out of 50 patients with bladder cancer by two radiologists. The mean and the minimum ADC values were measured using both methods. The inter-reader agreement was determined by the intraclass correlation coefficient. The ADC values were compared between different grades, states of muscle invasion, and lympho-vascular invasion (LVI); then, validity was evaluated using receiver operating characteristic (ROC) curves. Areas under the curve (AUC) were then compared for the level of statistical significance.

RESULTS

The inter-observer agreement was excellent for the ADC values using both methods. The volumetric measurement provides higher mean and lower minimum ADC values with statistically significant differences (P <0.00001). The highest diagnostic accuracy for differentiating tumor grade and predicting muscle invasion was for the minimum ADC by a selected ROI. However, the differences between the achieved AUCs were of no statistical significance. None of the ADC values predicted LVI with statistical significance.

CONCLUSION

The selected ROI and volumetric measurement methods of mean and minimum ADC in bladder cancer yield different values, still having comparable diagnostic performance with accurate ROI sampling. The minimum ADC value by ROI is preferred in everyday clinical practice.

Differentiation of submandibular sialadenitis based on apparent diffusion coefficient

OBJECTIVES

This study aimed to quantify the submandibular gland in suppurative sialadenitis, primary Sjögren's syndrome (pSS) and radiation-induced sialadenitis using the apparent diffusion coefficient (ADC) for differential diagnosis.

SUBJECTS AND METHODS

This retrospective study included 16 patients with suppurative sialadenitis (n = 9), pSS (n = 3) and radiation-induced sialadenitis (n = 4) who underwent magnetic resonance imaging between June 2006 and May 2022. The ADC of the submandibular glands in each state was calculated, and the differences were analysed using a one-way analysis of variance and Tukey's post hoc test. Receiver operating characteristic curves were used to assess the ability of the ADC to distinguish each condition. Statistical significance was set at p < 0.05.

RESULTS

The mean ADC value (×10-3 mm2/s) ± standard deviation in the control (non-affected side of the suppurative sialadenitis group), suppurative sialadenitis, pSS and radiation-induced groups were 0.94 ± 0.16, 1.24 ± 0.16, 1.33 ± 0.13 and 1.5 ± 0.12, respectively (p < 0.001). The diagnostic value for distinguishing each group was ≥0.75.

CONCLUSION

ADC values are useful for quantitatively assessing and distinguishing submandibular glands in suppurative sialadenitis, primary Sjögren's syndrome and radiation-induced sialadenitis.

Dual-Hit Strategy for Therapeutic Targeting of Pancreatic Cancer in Patient-Derived Xenograft Tumors

PURPOSE

Paracrine activation of pro-fibrotic hedgehog (HH) signaling in pancreatic ductal adenocarcinoma (PDAC) results in stromal amplification that compromises tumor drug delivery, efficacy, and patient survival. Interdiction of HH-mediated tumor-stroma crosstalk with smoothened (SMO) inhibitors (SHHi) "primes" PDAC patient-derived xenograft (PDX) tumors for increased drug delivery by transiently increasing vascular patency/permeability, and thereby macromolecule delivery. However, patient tumor isolates vary in their responsiveness, and responders show co-induction of epithelial-mesenchymal transition (EMT). We aimed to identify the signal derangements responsible for EMT induction and reverse them and devise approaches to stratify SHHi-responsive tumors noninvasively based on clinically-quantifiable parameters.

EXPERIMENTAL DESIGN

Animals underwent diffusion-weighted magnetic resonance (DW-MR) imaging for measurement of intratumor diffusivity. In parallel, tissue-level deposition of nanoparticle probes was quantified as a marker of vascular permeability/perfusion. Transcriptomic and bioinformatic analysis was employed to investigate SHHi-induced gene reprogramming and identify key "nodes" responsible for EMT induction.

RESULTS

Multiple patient tumor isolates responded to short-term SHH inhibitor exposure with increased vascular patency and permeability, with proportionate increases in tumor diffusivity. Nonresponding PDXs did not. SHHi-treated tumors showed elevated FGF drive and distinctly higher nuclear localization of fibroblast growth factor receptor (FGFR1) in EMT-polarized tumor cells. Pan-FGFR inhibitor NVP-BGJ398 (Infigratinib) reversed the SHHi-induced EMT marker expression and nuclear FGFR1 accumulation without compromising the enhanced permeability effect.

CONCLUSIONS

This dual-hit strategy of SMO and FGFR inhibition provides a clinically-translatable approach to compromise the profound impermeability of PDAC tumors. Furthermore, clinical deployment of DW-MR imaging could fulfill the essential clinical-translational requirement for patient stratification.

Abdominal Diffusion-Weighted MRI With Simultaneous Multi-Slice Acquisition: Agreement and Reproducibility of Apparent Diffusion Coefficients Measurements

BACKGROUND

Simultaneous multi-slice diffusion-weighted imaging (SMS-DWI) can shorten acquisition time in abdominal imaging.

PURPOSE

To investigate the agreement and reproducibility of apparent diffusion coefficient (ADC) from abdominal SMS-DWI acquired with different vendors and different breathing schemes.

STUDY TYPE

Prospective.

SUBJECTS

Twenty volunteers and 10 patients.

FIELD STRENGTH/SEQUENCE

3.0 T, SMS-DWI with a diffusion-weighted echo-planar imaging sequence.

ASSESSMENT

SMS-DWI was acquired using breath-hold and free-breathing techniques in scanners from two vendors, yielding four scans in each participant. Average ADC values were measured in the liver, pancreas, spleen, and both kidneys. Non-normalized ADC and ADCs normalized to the spleen were compared between vendors and breathing schemes.

STATISTICAL TESTS

Paired t-test or Wilcoxon signed rank test; intraclass correlation coefficient (ICC); Bland-Altman method; coefficient of variation (CV) analysis; significance level: P < 0.05.

RESULTS

Non-normalized ADCs from the four SMS-DWI scans did not differ significantly in the spleen (P = 0.262, 0.330, 0.166, 0.122), right kidney (P = 0.167, 0.538, 0.957, 0.086), and left kidney (P = 0.182, 0.281, 0.504, 0.405), but there were significant differences in the liver and pancreas. For normalized ADCs, there were no significant differences in the liver (P = 0.315, 0.915, 0.198, 0.799), spleen (P = 0.815, 0.689, 0.347, 0.423), pancreas (P = 0.165, 0.336, 0.304, 0.584), right kidney (P = 0.165, 0.336, 0.304, 0.584), and left kidney (P = 0.496, 0.304, 0.443, 0.371). Inter-reader agreements of non-normalized ADCs were good to excellent (ICCs ranged from 0.861 to 0.983), and agreement and reproducibility were good to excellent depending on anatomic location (CVs ranged from 3.55% to 13.98%). Overall CVs for abdominal ADCs from the four scans were 6.25%, 7.62%, 7.08, and 7.60%.

DATA CONCLUSION

The normalized ADCs from abdominal SMS-DWI may be comparable between different vendors and breathing schemes, showing good agreement and reproducibility. ADC changes above approximately 8% may potentially be considered as a reliable quantitative biomarker to assess disease or treatment-related changes.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Combination of prostate volume and apparent diffusion coefficient can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies

BACKGROUND

Nowadays, there are many patients who undergo unnecessary prostate biopsies after receiving a prostate imaging reporting and data system (PI-RADS) score of 3. Our purpose is to identify cutoff values of the prostate volume (PV) and minimum apparent diffusion coefficient (ADCmin) to stratify those patients to reduce unnecessary prostate biopsies.

METHODS

Data from 224 qualified patients who received prostate biopsies from January 2019 to June 2023 were collected. The Mann-Whitney U test was used to compare non-normal distributed continuous variables, which were recorded as median (interquartile ranges). The correlation coefficients were calculated using Spearman's rank correlation analysis. Categorical variables are recorded by numbers (percentages) and compared by χ2 test. Both univariate and multivariate logistic regression analysis were used to determine the independent predictors. The receiver-operating characteristic curve and the area under the curve (AUC) were used to evaluate the diagnostic performance of clinical variables.

RESULTS

Out of a total of 224 patients, 36 patients (16.07%) were diagnosed with clinically significant prostate cancer (csPCa), whereas 72 patients (32.14%) were diagnosed with any grade prostate cancer. The result of multivariate analysis demonstrated that the PV (p < 0.001, odds ratio [OR]: 0.952, 95% confidence interval [95% CI]: 0.927-0.978) and ADCmin (p < 0.01, OR: 0.993, 95% CI: 0.989-0.998) were the independent factors for predicting csPCa. The AUC values of the PV and ADCmin were 0.779 (95% CI: 0.718-0.831) and 0.799 (95% CI: 0.740-0.849), respectively, for diagnosing csPCa. After stratifying patients by PV and ADCmin, 24 patients (47.06%) with "PV < 55 mL and ADCmin < 685 μm2/s" were diagnosed with csPCa. However, only one patient (1.25%) with PV ≥ 55 mL and ADCmin ≥ 685 μm2/s were diagnosed with csPCa.

CONCLUSIONS

In this study, we found the combination of PV and ADCmin can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies. These patients with "PV ≥ 55 mL and ADCmin ≥ 685 μm2/s" may safely avoid prostate biopsies.

Investigation of radiomics models for predicting biochemical recurrence of advanced prostate cancer on pretreatment MR ADC maps based on automatic image segmentation

OBJECTIVES

To develop radiomics models based on automatic segmentation of the pretreatment apparent diffusion coefficient (ADC) maps for predicting the biochemical recurrence (BCR) of advanced prostate cancer (PCa).

METHODS

A total of 100 cases with pathologically confirmed PCa were retrospectively included in this study. These cases were randomly divided into training (n = 70) and test (n = 30) datasets. Two predictive models were constructed based on the combination of age, prostate specific antigen (PSA) level, Gleason score, and clinical staging before therapy and the prostate area (Model_1) or PCa area (Model_2). Another two predictive models were constructed based on only prostate area (Model_3) or PCa area (Model_4). The area under the receiver operating characteristic curve (ROC AUC) and precision-recall (PR) curve analysis were used to analyze the models' performance.

RESULTS

Sixty-five patients without BCR (BCR-) and 35 patients with BCR (BCR+) were confirmed. The age, PSA, volume, diameter and ADC value of the prostate and PCa were not significantly different between the BCR- and BCR+ groups or between the training and test datasets (all p > 0.05). The AUCs were 0.637 (95% CI: 0.434-0.838), 0.841 (95% CI: 0.695-0.940), 0.840 (95% CI: 0.698-0.983), and 0.808 (95% CI: 0.627-0.988) for Model_1 to Model_4 in the test dataset without significant difference. The 95% bootstrap confidence intervals for the areas under the PR curve of the four models were not statistically different.

CONCLUSION

The radiomics models based on automatically segmented prostate and PCa areas on the pretreatment ADC maps developed in our study can be promising in predicting BCR of advanced PCa.

Sex differences in normal fetal regional brain apparent diffusion coefficient changes assessed by in utero DWI

Objective

There are differences in the vulnerability of male and female fetal brains to adverse intrauterine exposure, preterm birth, and associated perinatal brain injury. The main objective of this study was to identify any statistically significant difference in the change of apparent diffusion coefficient (ADC) in the intracranial regions of male and female fetuses in the second and third trimesters.

Methods

Diffusion-weighted imaging (DWI) was performed in 200 fetuses between 20 and 37 gestational ages (GA) with normal results or suspicious results on sonography followed by structural MRI. Pairwise ADC values of the regions of interest (ROIs) were manually delineated on either side of the cerebral white matter: frontal white matter (FWM), parietal white matter (PWM), occipital white matter (OWM), temporal white matter (TWM), basal ganglia (BG), thalamus (THA), cerebellar hemisphere (CBM), and a single measurement in the pons. The changes in these values were studied over the gestational range, along with potential sex differences and asymmetries of the cerebral hemispheres.

Results

During the third trimester, ADC values in OWM, TWM, and CBM were significantly higher in male fetuses than those in female fetuses (p < 0.05). After the correction of false-discovery rates (FDR), the difference in CBM was the only statistically significant (p = 0.0032). However, the decreased rate of ADC values in male fetuses in CWM (except for FWM), BG, THA, CBM, and pons was higher than that in female fetuses during the second and third trimesters.

Conclusions

We have shown some differences in the intracranial regional ADC changes between male and female fetuses using in utero DWI during the second and third trimesters.

Role of diffusion-weighted imaging in response prediction and evaluation after high dose rate brachytherapy in patients with colorectal liver metastases

BACKGROUND

The aim of the study was to assess the role of diffusion-weighted imaging (DWI) to evaluate treatment response in patients with liver metastases of colorectal cancer.

PATIENTS AND METHODS

In this retrospective, observational cohort study, we included 19 patients with 18 responding metastases (R-Mets; follow-up at least one year) and 11 non-responding metastases (NR-Mets; local tumor recurrence within one year) who were treated with high-dose-rate brachytherapy (HDR-BT) and underwent pre- and post-interventional MRI. DWI (qualitatively, mean apparent diffusion coefficient [ADCmean], ADCmin, intraindividual change of ADCmean and ADCmin) were evaluated and compared between pre-interventional MRI, first follow-up after 3 months and second follow-up at the time of the local tumor recurrence (in NR-Mets, mean: 284 ± 122 d) or after 12 months (in R-Mets, mean: 387+/-64 d). Sensitivity, specificity, positive predictive values (PPVs), and negative predictive values (NPVs) for detection of local tumor recurrence were calculated on second follow up, evaluating (1) DWI images only, and (2) DWI with Gd-enhanced T1-weighted images on hepatobiliary phase (contrast-enhanced [CE] T1-weight [T1w] hepatobiliary phase [hb]).

RESULTS

ADCmean significantly increased 3 months after HDR-BT in both groups (R-Mets: 1.48 ± 0.44 and NR-Mets: 1.49 ± 0.19 x 10-3 mm2;/s, p < 0.0001 and p = 0.01), however, intraindividual change of ADCmean (175% vs.127%, p = 0.03) and ADCmin values (0.44 ± 0.24 to 0.82 ± 0.58 x 10-3 mm2/s) significantly increased only in R-Mets (p < 0.0001 and p < 0.001). ADCmin was significant higher in R-Mets compared to NR-Mets on first follow-up (p = 0.04). Sensitivity (1 vs. 0.72), specificity (0.94 vs. 0.72), PPV (0.91 vs. 0.61) and NPV (1 vs. 0.81) could be improved by combining DWI with CE T1w hb compared to DWI only.

CONCLUSIONS

DW-MRI seems to be helpful in the qualitative and quantitative evaluation of treatment response after HDR-BT of colorectal metastases in the liver.

Development and benchmarking diffusion magnetic resonance imaging analysis for integration into radiation treatment planning

PURPOSE

The rising promise in the utility of advanced multi-parametric magnetic resonance (MR) imaging in radiotherapy (RT) treatment planning creates a necessity for testing and enhancing the accuracy of quantitative imaging analysis. Standardizing the analysis of diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) to generate meaningful and reproducible apparent diffusion coefficient (ADC) and fractional anisotropy (FA) lays the requisite needed for clinical integration. The aim of the demonstrated work is to benchmark the generation of the ADC and FA parametric map analyses using integrated tools in a commercial treatment planning system against the currently used ones.

METHODS

Three software packages were used for generating ADC and FA maps in this study; one tool was developed within a commercial treatment planning system, another by the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library FSL (Analysis Group, FMRIB, Oxford, United Kingdom), and an in-house tool developed at the M.D. Anderson Cancer Center. The ADC and FA maps generated by all three packages for 35 subjects were subtracted from one another, and the standard deviation of the images' differences was used to compare the reproducibility. The reproducibility of the ADC maps was compared with the Quantitative Imaging Biomarkers Alliance (QIBA) protocol, while that of the FA maps was compared to data in published literature.

RESULTS

Results show that the discrepancies between the ADC maps calculated for each patient using the three different software algorithms are less than 2% which meets the 3.6% recommended QIBA requirement. Except for a small number of isolated points, the majority of differences in FA maps for each patient produced by the three methods did not exceed 0.02 which is 10 times lower than the differences seen in healthy gray and white matter. The results were also compared to the maps generated by existing MR Imaging consoles and showed that the robustness of console generated ADC and FA maps is largely dependent on the correct application of scaling factors, that only if correctly placed; the differences between the three tested methods and the console generated values were within the recommended QIBA guidelines.

CONCLUSIONS

Cross-comparison difference maps demonstrated that quantitative reproducibility of ADC and FA metrics generated using our tested commercial treatment planning system were comparable to in-house and established tools as benchmarks. This integrated approach facilitates the clinical utility of diffusion imaging in radiation treatment planning workflow.

Deep learning-based radiomics model from pretreatment ADC to predict biochemical recurrence in advanced prostate cancer

Purpose

To develop deep-learning radiomics model for predicting biochemical recurrence (BCR) of advanced prostate cancer (PCa) based on pretreatment apparent diffusion coefficient (ADC) maps.

Methods

Data were collected retrospectively from 131 patients diagnosed with advanced PCa, randomly divided into training (n = 93) and test (n = 38) datasets. Pre-treatment ADC images were segmented using a pre-trained artificial intelligence (AI) model to identify suspicious PCa areas. Three models were constructed, including a clinical model, a conventional radiomics model and a deep-radiomics model. The receiver operating characteristic (ROC), precision-recall (PR) curve and decision curve analysis (DCA) were used to assess predictive performance in test dataset. The net reclassification index (NRI) and integrated discrimination improvement (IDI) were employed to compare the performance enhancement of the deep-radiomics model in relation to the other two models.

Results

The deep-radiomics model exhibited a significantly higher area under the curve (AUC) of ROC than the other two (P = 0.033, 0.026), as well as PR curve (AUC difference 0.420, 0.432). The DCA curve demonstrated superior performance for the deep-radiomics model across all risk thresholds than the other two. Taking the clinical model as reference, the NRI and IDI was 0.508 and 0.679 for the deep-radiomics model with significant difference. Compared with the conventional radiomics model, the NRI and IDI was 0.149 and 0.164 for the deep-radiomics model without significant difference.

Conclusion

The deep-radiomics model exhibits promising potential in predicting BCR in advanced PCa, compared to both the clinical model and the conventional radiomics model.

Apparent diffusion coefficient for differentiation between extra-nodal lymphoma and squamous cell carcinoma in the head and neck: a systematic review and meta-analysis

BACKGROUND

Radiological differentiation between extra-nodal lymphoma and squamous cell carcinoma in the head and neck is often difficult due to their similarities.

PURPOSE

To evaluate the diagnostic benefit of apparent diffusion coefficient (ADC) calculated from diffusion-weighted imaging (DWI) in differentiating the two.

MATERIAL AND METHODS

A systematic review was performed by searching the MEDLINE, Scopus, and Embase databases in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement. Forest plots and the pooled mean difference of ADC values were calculated to describe the relationship between extra-nodal lymphoma and squamous cell carcinoma in the head and neck. Heterogeneity among studies was evaluated using the Cochrane Q test and I2 statistic.

RESULTS

The review identified eight studies with 440 patients (441 lesions) eligible for meta-analysis. Among all studies, the mean ADC values of squamous cell carcinoma was 0.88 × 10-3mm2/s and that of lymphoma was 0.64 × 10-3mm2/s. In the meta-analysis, the ADC value of lymphoma was significantly lower than that of squamous cell carcinoma (pooled mean difference = 0.235, 95% confidence interval [CI] = 0.168-0.302, P <0.0001). The Cochrane Q test (chi-square = 55.7, P <0.0001) and I2 statistic (I2 = 87.4%, 95% CI = 77.4-93.0%) revealed significant heterogeneity.

CONCLUSION

This study highlights the value of quantitative assessment of ADC for objective and reliable differentiation between extra-nodal lymphoma and squamous cell carcinoma in the head and neck. Conclusions should be interpreted with caution due to heterogeneity in the study data.

Prognostic Value of Apparent Diffusion Coefficient (ADC) in Patients with Diffuse Gliomas

This study aimed to evaluate potential posttreatment changes in ADC values within the tissue surrounding the enhancing lesion, particularly in areas not exhibiting MRI characteristics of involvement. Additionally, the objective was to investigate the correlations among ADC values, treatment response, and survival outcomes in individuals diagnosed with gliomas. This retrospective study included a total of 49 patients that underwent either stereotactic biopsy or maximal surgical resection. Histologically confirmed as Grade III or IV gliomas, all cases adhered to the 2016 and 2021 WHO classifications, with subsequent radio-chemotherapy administered post-surgery. Patients were divided into two groups: short and long survival groups. Baseline and follow-up MRI scans were obtained on a 1.5 T MRI scanner. Two ROI circles were positioned near the enhancing area, one ROI in the NAWM ipsilateral to the neoplasm and another symmetrically in the contralateral hemisphere on ADC maps. At follow-up there was a significant difference in both ipsilateral and contralateral NAWM between the two groups, -0.0857 (p = 0.004) and -0.0607 (p = 0.037), respectively. There was a weak negative correlation between survival and ADC values in ipsilateral and contralateral NAWM at the baseline with the correlation coefficient -0.328 (p = 0.02) and -0.302 (p = 0.04), respectively. The correlation was stronger at the follow-up. The findings indicate that ADC values in normal-appearing white matter (NAWM) may function as a prognostic biomarker in patients with diffuse gliomas.

Apparent diffusion coefficient values can predict neuromotor outcome in term neonates with hypoxic-ischaemic encephalopathy

AIM

To determine the apparent diffusion coefficient (ADC) in brain structures during the first 2 weeks of life and its relation with neurological outcome for hypoxic-ischaemic encephalopathy (HIE) in term neonates.

METHODS

We retrospectively evaluated 56 term-born neonates. The ADC values were measured for 11 brain regions. The clinical outcomes at least 2 years of age were defined as normal outcome, mild disability and severe disability. The area under curves (AUCs) by ROC analysis were performed to predict the neurodevelopmental outcomes. The clinical outcomes were compared between favourable outcome and adverse outcome and also between normal outcome and unfavourable outcome.

RESULTS

Thirty-four patients were judged as normal outcome, 10 as mild disability and 12 as severe disability. When the clinical outcomes were compared between favourable outcome and adverse outcome, the AUC on the 1st week was highest value at the thalamus. When the clinical outcomes were compared between normal outcome and unfavourable outcome, the AUC on the 1st week was highest at the thalamus.

CONCLUSION

The ADC values in the thalamus in the 1st week can predict the neurological outcome. The ADC values in centrum semiovale on the 2nd week can be used to predict neurodevelopmental outcomes.

Survival prediction using apparent diffusion coefficient values in recurrent glioblastoma under bevacizumab treatment: an updated systematic review and meta-analysis

Bevacizumab is a common strategy for the treatment of recurrent glioblastoma. Survival status is a crucial issue for patients with recurrent glioblastoma, and the apparent diffusion coefficient (ADC) values of the lower Gaussian curve have been reported to have the potential to predict prognosis in recurrent glioblastoma. In the present study, we aimed to clarify the survival prediction of ADC values in patients with recurrent glioblastoma receiving bevacizumab treatment through a systematic review and meta-analysis of randomized clinical trials, comparing ADC values higher than the cut-off values with those lower than the cut-off values to determine which type of ADC values can be associated with significant survival benefits. Different survival indicators were analyzed, including overall survival (OS) and progression-free survival (PFS). Ten studies with a total of 782 patients with recurrent glioblastoma were included. The focused outcomes were OS and PFS. Our results showed that ADC values lower than the cut-off values were associated with significant benefits for OS status compared with ADC values higher than the cut-off values. Similar significant benefits were observed for PFS. The meta-analysis results suggest that ADC values lower than the cut-off values might be associated with significant benefits for OS and PFS when compared with ADC values higher than the cut-off values. However, bias in relation to the different stages of recurrent glioblastoma and different types, doses, and regimens of bevacizumab should not be ignored.

Apparent diffusion coefficient in intrahepatic cholangiocarcinoma diffusion-weighted magnetic resonance imaging noninvasively predicts Ki-67 expression

AIM

Tumor Ki-67 expression reflects prognosis and cancer grade, and biopsy-based preoperative assessment of Ki-67 expression is key to treatment. Apparent diffusion coefficient (ADC) values obtained with this imaging may noninvasively predict Ki-67 by reflecting tumor cell density and limited water molecule movement from irregular alignment. This study aimed to investigate the ability of ADC values to predict Ki-67 expression in intrahepatic cholangiocarcinoma (ICC).

METHOD

We retrospectively analyzed 39 cases of ICC confirmed by surgical pathology. All patients had undergone magnetic resonance imaging, and ADC values (mean, minimum, and maximum) were calculated. Ki-67 expression was assessed by immunohistochemistry, and patients were divided into groups of high (n = 18) and low (n = 21) Ki-67 expression. To assess the diagnostic performance of the ADC values for Ki-67 expression, we used the receiver operating characteristic curve and compared the areas under the curve (AUC).

RESULTS

The mean and minimum ADC values were significantly lower in the group with high Ki-67 expression. For predicting high Ki-67 expression, the AUC values were 0.701 for mean ADC, 0.818 for minimum ADC, and 0.571 for maximum ADC. The diagnostic sensitivity and specificity of the minimum ADC values were 88.9% and 76.2%, respectively. In addition, with ADC values combined, the AUC increased to 0.831. Apparent diffusion coefficient is a useful predictor of Ki-67 expression level in ICC.

CONCLUSION

Apparent diffusion coefficient values, especially minimum ADC values, can noninvasively predict ICC associated with high Ki-67 expression.

Diagnostic value of apparent diffusion coefficient of psoas muscles for evaluating complications in patients with Crohn's disease

Aim

To assess the association of the apparent diffusion coefficient (ADC) of the psoas muscles and psoas muscle index (PMI) with the activity and behaviour of Crohn's disease (CD).

Material and methods

This was a retrospective study of 88 CD patients who underwent magnetic resonance enterography. Patients were classified according to the Montreal Classification in uncomplicated (non-stricturing, non-penetrating, B1), and complicated (structuring [B2] and penetrating disease [B3]). At the level of the third lumbar vertebra, the ADC and PMI were estimated. CD activity was analysed using the Magnetic Resonance Index of Activity (MaRIA), and depending on its values patients were categorized as high or low activity. Additionally, the presence of creeping fat (CrF) was used to evaluate activity. ADC and PMI were using Student's t-test.

Results

Our study included 47 males and 41 females (mean age of 38.69 ±14.4 years). The ADC in uncomplicated (B1, n = 45) and complicated disease (B2 + B3, n = 43) were 1.11 ±0.19 and 1.03 ±0.10 (10-3*mm2/s), respectively, (p = 0.02). ADC was significantly lower in patients with stricturing disease than in patients without strictures (1.02 ±0.11 and 1.10 ±0.18 [10-3 mm2/s], respectively, p = 0.01). The group with non-penetrating disease showed higher PMI than those with penetrating disease (5.71 ±1.88 vs. 4.42 ±1.55 cm2/m2, respectively, p = 0.10). There was no significant difference in PMI and ADC between patients with low and high MaRIA or positive and negative CrF.

Conclusions

The ADC of the psoas muscles is significantly lower in CD patients with uncomplicated disease, particularly those with stricturing disease. Therefore, ADC can be considered as an imaging biomarker of myopathic changes in CD patients.

Learning ADC maps from accelerated radial k-space diffusion-weighted MRI in mice using a deep CNN-transformer model

PURPOSE

To accelerate radially sampled diffusion weighted spin-echo (Rad-DW-SE) acquisition method for generating high quality ADC maps.

METHODS

A deep learning method was developed to generate accurate ADC maps from accelerated DWI data acquired with the Rad-DW-SE method. The deep learning method integrates convolutional neural networks (CNNs) with vision transformers to generate high quality ADC maps from accelerated DWI data, regularized by a monoexponential ADC model fitting term. A model was trained on DWI data of 147 mice and evaluated on DWI data of 36 mice, with acceleration factors of 4× and 8× compared to the original acquisition parameters.

RESULTS

Ablation studies and experimental results have demonstrated that the proposed deep learning model generates higher quality ADC maps from accelerated DWI data than alternative deep learning methods under comparison when their performance is quantified in whole images as well as in regions of interest, including tumors, kidneys, and muscles.

CONCLUSIONS

The deep learning method with integrated CNNs and transformers provides an effective means to accurately compute ADC maps from accelerated DWI data acquired with the Rad-DW-SE method.

Quantitative MRI in the Local Staging of Prostate Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

Local staging of prostate cancer (PCa) is important for treatment planning. Radiologist interpretation using qualitative criteria is variable with high specificity but low sensitivity. Quantitative methods may be useful in the diagnosis of extracapsular extension (ECE).

PURPOSE

To assess the performance of quantitative MRI markers for detecting ECE.

STUDY TYPE

Systematic review and meta-analysis.

SUBJECTS

4800 patients from 28 studies with histopathologically confirmed PCa on radical prostatectomy were pooled for meta-analysis. Patients from 46 studies were included for systematic review.

FIELD STRENGTH/SEQUENCE

Diffusion-weighted, T2-weighted, and dynamic contrast-enhanced MRI at 1.5 T or 3 T.

ASSESSMENT

PubMed, Embase, Web of Science, Scopus, and Cochrane databases were searched to identify studies on diagnostic test accuracy or association of any quantitative MRI markers with ECE. Results extracted by two independent reviewers for tumor contact length (TCL) and mean apparent diffusion coefficient (ADC-mean) were pooled for meta-analysis, but not for other quantitative markers including radiomics due to low number of studies available.

STATISTICAL TESTS

Hierarchical summary receiver operating characteristic (HSROC) curves were computed for both TCL and ADC-mean, but summary operating points were computed for TCL only. Heterogeneity was investigated by meta-regression. Results were significant if P ≤ 0.05.

RESULTS

At the 10 mm threshold for TCL, summary sensitivity and specificity were 0.76 [95% confidence interval (CI) 0.71-0.81] and 0.68 [95% CI 0.63-0.73], respectively. At the 15 mm threshold, summary sensitivity and specificity were 0.70 [95% CI 0.53-0.83] and 0.74 [95% CI 0.60-0.84] respectively. The area under the HSROC curves for TCL and ADC-mean were 0.79 and 0.78, respectively. Significant sources of heterogeneity for TCL included timing of MRI relative to biopsy.

DATA CONCLUSION

Both 10 mm and 15 mm thresholds for TCL may be reasonable for clinical use. From comparison of the HSROC curves, ADC-mean may be superior to TCL at higher sensitivities.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

Efficiency and Accuracy Evaluation of Multiple Diffusion-Weighted MRI Techniques Across Different Scanners

BACKGROUND

The choice between different diffusion-weighted imaging (DWI) techniques is difficult as each comes with tradeoffs for efficient clinical routine imaging and apparent diffusion coefficient (ADC) accuracy.

PURPOSE

To quantify signal-to-noise-ratio (SNR) efficiency, ADC accuracy, artifacts, and distortions for different DWI acquisition techniques, coils, and scanners.

STUDY TYPE

Phantom, in vivo intraindividual biomarker accuracy between DWI techniques and independent ratings.

POPULATION/PHANTOMS

NIST diffusion phantom. 51 Patients: 40 with prostate cancer and 11 with head-and-neck cancer at 1.5 T FIELD STRENGTH/SEQUENCE: Echo planar imaging (EPI): 1.5 T and 3 T Siemens; 3 T Philips. Distortion-reducing: RESOLVE (1.5 and 3 T Siemens); Turbo Spin Echo (TSE)-SPLICE (3 T Philips). Small field-of-view (FOV): ZoomitPro (1.5 T Siemens); IRIS (3 T Philips). Head-and-neck and flexible coils.

ASSESSMENT

SNR Efficiency, geometrical distortions, and susceptibility artifacts were quantified for different b-values in a phantom. ADC accuracy/agreement was quantified in phantom and for 51 patients. In vivo image quality was independently rated by four experts.

STATISTICAL TESTS

QIBA methodology for accuracy: trueness, repeatability, reproducibility, Bland-Altman 95% Limits-of-Agreement (LOA) for ADC. Wilcoxon Signed-Rank and student tests on P < 0.05 level.

RESULTS

The ZoomitPro small FOV sequence improved b-image efficiency by 8%-14%, reduced artifacts and observer scoring for most raters at the cost of smaller FOV compared to EPI. The TSE-SPLICE technique reduced artifacts almost completely at a 24% efficiency cost compared to EPI for b-values ≤500 sec/mm2 . Phantom ADC 95% LOA trueness were within ±0.03 × 10-3  mm2 /sec except for small FOV IRIS. The in vivo ADC agreement between techniques, however, resulted in 95% LOAs in the order of ±0.3 × 10-3  mm2 /sec with up to 0.2 × 10-3  mm2 /sec of bias.

DATA CONCLUSION

ZoomitPro for Siemens and TSE SPLICE for Philips resulted in a trade-off between efficiency and artifacts. Phantom ADC quality control largely underestimated in vivo accuracy: significant ADC bias and variability was found between techniques in vivo.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

Discrimination of benign, atypical, and malignant peripheral nerve sheath tumors in neurofibromatosis type 1 using diffusion-weighted MRI

Background

Neurofibromatosis type 1 (NF1) is associated with the development of benign (BPNST) and malignant (MPNST) peripheral nerve sheath tumors. Recently described atypical neurofibromas (ANF) are considered pre-malignant precursor lesions to MPNSTs. Previous studies indicate that diffusion-weighted magnetic resonance imaging (DW-MRI) can reliably discriminate MPNSTs from BPNSTs. We therefore investigated the diagnostic accuracy of DW-MRI for the discrimination of benign, atypical, and malignant peripheral nerve sheath tumors.

Methods

In this prospective explorative single-center phase II diagnostic study, 44 NF1 patients (23 male; 30.1 ± 11.8 years) underwent DW-MRI (b-values 0-800 s/mm²) at 3T. Two radiologists independently assessed mean and minimum apparent diffusion coefficients (ADCmean/min) in areas of largest tumor diameters and ADCdark in areas of lowest signal intensity by manual contouring of the tumor margins of 60 BPNSTs, 13 ANFs, and 21 MPNSTs. Follow-up of ≥ 24 months (BPNSTs) or histopathological evaluation (ANFs + MPNSTs) served as diagnostic reference standard. Diagnostic ADC-based cut-off values for discrimination of the three tumor groups were chosen to yield the highest possible specificity while maintaining a clinically acceptable sensitivity.

Results

ADC values of pre-malignant ANFs clustered between BPNSTs and MPNSTs. Best BPNST vs. ANF + MPNST discrimination was obtained using ADCdark at a cut-off value of 1.6 × 10-3 mm2/s (85.3% sensitivity, 93.3% specificity), corresponding to an AUC of 94.3% (95% confidence interval: 85.2-98.0). Regarding BPNST + ANF vs. MPNST, best discrimination was obtained using an ADCdark cut-off value of 1.4 × 10-3 mm2/s (83.3% sensitivity, 94.5% specificity).

Conclusions

DW-MRI using ADCdark allows specific and noninvasive discrimination of benign, atypical, and malignant nerve sheath tumors in NF1.

Clinical value of conventional magnetic resonance imaging combined with diffusion-weighted imaging in predicting pelvic lymph node metastasis of cervical cancer

Background

In cervical cancer (CC), the involvement of pelvis lymph nodes is a crucial factor for patients' outcome. We aimed to investigate the value of conventional magnetic resonance imaging (MRI) combined with diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) in predicting CC pelvic lymph node metastasis (PLNM).

Methods

This retrospective study included CC patients who received surgical treatments. Surgical pathology results served as the gold standard for investigating the diagnostic performance of conventional MRI combined with DWI. We analyzed the association between tumor ADC and PLNM, as well as other pathological factors. The areas under the receiver operating characteristic curves (AUCs) for ADC in assessing PLNM and pathological factors were evaluated, and optimal cut-off points were obtained.

Results

A total of 261 CC patients were analyzed. PLNM patients had significantly lower tumor ADC (0.829 ± 0.144×10-3mm2/s vs. 1.064 ± 0.345×10-3mm2/s, p<0.0001), than non-PLNM CC. The agreement between conventional MRI combined with DWI and pathological results on PLNM diagnosis was substantial (Kappa=0.7031, p<0.0001), with 76% sensitivity, 94.31% specificity, and 90.8% accuracy. The AUC of tumor ADC was 0.703, and the optimal cut-off was 0.95×10-3 mm2/s. In multivariate analysis model 1, tumor ADC<0.95×10-3mm2/s was significantly associated with PLNM (OR, 2.83; 95%CI, 1.08-7.43; p= 0.0346) after adjusting for age and pathological risk factors. In multivariate analysis model 2, tumor ADC<0.95×10-3mm2/s (OR, 4.00; 95%CI, 1.61-9.89; p=0.0027), age<35 years old (OR, 2.93; 95%CI, 1.04-8.30; p=0.0428), increased tumor diameter on MRI (OR, 2.17; 95%CI, 1.18-3.99; p=0.0128), vaginal vault involvement on MRI (OR, 2; 95%CI, 1.002-3.99; p=0.0494) were independent predictors for PLNM. Tumor ADC<0.95×10-3mm2/s was significantly associated with higher risk of tumor diameter ≥4cm (OR, 2.60; 95%CI, 1.43-4.73; p=0.0017), muscular layer infiltration >1/2 (OR, 5.46; 95%CI, 3.19-9.34; p<0.0001), vaginal vault involvement (OR, 2.25; 95%CI, 1.28-3.96; p=0.0051), and lymphovascular space involvement (OR, 3.81; 95%CI, 2.19-6.63; p<0.0001).

Conclusion

Conventional MRI combined with DWI had a good diagnostic performance in detecting PLNM. The tumor ADC value in PLNM patients was significantly lower than that in non-PLNM patients. Tumor ADC <0.95×10-3mm2/s, age <35 years old, increased tumor diameter on MRI, vaginal vault involvement on MRI were independent predictors for PLNM.

Diffusion-Weighted MR Imaging of the Thymus in Children with Non-Thymic Neoplasms

Purpose: To investigate the diffusion-weighted imaging (DWI) findings and apparent diffusion coefficient (ADC) value of the thymus in children under the age of 13 who have non-thymic neoplasms. Materials and Methods: From January 2021 to April 2023, a single-center retrospective study analyzed consecutive 191 thoracic MRI scans with DWI from 67 children (<13 years) with non-thymic neoplasms. The scans were categorized based on the presence of restricted diffusion on DWI. We analyzed the demographics, laboratory data, and MR findings of the thymus. Statistical differences were assessed using generalized estimating equations. Results: Forty-five percent (86/191) of the scans exhibited restricted diffusion in the thymus: multifocal (n = 65; 76%), focal (n = 19; 22%), and diffuse (n = 2; 2%) patterns. The restricted diffusion group demonstrated higher absolute lymphocyte counts, more prominent thymus sizes, and higher frequency of off-treatment status compared to the unrestricted diffusion group (p>0.05). The mean ADC value across all 191 scans was 1.80 × 10-3 mm2/s. No significant difference was observed in the ADC value related to restricted diffusion patterns, the MRI vendors, or the age at the time of the scan. Conclusions: Restricted diffusion was observed in 45% of the thymus in children with non-thymic neoplasms, with a mean ADC value of 1.80 × 10-3 mm2/s. Recognizing the DWI findings can prevent unnecessary invasive procedures, alleviating concerns for patients and families.

ADC histogram parameters differentiating atypical from transitional meningiomas: correlation with Ki-67 proliferation index

BACKGROUND

Preoperative differentiation of atypical meningioma (AtM) from transitional meningioma (TrM) is critical to clinical treatment.

PURPOSE

To investigate the role of apparent diffusion coefficient (ADC) histogram analysis in differentiating AtM from TrM and its correlation with the Ki-67 proliferation index (PI).

METHODS

Clinical, imaging, and pathological data of 78 AtM and 80 TrM were retrospectively collected. Regions of interest (ROIs) were delineated on axial ADC images using MaZda software and histogram parameters (mean, variance, skewness, kurtosis, 1st percentile [ADCp1], 10th percentile [ADCp10], 50th percentile [ADCp50], 90th percentile [ADCp90], and 99th percentile [ADCp99]) were generated. The Mann-Whitney U test was used to compare the differences in histogram parameters between the two groups; receiver operating characteristic (ROC) curves were used to assess diagnostic efficacy in differentiating AtM from TrM preoperatively. The correlation between histogram parameters and Ki-67 PI was analyzed.

RESULTS

All histogram parameters of AtM were lower than those of TrM, and the variance, skewness, kurtosis, ADCp90, and ADCp99 were significantly different (P < 0.05). Combined ADC histogram parameters (variance, skewness, kurtosis, ADCp90, and ADCp99) achieved the best diagnostic performance for distinguishing AtM from TrM. Area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 0.800%, 76.25%, 67.95%, 70.15%, 70.93%, and 73.61%, respectively. All histogram parameters were negatively correlated with Ki-67 PI (r = -0.012 to -0.293).

CONCLUSION

ADC histogram analysis is a potential tool for non-invasive differentiation of AtM from TrM preoperatively, and ADC histogram parameters were negatively correlated with the Ki-67 PI.

The Role of Diffusion-Weighted Imaging in the Evaluation of Treatment of Newly Diagnosed Type 2 Diabetic Patients

INTRODUCTION

To compare the pre and post-treatment pancreatic apparent diffusion coefficient (ADC) values of type II diabetes patients with control subjects, and also to evaluate its effectiveness in evaluating the response to treatment.

METHODS

The study included 35 newly diagnosed type 2 diabetic patients and 35 non-diabetic participants, matched for sex and age. Insulin and metformin treatment was given to the patients. Abdominal diffusion-weighted MR imaging was performed before and after the treatment. ADCs of the control group and patients pre and post-treatment were compared. In addition, the clinical parameters of the patients related to diabetes were recorded.

RESULTS

There was a significant difference between the median pancreatic ADC values of the patients pre and post-treatment. While there was a significant difference between the median pancreatic ADC values of the patient and the control groups before the treatment, no significant difference after the treatment was observed. There was a positive correlation between mean pancreatic ADC values and age, as well as a negative correlation with Hb1Ac level and eGFR.

CONCLUSION

Pancreatic ADC values of newly diagnosed type II diabetes patients can be used as a marker of pancreatic function in the evaluation of response to treatment and clinical decisions.

Apparent diffusion coefficient measurements of bone marrow infiltration patterns in multiple myeloma for the assessment of tumor burden - a feasibility study

BACKGROUND

The purpose of our study was to explore and compare the tumor burden of different bone marrow infiltration patterns and evaluate the feasibility of apparent diffusion coefficient (ADC) value to identify patterns in multiple myeloma (MM).

PATIENTS AND METHODS

Ninety-three patients with newly diagnosed multiple myeloma and 23 controls had undergone routine magnetic resonance imaging (MRI) and diffusion-weighted MRI (DWI) from January 2019 to November 2020. Five bone marrow (BM) infiltration patterns were allocated according to routine MRI. The laboratory data and ADC values of patterns were analyzed and compared. ROC analysis was used to establish the best diagnostic ADC threshold value for identifying these patterns and distinguishing normal pattern from controls. Besides, the correlation between the ADC values of diffuse pattern and the plasma cells ratio was assessed.

RESULTS

The values of hemoglobin, beta-2 microglobulin (β2-MG), plasma cell, M protein, the percentages of stage, high-risk fluorescence in situ hybridization, and ADC values showed significant difference among patterns. ADCmean at a specific value (368.5×10-6 mm2/s) yielded a maximum specificity (95.5%) and sensitivity (92.0%) in diagnosing MM. A specific value (335.5×10-6mm2/s) yielded a maximum specificity (84.7%) and sensitivity (88.0%) in discriminating visually normal pattern in MM from controls. There was a moderate positive correlation between the plasma cells ratio and ADCs of diffuse infiltration patterns (r = 0.648, P < 0.001).

CONCLUSIONS

The bone marrow infiltration patterns in MM patients can indicate the tumor burden and ADC value has the ability to discriminate these patterns objectively.

Regional ADC values of the morphologically normal canine brain

Introduction

Diffusion-weighted magnetic resonance imaging is increasingly available for investigation of canine brain diseases. Apparent diffusion coefficient (ADC) of normal canine brains is reported only in small numbers of subjects. The aim of the study was to investigate the ADC of different anatomical regions in the morphologically normal brain in a large population of canine patients in clinical setting. Additionally, possible influence on the ADC value of patient-related factors like sex, age and body weight, difference between the left and right side of the cerebral hemispheres, and between gray and white matter were investigated.

Methods

Brain magnetic resonance studies including diffusion-weighted images of dogs presented at the Vetsuisse Faculty-University Zurich between 2015 and 2020 were reviewed retrospectively. Only morphologically normal brain magnetic resonance studies of dogs presented with neurological signs or non-neurological signs were included. Apparent diffusion coefficient values of 12 regions of interest (ROIs) in each hemisphere and an additional region in the cerebellar vermis were examined in each dog.

Results

A total of 321 dogs (including 247 dogs with neurological signs and 62 dogs with non-neurological signs) of various breeds, sex and age were included. Apparent diffusion coefficient significantly varied among most anatomical brain regions. A significantly higher ADC was measured in the gray [median 0.79 (range 0.69-0.90) × 10-3 mm2/s] compared to the white matter [median 0.70 (range 0.63-0.85) × 10-3 mm2/s]. No significant differences were found between the left and right cerebral hemispheres in most of the regions, neither between sexes, different reproductive status, and not consistently between body weight groups. Age was correlated first with a decrease from dogs <1 year of age to middle-age (⩾3 to <8 years) dogs and later with an increase of ADC values in dogs ⩾8 years.

Discussion

Apparent diffusion coefficient values of 25 ROIs were described in 321 morphologically normal canine brains in clinical setting. Apparent diffusion coefficient differences depending on the brain anatomical region are present. Apparent diffusion coefficient differences among age classes are present, likely consistent with brain maturation and aging. The described data can be a reference for future studies in clinical settings on the canine brain.

Feasibility of quantitative diffusion-weighted imaging during intra-procedural MRI-guided brachytherapy of locally advanced cervical and vaginal cancers

PURPOSE

To determine the feasibility of quantitative apparent diffusion coefficient (ADC) acquisition during magnetic resonance imaging-guided brachytherapy (MRgBT) using reduced field-of-view (rFOV) diffusion-weighted imaging (DWI).

METHODS AND MATERIALS

T2-weighted (T2w) MR and full-FOV single-shot echo planar (ssEPI) DWI were acquired in 7 patients with cervical or vaginal malignancy at baseline and prior to brachytherapy, while rFOV-DWI was acquired during MRgBT following brachytherapy applicator placement. The gross target volume (GTV) was contoured on the T2w images and registered to the ADC map. Voxels at the GTV's maximum Maurer distance comprised a central sub-volume (GTVcenter). Contour ADC mean and standard deviation were compared between timepoints using repeated measures ANOVA.

RESULTS

ssEPI-DWI mean ADC increased between baseline and prebrachytherapy from 1.03 ± 0.18 10-3 mm2/s to 1.34 ± 0.28 10-3 mm2/s for the GTV (p = 0.06) and from 0.84 ± 0.13 10-3 mm2/s to 1.26 ± 0.25 10-3 mm2/s at the level of the GTVcenter (p = 0.03), consistent with early treatment response. rFOV-DWI during MRgBT demonstrated mean ADC values of 1.28 ± 0.14 10-3 mm2/s and 1.28 ± 0.19 10-3 mm2/s for the GTV and GTVcenter, respectively (p = 0.02 and p = 0.03 relative to baseline). No significant differences were observed between ssEPI-DWI and rFOV-DWI ADC measurements.

CONCLUSIONS

Quantitative ADC measurement in the setting of MRI guided brachytherapy implant placement for cervical and vaginal cancers is feasible using rFOV-DWI, with comparable mean ADC comparable to prebrachytherapy ssEPI-DWI, and may enable MRI-guided radiotherapy targeting of low ADC, radiation resistant sub-volumes of tumor.

Potential Antihuman Epidermal Growth Factor Receptor 2 Target Therapy Beneficiaries: The Role of MRI-Based Radiomics in Distinguishing Human Epidermal Growth Factor Receptor 2-Low Status of Breast Cancer

BACKGROUND

Multiparametric MRI radiomics could distinguish human epidermal growth factor receptor 2 (HER2)-positive from HER2-negative breast cancers. However, its value for further distinguishing HER2-low from HER2-negative breast cancers has not been investigated.

PURPOSE

To investigate whether multiparametric MRI-based radiomics can distinguish HER2-positive from HER2-negative breast cancers (task 1) and HER2-low from HER2-negative breast cancers (task 2).

STUDY TYPE

Retrospective.

POPULATION

Task 1: 310 operable breast cancer patients from center 1 (97 HER2-positive and 213 HER2-negative); task 2: 213 HER2-negative patients (108 HER2-low and 105 HER2-zero); 59 patients from center 2 (16 HER2-positive, 27 HER2-low and 16 HER2-zero) for external validation.

FIELD STRENGTH/SEQUENCE

A 3.0 T/T1-weighted contrast-enhanced imaging (T1CE), diffusion-weighted imaging (DWI)-derived apparent diffusion coefficient (ADC).

ASSESSMENT

Patients in center 1 were assigned to a training and internal validation cohort at a 2:1 ratio. Intratumoral and peritumoral features were extracted from T1CE and ADC. After dimensionality reduction, the radiomics signatures (RS) of two tasks were developed using features from T1CE (RS-T1CE), ADC (RS-ADC) alone and T1CE + ADC combination (RS-Com).

STATISTICAL TESTS

Mann-Whitney U tests, the least absolute shrinkage and selection operator, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

RESULTS

For task 1, RS-ADC yielded higher area under the ROC curve (AUC) in the training, internal, and external validation of 0.767/0.725/0.746 than RS-T1CE (AUC = 0.733/0.674/0.641). For task 2, RS-T1CE yielded higher AUC of 0.765/0.755/0.678 than RS-ADC (AUC = 0.706/0.608/0.630). For both of task 1 and task 2, RS-Com achieved the best performance with AUC of 0.793/0.778/0.760 and 0.820/0.776/0.711, respectively, and obtained higher clinical benefit in DCA compared with RS-T1CE and RS-ADC. The calibration curves of all RS demonstrated a good fitness.

DATA CONCLUSION

Multiparametric MRI radiomics could noninvasively and robustly distinguish HER2-positive from HER2-negative breast cancers and further distinguish HER2-low from HER2-negative breast cancers.

EVIDENCE LEVEL

3.

TECHNICAL EFFICACY

Stage 2.

High-resolution Diffusion-weighted Imaging of the Prostate Using Multiplexed Sensitivity-encoding: Comparison with the Conventional and Reduced Field-of-view Techniques

PURPOSE

To compare objective and subjective image quality, lesion conspicuity, and apparent diffusion coefficient (ADC) of high-resolution multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) with conventional DWI (c-DWI) and reduced FOV DWI (rFOV-DWI) in prostate MRI.

METHODS

Forty-seven patients who underwent prostate MRI, including c-DWI, rFOV-DWI, and MUSE-DWI, were retrospectively evaluated. SNR and ADC of normal prostate tissue and contrast-to-noise ratio (CNR) and ADC of prostate cancer (PCa) were measured and compared between the three sequences. Image quality and lesion conspicuity were independently graded by two radiologists using a 5-point scale and compared between the three sequences.

RESULTS

The SNR of normal prostate tissue was significantly higher with rFOV-DWI than with the other two DWI techniques (P ≤ 0.01). The CNR of the PCa was significantly higher with rFOV-DWI than with MUSE-DWI (P < 0.05). The ADC of normal prostate tissue measured by rFOV-DWI was lower than that measured by MUSE-DWI and c-DWI (P < 0.01), while there was no difference in the ADC of cancers. In the qualitative analysis, MUSE-DWI showed significantly higher scores than rFOV-DWI and c-DWI for visibility of anatomy and overall image quality in both readers, and significantly higher scores for distortion in one of the two readers (P < 0.001). There was no difference in lesion conspicuity between the three sequences.

CONCLUSION

High-resolution MUSE-DWI showed higher image quality and reduced distortion compared to c-DWI, while maintaining a wide FOV and similar ADC quantification, although no difference in lesion conspicuity was observed.

Apparent Diffusion Coefficient Metrics to Differentiate between Treatment-Related Abnormalities and Tumor Progression in Post-Treatment Glioblastoma Patients: A Retrospective Study

Distinguishing treatment-related abnormalities (TRA) from tumor progression (TP) in glioblastoma patients is a diagnostic imaging challenge due to the identical morphology of conventional MR imaging sequences. Diffusion-weighted imaging (DWI) and its derived images of the apparent diffusion coefficient (ADC) have been suggested as diagnostic tools for this problem. The aim of this study is to determine the diagnostic accuracy of different cut-off values of the ADC to differentiate between TP and TRA. In total, 76 post-treatment glioblastoma patients with new contrast-enhancing lesions were selected. Lesions were segmented using a T1-weighted, contrast-enhanced scan. The mean ADC values of the segmentations were compared between TRA and TP groups. Diagnostic accuracy was compared by use of the area under the curve (AUC) and the derived sensitivity and specificity values from cutoff points. Although ADC values in TP (mean = 1.32 × 10-3 mm2/s; SD = 0.31 × 10-3 mm2/s) were significantly different compared to TRA (mean = 1.53 × 10-3 mm2/s; SD = 0.28 × 10-3 mm2/s) (p = 0.003), considerable overlap in their distributions exists. The AUC of ADC values to distinguish TP from TRA was 0.71, with a sensitivity and specificity of 65% and 70%, respectively, at an ADC value of 1.47 × 10-3 mm2/s. These findings therefore indicate that ADC maps should not be used in discerning between TP and TRA at a certain timepoint without information on temporal evolution.

Feasibility of Accelerated Prostate Diffusion-Weighted Imaging on 0.55 T MRI Enabled With Random Matrix Theory Denoising

INTRODUCTION

Prostate cancer diffusion weighted imaging (DWI) MRI is typically performed at high-field strength (3.0 T) in order to overcome low signal-to-noise ratio (SNR). In this study, we demonstrate the feasibility of prostate DWI at low field enabled by random matrix theory (RMT)-based denoising, relying on the MP-PCA algorithm applied during image reconstruction from multiple coils.

METHODS

Twenty-one volunteers and 2 prostate cancer patients were imaged with a 6-channel pelvic surface array coil and an 18-channel spine array on a prototype 0.55 T system created by ramping down a commercial magnetic resonance imaging system (1.5 T MAGNETOM Aera Siemens Healthcare) with 45 mT/m gradients and 200 T/m/s slew rate. Diffusion-weighted images were acquired with 4 non-collinear directions, for which b = 50 s/mm 2 was used with 8 averages and b = 1000 s/mm 2 with 40 averages; 2 extra b = 50 s/mm 2 were used as part of the dynamic field correction. Standard and RMT-based reconstructions were applied on DWI over different ranges of averages. Accuracy/precision was evaluated using the apparent diffusion coefficient (ADC), and image quality was evaluated over 5 separate reconstructions by 3 radiologists with a 5-point Likert scale. For the 2 patients, we compare image quality and lesion visibility of the RMT reconstruction versus the standard one on 0.55 T and on clinical 3.0 T.

RESULTS

The RMT-based reconstruction in this study reduces the noise floor by a factor of 5.8, thereby alleviating the bias on prostate ADC. Moreover, the precision of the ADC in prostate tissue after RMT increases over a range of 30%-130%, with the increase in both signal-to-noise ratio and precision being more prominent for a low number of averages. Raters found that the images were consistently of moderate to good overall quality (3-4 on the Likert scale). Moreover, they determined that b = 1000 s/mm 2 images from a 1:55-minute scan with the RMT-based reconstruction were on par with the corresponding images from a 14:20-minute scan with standard reconstruction. Prostate cancer was visible on ADC and calculated b = 1500 images even with the abbreviated 1:55-minute scan reconstructed with RMT.

CONCLUSIONS

Prostate imaging using DWI is feasible at low field and can be performed more rapidly with noninferior image quality compared with standard reconstruction.

Synthetic MRI plus FSE-PROPELLER DWI for differentiating malignant from benign head and neck tumors: a preliminary study

Background

Preoperative classification of head and neck (HN) tumors remains challenging, especially distinguishing early cancerogenic masses from benign lesions. Synthetic MRI offers a new way for quantitative analysis of tumors. The present study investigated the application of synthetic MRI and stimulus and fast spin echo diffusion-weighted imaging with periodically rotated overlapping parallel lines with enhanced reconstruction (FSE-PROPELLER DWI) to differentiate malignant from benign HN tumors.

Materials and methods

Forty-eight patients with pathologically confirmed HN tumors were retrospectively recruited between August 2022 and October 2022. The patients were divided into malignant (n = 28) and benign (n = 20) groups. All patients were scanned using synthetic MRI and FSE-PROPELLER DWI. T1, T2, and proton density (PD) values were acquired on the synthetic MRI and ADC values on the FSE-PROPELLER DWI.

Results

Benign tumors (ADC: 2.03 ± 0.31 × 10-3 mm2/s, T1: 1741.13 ± 662.64 ms, T2: 157.43 ± 72.23 ms) showed higher ADC, T1, and T2 values compared to malignant tumors (ADC: 1.46 ± 0.37 × 10-3 mm2/s, T1: 1390.06 ± 241.09 ms, T2: 97.64 ± 14.91 ms) (all P<0.05), while no differences were seen for PD values. ROC analysis showed that T2+ADC (cut-off value, > 0.55; AUC, 0.950) had optimal diagnostic performance vs. T1 (cut-off value, ≤ 1675.84 ms; AUC, 0.698), T2 (cut-off value, ≤ 113.24 ms; AUC, 0.855) and PD (cut off value, > 80.67 pu; AUC, 0.568) alone in differentiating malignant from benign lesions (all P<0.05); yet, the difference in AUC between ADC and T2+ADC or T2 did not reach statistical significance.

Conclusion

Synthetic MRI and FSE-PROPELLER DWI can quantitatively differentiate malignant from benign HN tumors. T2 value is comparable to ADC value, and T2+ADC values could improve diagnostic efficacy., apparent diffusion coeffificient, head and neck tumors.

Arterial spin labeling image findings in the acute phase in paediatric patients with acute encephalopathy with biphasic seizures and late reduced diffusion

Introduction

Diagnosing acute encephalopathy with biphasic seizures and late reduced diffusion (AESD) after the first seizure (early seizure/seizures, ES/ESs) is challenging because a reduced apparent diffusion coefficient (ADC) in the cortical or subcortical white matter, often described as having a "bright-tree appearance (BTA)," is usually not observed until secondary seizures (late seizures, LSs) occur. Previous studies have reported hypoperfusion on arterial spin labeling (ASL) within 24 h after ES/ESs in patients with AESD and hyperperfusion within 24 h after LS onset. This study aimed to investigate cerebral blood flow in the hyperacute phase (between ES/ESs and LSs) using ASL in patients with AESD.

Methods

Eight ASL images were acquired in six patients with AESD admitted to our hospital from October 2021 to October 2022. ASL findings in the hyperacute phase were investigated and video-electroencephalogram findings obtained around ASL image acquisition in the hyperacute phase were evaluated.

Results

Four ASL images were obtained for three patients before LS onset, with three images showing hyperperfusion areas and one image showing hypoperfusion areas. These hyperperfuion regions coincided with BTA on subsequent images of these patients.In one patient, the first ASL image was obtained in the late hyperacute phase and revealed hyperperfusion areas with a slightly abnormal change on diffusion-weighted image (DWI), which were not accompanied by ADC abnormalities. The second ASL image obtained 51 h after the first ASL, and before LS onset revealed more prominent hyperperfusion areas than the first ASL image, which were accompanied by BTA. In another patient, the ASL image obtained 82 h after ES revealed hyperperfusion areas without abnormal change on DWI or ADC.

Conclusion

This study revealed that two patients exhibited hyperperfusion regions and another patient exhibited hypoperfusion regions among three patients who underwent ASL imaging during the period from 24 h after ES/ESs to LSs in patients with LSs or cooling initiation in patients without LSs due to early anaesthesia induction (late hyperacute phase). Further prospective studies on cerebral blood flow are required to explore the relationship among the timing of image acquisition, the presence of electrographic seizures, and ASL findings in patients with AESD.

Volumetric apparent diffusion coefficient (ADC) histogram analysis of the brain in paediatric patients with hypoxic ischaemic encephalopathy

Purpose

To evaluate the whole brain, hippocampus, thalamus, and lentiform nucleus by volumetric apparent diffusion coefficient (ADC) histogram analysis in paediatric patients with hypoxic-ischaemic encephalopathy (HIE).

Material and methods

This retrospective study included 25 patients with HIE and 50 patients as the control group. Diffusion-weighted imaging was obtained at b-values of 1000 mm2/s. The histogram parameters of ADC values, including the mean, minimum, maximum, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles, as well as skewness, kurtosis, and variance were determined. The interclass correlation coefficient (ICC) was used to assess the inter-observer agreement.

Results

ADCmin, ADCmean, and ADCmax, as well as the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC values for the HIE group were all lower than those of the control group (p < 0.001) in the volumetric histogram analysis of the hippocampus, thalamus, and lentiform nucleus. In the whole-brain histogram analysis, ADC min, and the 50th and 75th percentiles of ADC values did not differ significantly, while other parameters were lower in the HIE group. The ROC curve revealed that the ADC histogram parameters of the hippocampus provided the most accurate results for the diagnosis of HIE. The area under the curve (AUC) of the 95th percentile of ADC values was the highest (AUC = 0.915; cut-off 1.262 × 10-3 mm2/s; sensitivity 88% and specificity 84%).

Conclusions

Volumetric ADC histogram analysis of the whole brain, hippocampus, thalamus, and lentiform nucleus with b-values of 1000 mm2/s can serve as an imaging marker for determining HIE.

Development and validation of apparent diffusion coefficient histogram-based nomogram for predicting malignant transformation of sinonasal inverted papilloma

OBJECTIVES

To develop and validate a nomogram based on whole-tumour histograms of apparent diffusion coefficient (ADC) maps for predicting malignant transformation (MT) in sinonasal inverted papilloma (IP).

METHODS

This retrospective study included 209 sinonasal IPs with and without MT, which were assigned into a primary cohort (n = 140) and a validation cohort (n = 69). Eight ADC histogram features were extracted from the whole-tumour region of interest. Morphological MRI features and ADC histogram parameters were compared between the two groups (with and without MT). Stepwise logistic regression was used to identify independent predictors and to construct models. The predictive performances of variables and models were assessed using the area under the curve (AUC). The optimal model was presented as a nomogram, and its calibration was assessed.

RESULTS

Four morphological features and seven ADC histogram parameters showed significant differences between the two groups in both cohorts (all p < 0.05). Maximum diameter, loss of convoluted cerebriform pattern, ADC10th and ADCSkewness were identified as independent predictors to construct the nomogram. The nomogram showed significantly better performance than the morphological model in both the primary (AUC, 0.96 vs 0.88; p = 0.006) and validation (AUC, 0.96 vs 0.88; p = 0.015) cohorts. The nomogram showed good calibration in both cohorts. Decision curve analysis demonstrated that the nomogram is clinically useful.

CONCLUSIONS

The developed nomogram, which incorporates morphological MRI features and ADC histogram parameters, can be conveniently used to facilitate the pre-operative prediction of MT in IPs.

Microstructural alterations in hypoxia-related BRAIN centers after COVID-19 by using DTI: A preliminary study

PURPOSE

To investigate whether the diffusion tensor imaging (DTI) parameters alterations in the in hypoxia-related neuroanatomical localizations in patients after COVID-19. Additionally, the relationship between DTI findings and the clinical severity of the disease is evaluated.

METHODS

The patients with COVID-19 were classified into group 1 (total patients, n = 74), group 2 (outpatient, n = 46), and group 3 (inpatient, n = 28) and control (n = 52). Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were calculated from the bulbus, pons, thalamus, caudate nucleus, globus pallidum, putamen, and hippocampus. DTI parameters were compared between groups. Oxygen saturation, D dimer and lactate dehydrogenase (LDH) values associated with hypoxia were analyzed in inpatient group. Laboratory findings were correlated with ADC and FA values.

RESULTS

Increased ADC values in the thalamus, bulbus and pons were found in group 1 compared to control. Increased FA values in the thalamus, bulbus, globus pallidum and putamen were detected in group 1 compared to control. The FA and ADC values obtained from putamen were higher in group 3 compared to group 2. There was a negative correlation between basal ganglia and hippocampus FA values and plasma LDH values. The ADC values obtained from caudate nucleus were positively correlated with plasma D Dimer values.

CONCLUSION

ADC and FA changes may reveal hypoxia-related microstructural damage after COVID-19 infection. We speculated that the brainstem and basal ganglia can affected during the subacute period.

MRI Evaluation of Rectal Cancer Lymph Node Staging Using Apparent Diffusion Coefficient

Introduction Colorectal cancer is the third most diagnosed cancer globally. Lymph node metastases significantly affect prognosis, emphasizing the importance of early detection and management. Despite significant advances in conventional MRI's role in staging, improvements in advanced functional imaging such as diffusion-weighted imaging (DWI) in identifying lymph node metastases persist. Objectives The aim is to evaluate the effectiveness of apparent diffusion coefficient (ADC) MRI in evaluating lymph node staging in rectal cancer. Patients and methods In a prospective study, 89 patients with stage II-III rectal cancer were grouped into two treatments: pre-operative FOLFOX4 chemotherapy and standard pre-operative chemoradiotherapy. All underwent 1.5T MRI, with T2-weighted and DWI sequences. A radiologist defined regions of interest on the tumor, lymph nodes, and intact rectal wall to calculate ADC values. Results Rectal cancer ADC's receiver operating characteristic curve had an area under the curve (AUC) of 0.688 (P < 0.001), with optimal ADC cutoff at 0.99 x 10-3 mm2/s (sensitivity: 75%, specificity: 83%). For lymph nodes, AUC was 0.508 (P < 0.001), with a cutoff of 0.9 x 10-3 mm2/s (sensitivity: 78%, specificity: 67%). No correlation between tumor and lymph node ADC values was observed. In chemotherapy patients, "healthy" inguinal lymph nodes had higher ADC values than affected ones pre-treatment (P = 0.001), a disparity fading post-treatment (P = 0.313). For chemoradiotherapy patients, the ADC difference persisted pre and post-treatment (P = 0.001). Conclusion The study of ADC-MRI showed different ADC values between tumors and lymph nodes and highlighted ADC differences between treatment groups. Notably, no correlation was observed between tumor and lymph node ADC values. However, differences were apparent when comparing "healthy" inguinal nodes with lymph nodes affected by cancer.

Evaluation of Imaging Findings of Pancreatobiliary and Intestinal Type Periampullary Carcinomas with 3.0T MRI

RATIONALE AND OBJECTIVES

The aim of this study was to differentiate pancreatobiliary and intestinal type periampullary carcinomas using dynamic contrast MRI and MRCP (Magnetic Resonance Cholangiopancreatography) with diffusion-weighted imaging (DWI) MATERIALS AND METHODS: MRI and MRCP images of 70 patients with pathologically proven periampullary adenocarcinoma were included. MRCP image features, extra-ampullary features, enhancement patterns, and apparent diffusion coefficient (ADC) values derived from b-values of 1000 s/mm² were evaluated by two radiologists independently. The interclass correlation coefficient (ICC) or Cohen's kappa statistic was used to evaluate the interobserver agreement.

RESULTS

51 patients were diagnosed with pancreatobiliary type carcinomas, and 19 with intestinal type. In the pancreatobiliary subtype, the distal wall of the common bile duct was usually irregular (p = 0.047). Although the progressive enhancement pattern was evident in the pancreatobiliary type, an oval filling defect in the distal common bile duct was found to be more common in the intestinal type (p<0.001). The pancreatic duct cut-off sign (p<0.001), gastroduodenal artery involvement (p <0,001), and lymphadenopathy (p<0.05) were mostly observed in pancreatobiliary carcinomas. The ADCmin, ADCmean, and ADCmax values of the pancreatobiliary type carcinomas were all lower compared to the intestinal type carcinomas (p <0.05).

CONCLUSION

The oval filling defect seen in MRI and MRCP examinations suggests intestinal type, whereas the progressive contrasting pattern of the masses with irregular narrowing in the distal margin of the common bile duct, the pancreatic duct cut-off sign, gastroduodenal artery involvement, lymphadenopathy, and low ADC values indicate pancreatobiliary type carcinomas.

Liver Imaging Reporting and Data System (LI-RADS) v2018: differential diagnostic value of ADC values for benign and malignant nodules with moderate probability (LR-3)

Objective

To evaluate the usefulness of the apparent diffusion coefficient (ADC) in differentiating between benign and malignant LR-3 lesions classified by Liver Imaging Reporting and Data System 2018 (LI-RADS v2018).

Methods

Retrospectively analyzed 88 patients with liver nodules confirmed by pathology and classified as LR-3 by LI-RADS. All patients underwent preoperative contrast-enhanced MR examination, and the following patient-related imaging features were collected: tumor size,nonrim APHE, nonperipheral "washout", enhancing "capsule", mild-moderate T2 hyperintensity, fat in mass, restricted diffusion, and nodule-in-nodule architecture. We performed ROC analysis and calculated the sensitivity and specificity.

Results

A total of 122 lesions were found in 88 patients, with 68 benign and 54 malignant lesions. The mean ADC value for malignant and benign lesions were 1.01 ± 0.15 × 103 mm2/s and 1.41 ± 0.31 × 103 mm2/s, respectively. The ADC value of malignant lesions was significantly lower than that of benign lesions, p < 0.0001. Compared with other imaging features, ADC values had the highest AUC (AUC = 0.909), with a sensitivity of 92.6% and a specificity of 74.1% for the differentiation of benign and malignant lesions.

Conclusions

ADC values are useful for differentiating between benign and malignant liver nodules in LR-3 classification, it improves the sensitivity of LI-RADS in the diagnosis of HCC while maintaining high specificity, and we recommend including ADC values in the standard interpretation of LI-RADSv2018.

Application of Dynamic Enhanced Magnetic Resonance Imaging Texture Analysis Combined with ADCs in Predicting Pelvic Lymph Metastasis of Prostate Cancer

OBJECTIVE

The application value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) texture analysis combined with apparent diffusion coefficient (ADC) in predicting pelvic lymph node metastasis of prostate cancer was explored.

METHODS

The clinical and imaging data of 151 patients with prostate cancer admitted to The Affiliated Tumor Hospital of Guizhou Medical University from November 2019 to November 2021 were retrospectively analysed. According to the final pathological diagnosis results, they were divided into two groups: Metastasis group (n = 63, pelvic lymph node metastasis) and non-metastasis group (n = 88, no pelvic lymph node metastasis). The DCE-MRI texture parameters and ADCs of the two groups were compared using Omni-Kinetics software and MADC software packages. The receiver operating characteristic (ROC) curve was used in evaluating the predictive value of each method and their combination, and Spearman rank correlation analysis was used in evaluating their correlation.

RESULTS

The volume transfer (Ktrans) and interstitium-to-plasmarate rate constant (Kep) in the metastatic group were significantly higher than those in the non-metastatic group (p < 0.001). However, no significant difference in extravascular extracellular space volume fraction (Ve) was found between the groups (p > 0.05). The ADC of the metastatic group was lower (p < 0.001). The Ktrans and Kep values were positively correlated with pelvic lymph node metastasis of prostate cancer (r = 0.580, 0.684; p < 0.001), and the ADC was negatively correlated with pelvic lymph node metastasis of prostate cancer (r = -0.478; p < 0.001). The ROC curve showed that the area under the curve (AUC) of DCE-MRI texture analysis parameters Ktrans and Kep combined with ADC was large, and the prediction efficiency increased. The AUC, sensitivity and specificity were 0.974, 95.20% and 93.20% (p < 0.001), respectively.

CONCLUSIONS

DCE-MRI texture analysis combined with ADC value can accurately predict pelvic lymphatic metastasis of prostate cancer, which is helpful for the selection and formulation of clinical treatment plans and has certain guiding value for the implementation of pelvic lymph node clearing in patients.

The usefulness of the apparent diffusion coefficient value in diagnosing acute spinal cord ischemia

The purpose of our study was to assess the usefulness of the apparent diffusion coefficient (ADC) value in differentiating between a normal spinal cord and a spinal cord with acute ischemia. Control group of 113 and 8 acute spinal cord ischemia patients were enrolled in this study. The ADC values were measured when diffusion-weighted imaging was first performed after the onset of acute spinal cord ischemia. The mean ADC value each of the control group and acute spinal cord ischemia patients was 0.99 ± 0.19 × 10-3 mm2/s and 0.70 ± 0.15 × 10-3 mm2/s. The mean ADC value in patients with acute spinal cord ischemia was significantly lower than that in patients with a normal spinal cord (P < 0.01). We found the cutoff ADC value (0.86 × 10-3 mm2/s) to be a useful indicator of acute spinal cord ischemia (sensitivity = 100.0%, specificity = 71.7%, AUC = 0.92). In conclusions, it is suggested that the ADC value may be useful in the diagnosis of acute spinal cord ischemia.

Automated acute ischemic stroke lesion delineation based on apparent diffusion coefficient thresholds

Purpose

Automated lesion segmentation is increasingly used in acute ischemic stroke magnetic resonance imaging (MRI). We explored in detail the performance of apparent diffusion coefficient (ADC) thresholding for delineating baseline diffusion-weighted imaging (DWI) lesions.

Methods

Retrospective, exploratory analysis of the prospective observational single-center 1000Plus study from September 2008 to June 2013 (clinicaltrials.org; NCT00715533). We built a fully automated lesion segmentation algorithm using a fixed ADC threshold (≤620 × 10-6 mm2/s) to delineate the baseline DWI lesion and analyzed its performance compared to manual assessments. Diagnostic capabilities of best possible ADC thresholds were investigated using receiver operating characteristic curves. Influential patient factors on ADC thresholding techniques' performance were studied by conducting multiple linear regression.

Results

108 acute ischemic stroke patients were selected for analysis. The median Dice coefficient for the algorithm was 0.43 (IQR 0.20-0.64). Mean ADC values in the DWI lesion (β = -0.68, p < 0.001) and DWI lesion volumes (β = 0.29, p < 0.001) predicted performance. Optimal individual ADC thresholds differed between subjects with a median of ≤691 × 10-6 mm2/s (IQR ≤660-750 × 10-6 mm2/s). Mean ADC values in the DWI lesion (β = -0.96, p < 0.001) and mean ADC values in the brain parenchyma (β = 0.24, p < 0.001) were associated with the performance of individual thresholds.

Conclusion

The performance of ADC thresholds for delineating acute stroke lesions varies substantially between patients. It is influenced by factors such as lesion size as well as lesion and parenchymal ADC values. Considering the inherent noisiness of ADC maps, ADC threshold-based automated delineation of very small lesions is not reliable.

Feasibility of accelerated T2 mapping for the preoperative assessment of endometrial carcinoma

Objective

The application value of T2 mapping in evaluating endometrial carcinoma (EMC) features remains unclear. The aim of the study was to determine the quantitative T2 values in EMC using a novel accelerated T2 mapping, and evaluate them for detection, classification,and grading of EMC.

Materials and methods

Fifty-six patients with pathologically confirmed EMC and 17 healthy volunteers were prospectively enrolled in this study. All participants underwent pelvic magnetic resonance imaging, including DWI and accelerated T2 mapping, before treatment. The T2 and apparent diffusion coefficient (ADC) values of different pathologic EMC features were extracted and compared. Receiver operating characteristic (ROC) curve analysis was performed to analyze the diagnostic efficacy of the T2 and ADC values in distinguishing different pathological features of EMC.

Results

The T2 values and ADC values were significantly lower in EMC than in normal endometrium (bothl p < 0.05). The T2 and ADC values were significantly different between endometrioid adenocarcinoma (EA) and non-EA (both p < 0.05) and EMC tumor grades (all p < 0.05) but not for EMC clinical types (both p > 0.05) and depth of myometrial invasion (both p > 0.05). The area under the ROC curve (AUC) was higher for T2 values than for ADC values in predicting grade 3 EA (0.939 vs. 0.764, p = 0.048). When combined T2 and ADC values, the AUC for predicting grade 3 EA showed a significant increase to 0.947 (p = 0.03) compared with those of ADC values. The T2 and ADC values were negatively correlated with the tumor grades (r = -0.706 and r = -0.537, respectively).

Conclusion

Quantitative T2 values demonstrate potential suitability in discriminating between EMC and normal endometrium, EA and non-EA, grade 3 EA and grade 1/2 EA. Combining T2 and ADC values performs better in predicting the histological grades of EA in comparison with ADC values alone.

Diffusion-Weighted MRI for Treatment Response Assessment in Osteoblastic Metastases-A Repeatability Study

The apparent diffusion coefficient (ADC) is a candidate marker of treatment response in osteoblastic metastases that are not evaluable by morphologic imaging. However, it is unclear whether the ADC meets the basic requirement for reliable treatment response evaluation, namely a low variance of repeated measurements in relation to the differences found between viable and nonviable metastases. The present study addresses this question by analyzing repeated in vivo ADCmedian measurements of 65 osteoblastic metastases in nine patients, as well as phantom measurements. PSMA-PET served as a surrogate for bone metastasis viability. Measures quantifying repeatability were calculated and differences in mean ADC values according to PSMA-PET status were examined. The relative repeatability coefficient %RC of ADCmedian measurements was 5.8% and 12.9% for phantom and in vivo measurements, respectively. ADCmedian values of bone metastases ranged from 595×10-6mm2/s to 2090×10-6mm2/s with an average of 63% higher values in nonviable metastases compared with viable metastases (p < 0.001). ADC shows a small repeatability coefficient in relation to the difference in ADC values between viable and nonviable metastases. Therefore, ADC measurements fulfill the technical prerequisite for reliable treatment response evaluation in osteoblastic metastases.

Diagnostic Efficacy of Diffusion-weighted Imaging in Distinguishing Chronic Diffuse Sclerosing Osteomyelitis from Suppurative Osteomyelitis of the Mandible

PURPOSE

Chronic diffuse sclerosing osteomyelitis (CDSO) is a non-suppurative inflammatory bone disease diagnosed based on combined clinical, histopathological, and radiological findings. Accurate diagnosis is important since CDSO is more refractory to treatment than suppurative osteomyelitis. The purpose of this study was to determine the diagnostic efficacy of diffusion-weighted imaging (DWI) in the quantitative assessment of CDSO to distinguish it from acute suppurative osteomyelitis (ASO) and chronic suppurative osteomyelitis (CSO) of the mandible.

METHODS

Using a retrospective cohort study design, we analyzed MRI data of 6 patients with CDSO and 34 patients with ASO and CSO. The mean apparent diffusion coefficient (ADC) values of the three groups (CDSO, ASO, and CSO groups) were calculated, and differences were analyzed using Kruskal-Wallis and post-hoc Mann-Whitney tests with Bonferroni adjustments. We performed a receiver operating characteristic (ROC) curve analysis to evaluate the ability of the ADC to predict CDSO. P < 0.05 was considered statistically significant.

RESULTS

The mean ADCs in the CDSO, ASO, and CSO groups were 1.22 ± 0.04 × 10-3 mm2/s, 1.28 ± 0.08 × 10-3 mm2/s, and 1.06 ± 0.09 × 10-3 mm2/s, respectively. Significant differences were observed between the ASO and CSO groups (P < 0.001) and CSO and CDSO groups (P < 0.01). However, there was no significant difference between the ASO and CDSO groups (P = 0.21). The ROC analysis revealed a cut-off ADC value of 1.19 for distinguishing the CSO group from the CDSO group. Sensitivity, specificity, accuracy, and area under the ROC curve were 1.0, 0.92, 0, 95, and 0.94, respectively.

CONCLUSION

The results suggest that ADC may be useful in distinguishing CDSO from mandibular suppurative osteomyelitis.

Whole-tumor histogram analysis of apparent diffusion coefficients for predicting lymphovascular space invasion in stage IB-IIA cervical cancer

Objectives

To investigate the value of apparent diffusion coefficient (ADC) histogram analysis based on whole tumor volume for the preoperative prediction of lymphovascular space invasion (LVSI) in patients with stage IB-IIA cervical cancer.

Methods

Fifty consecutive patients with stage IB-IIA cervical cancer were stratified into LVSI-positive (n = 24) and LVSI-negative (n = 26) groups according to the postoperative pathology. All patients underwent pelvic 3.0T diffusion-weighted imaging with b-values of 50 and 800 s/mm² preoperatively. Whole-tumor ADC histogram analysis was performed. Differences in the clinical characteristics, conventional magnetic resonance imaging (MRI) features, and ADC histogram parameters between the two groups were analyzed. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of ADC histogram parameters in predicting LVSI.

Results

ADC_max, ADC_range, ADC₉₀, ADC₉₅, and ADC₉₉ were significantly lower in the LVSI-positive group than in the LVSI-negative group (all P-values < 0.05), whereas no significant differences were reported for the remaining ADC parameters, clinical characteristics, and conventional MRI features between the groups (all P-values > 0.05). For predicting LVSI in stage IB-IIA cervical cancer, a cutoff ADC_max of 1.75×10^-3 mm²/s achieved the largest area under ROC curve (A_z) of 0.750, followed by a cutoff ADC_range of 1.36×10^-3 mm²/s and ADC₉₉ of 1.75×10^-3 mm²/s (A_z = 0.748 and 0.729, respectively), and the cutoff ADC₉₀ and ADC₉₅ achieved an A_z of <0.70.

Conclusion

Whole-tumor ADC histogram analysis has potential value for preoperative prediction of LVSI in patients with stage IB-IIA cervical cancer. ADC_max, ADC_range, and ADC₉₉ are promising prediction parameters.

Correlation of mean apparent diffusion coefficient (ADC) and maximal standard uptake value (SUVmax) evaluated by diffusion-weighted MRI and 18F-FDG-PET/CT in children with Hodgkin lymphoma: a feasibility study

BACKGROUND

The objective was to analyse if magnetic resonance imaging (MRI) can act as a non-radiation exposure surrogate for (18)F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in children with histologically confirmed Hodgkin lymphoma (HL) before treatment. This was done by analysing a potential correlation between apparent diffusion coefficient (ADC) in MRI and the maximum standardized uptake value (SUVmax) in FDG-PET/CT.

PATIENTS AND METHODS

Seventeen patients (six female, eleven male, median age: 16 years, range: 12-20 years) with histologically confirmed HL were retrospectively analysed. The patients underwent both MRI and (18)F-FDG PET/CT before the start of treatment. (18)F-FDG PET/CT data and correlating ADC maps in MRI were collected. For each HL-lesion two readers independently evaluated the SUVmax and correlating meanADC.

RESULTS

The seventeen patients had a total of 72 evaluable lesions of HL and there was no significant difference in the number of lesions between male and female patients (median male: 15, range: 12-19 years, median female: 17 range: 12-18 years, p = 0.021). The mean duration between MRI and PET/CT was 5.9 ± 5.3 days. The inter-reader agreement as assessed by the intraclass correlation coefficient (ICC) was excellent (ICC = 0.98, 95% CI: 0.97-0.99). The correlated SUVmax and meanADC of all 17 patients (ROIs n = 72) showed a strong negative correlation of -0.75 (95% CI: -0.84, - -0.63, p = 0.001). Analysis revealed a difference in the correlations of the examination fields. The correlated SUVmax and meanADC showed a strong correlation at neck and thoracal examinations (neck: -0.83, 95% CI: -0.93, - -0.63, p < 0.0001, thoracal: -0.82, 95% CI: -0.91, - -0.64, p < 0.0001) and a fair correlation at abdominal examinations of -0.62 (95% CI: -0.83, - -0.28, p = 0.001).

CONCLUSIONS

SUVmax and meanADC showed a strong negative correlation in paediatric HL lesions. The assessment seemed robust according to inter-reader agreements. Our results suggest that ADC maps and meanADC have the potential to replace PET/CT in the analysis of disease activity in paediatric Hodgkin lymphoma patients. This may help reduce the number of PET/CT examinations and decrease radiation exposure to children.

Investigating the Coating Effect on Charge Transfer Mechanisms in Composite Electrodes for Lithium-Ion Batteries

The performance of lithium-ion batteries (LIBs) relies on the characteristics of the cathode material, including both intentionally applied coatings and naturally formed surface layers or binder adhesion. This study investigated the influence of the ion-permeable surface fraction, distribution, and characteristics of the coating on the performance of a lithium iron phosphate (LFP) electrode material. We developed an extended Newman-type half-cell model and examined the impact of coating parameters on the galvanostatic discharge curves of the LFP electrode material. The study found that the ion-permeable surface fraction has a significant influence on the diffusion and charge transfer characteristics of the electrode material. A decrease in the ion-permeable surface fraction leads to a decrease in the measured diffusion coefficients and to an increase in the overall coating resistance of the electrode material. Interestingly, the distribution of the ion-permeable surface also plays a role in the diffusion characteristics, with a coarsely dispersed coating resulting in lower diffusion coefficients. Additionally, the coating characteristics significantly affect the polarization and capacity of the electrode material at different C-rates. The model was used to approximate the experimental discharge curves of the LFP-based composite electrodes with two different compositions, and the simulated data showed satisfactory agreement with the experiment. Thus, we believe that the developed model and its further extension will be useful in numerical simulations that aim to facilitate the search for optimal compositions.

Comparing CT and MR Properties of Artificial Thrombi According to Their Composition

This study aims to determine whether and to what extent the structure and composition of thrombi can be assessed using NMR and CT measurements. Seven different thrombus models, namely, six RBC thrombi with hematocrit levels (HTs) of 0%, 20%, 40%, 60%, 80% and 100% and one platelet thrombus model, were analyzed using proton NMR at 100 MHz and 400 MHz, with measurements of T₁ and T₂ NMR relaxation times and measurements of the apparent diffusion coefficient (ADC). In addition, the thrombus models were CT-scanned in a dual-energy mode (80 kV and 140 kV) and in a single-energy mode (80 kV) to measure their CT numbers. The results confirmed that RBC thrombi can be distinguished from platelet thrombi by using ADC and CT number measurements in all three settings, while they cannot be distinguished by using T₁ and T₂ measurements. All measured parameters allowed for the differentiation of RBC thrombi according to their HT values, but the best sensitivity to HT was obtained with ADC and single-energy CT measurements. The importance of this study also lies in the potential application of its results for the characterization of actual thrombi in vivo.

Quantitative Assessment of Intervertebral Disc Composition by MRI: Sensitivity to Diurnal Variation

Whether diurnal variation exists in quantitative MRI indices such as the T1rho relaxation time (T1ρ) of the intervertebral disc (IVD) is yet to be explored. This prospective study aimed to evaluate the diurnal variation in T1ρ, apparent diffusion coefficient (ADC), and electrical conductivity (σ) of lumbar IVD and its relationship with other MRI or clinical indices. Lumbar spine MRI, including T1ρ imaging, diffusion-weighted imaging (DWI), and electric properties tomography (EPT), was conducted on 17 sedentary workers twice (morning and evening) on the same day. The T1ρ, ADC, and σ of IVD were compared between the time points. Their diurnal variation, if any, was tested for correlation with age, body mass index (BMI), IVD level, Pfirrmann grade, scan interval, and diurnal variation in IVD height index. The results showed a significant decrease in T1ρ and ADC and a significant increase in the σ of IVD in the evening. T1ρ variation had a weak correlation with age and scan interval, and ADC variation with scan interval. Diurnal variation exists for the T1ρ, ADC, and σ of lumbar IVD, which should be accounted for in image interpretation. This variation is thought to be due to diurnal variations in intradiscal water, proteoglycan, and sodium ion concentration.