The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index

BACKGROUND

The grading of adult isocitrate dehydrogenase (IDH)-mutant astrocytomas is a crucial prognostic factor.

PURPOSE

To investigate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) in the grading of adult IDH-mutant astrocytomas, and to analyze the correlation between ADC and the Ki-67 proliferation index.

MATERIAL AND METHODS

The clinical and MRI data of 82 patients with adult IDH-mutant astrocytoma who underwent surgical resection and molecular genetic testing with IDH and 1p/19q were retrospectively analyzed. The conventional MRI features, ADCmin, ADCmean, and nADC of the tumors were compared using the Kruskal-Wallis single factor ANOVA and chi-square tests. Receiver operating characteristic (ROC) curves were drawn to evaluate conventional MRI and ADC accuracy in differentiating tumor grades. Pearson correlation analysis was performed to determine the correlation between ADC and the Ki-67 proliferation index.

RESULTS

The difference in enhancement, ADCmin, ADCmean, and nADC among WHO grade 2, 3, and 4 tumors was statistically significant (all P <0.05). ADCmin showed the preferable diagnostic accuracy for grading WHO grade 2 and 3 tumors (AUC=0.724, sensitivity=63.4%, specificity=80%, positive predictive value (PPV)=62.0%; negative predictive value (NPV)=82.5%), and distinguishing grade 3 from grade 4 tumors (AUC=0.764, sensitivity=70%, specificity=76.2%, PPV=75.0%, NPV=71.4%). Enhancement + ADC model showed an optimal predictive accuracy (grade 2 vs. 3: AUC = 0.759; grade 3 vs. 4: AUC = 0.799). The Ki-67 proliferation index was negatively correlated with ADCmin, ADCmean, and nADC (all P <0.05), and positively correlated with tumor grade.

CONCLUSION

Conventional MRI features and ADC are valuable to predict pathological grading of adult IDH-mutant astrocytomas.

Reduction of ADC bias in diffusion MRI with deep learning-based acceleration: A phantom validation study at 3.0 T

PURPOSE

Further acceleration of DWI in diagnostic radiology is desired but challenging mainly due to low SNR in high b-value images and associated bias in quantitative ADC values. Deep learning-based reconstruction and denoising may provide a solution to address this challenge.

METHODS

The effects of SNR reduction on ADC bias and variability were investigated using a commercial diffusion phantom and numerical simulations. In the phantom, performance of different reconstruction methods, including conventional parallel (SENSE) imaging, compressed sensing (C-SENSE), and compressed SENSE acceleration with an artificial intelligence deep learning-based technique (C-SENSE AI), was compared at different acceleration factors and flip angles using ROI-based analysis. ADC bias was assessed by Lin's Concordance correlation coefficient (CCC) followed by bootstrapping to calculate confidence intervals (CI). ADC random measurement error (RME) was assessed by the mean coefficient of variation (CV¯) and non-parametric statistical tests.

RESULTS

The simulations predicted increasingly negative bias and loss of precision towards lower SNR. These effects were confirmed in phantom measurements of increasing acceleration, for which CCC decreased from 0.947 to 0.279 and CV¯ increased from 0.043 to 0.439, and of decreasing flip angle, for which CCC decreased from 0.990 to 0.063 and CV¯ increased from 0.037 to 0.508. At high acceleration and low flip angle, C-SENSE AI reconstruction yielded best denoised ADC maps. For the lowest investigated flip angle, CCC = {0.630, 0.771 and 0.987} and CV¯={0.508, 0.426 and 0.254} were obtained for {SENSE, C-SENSE, C-SENSE AI}, the improvement by C-SENSE AI being significant as compared to the other methods (CV: p = 0.033 for C-SENSE AI vs. C-SENSE and p < 0.001 for C-SENSE AI vs. SENSE; CCC: non-overlapping CI between reconstruction methods). For the highest investigated acceleration factor, CCC = {0.479,0.926,0.960} and CV¯={0.519,0.119,0.118} were found, confirming the reduction of bias and RME by C-SENSE AI as compared to C-SENSE (by trend) and to SENSE (CV: p < 0.001; CCC: non-overlapping CI).

CONCLUSION

ADC bias and random measurement error in DWI at low SNR, typically associated with scan acceleration, can be effectively reduced by deep-learning based C-SENSE AI reconstruction.

The Relationship between Breast Cancer Subtypes, Prognostic Factors, and Apparent Diffusion Coefficient Histogram Analysis

BACKGROUND

Diffusion Magnetic Resonance Imaging (MRI) is a useful method to evaluate tumor biology and tumor microstructure. The apparent diffusion coefficient (ADC) value correlates negatively with the cellular density of the tumor.

OBJECTIVE

This study aimed to investigate the effectiveness of the ADC histogram analysis in showing the relationship between breast cancer prognostic factors and ADC parameters.

METHODS

This study is a retrospective observational descriptive study. ADC histogram parameters were evaluated in all tumor volumes of 67 breast cancer patients. Minimum, 5, 10, 25, 50, 75, 90, 95 percentiles, maximum, mean, median ADC values, kurtosis, and skewness were calculated. Breast MRI examinations were performed on a 3T MR scanner. We evaluated the fibroglandular tissue density of bilateral breasts, background enhancement, localization of masses, multifocality-multicentricity, shape, rim, internal contrast enhancement, and kinetic curve on breast MRI. BIRADS scoring was performed according to breast MRI. Pathologically, histologic type, histologic grade, HER 2, Ki 67, ER-, and PR status were evaluated.

RESULTS

A significant correlation was found between tumor volume and ADC scores. There is a significant correlation between min ADC values (p< 0.031), max ADC (p< 0.001), and skewness (p< 0.019). A significant correlation was found between tumor kurtosis and lymph nodes (p< 0.029). There was a significant difference in ADC mean, ADC10%, ADC25%, ADC50%, ADC75%, ADC90%, ADC 95% and ADCmax values depending on ER-and PRstatus. (for ER p = 0.004, p = 0.018, p = 0.010, p = 0.008, p = 0.004, p = 0.004, p = 0.02, p = 0.02 and p = 0.038, for PR p < 0.001, p = 0.028, p = 0.011, p = 0.001, p < 0.001, p =<0.001, p < 0.001, and p < 0.001, respectively; p < 0.05). These values were lower in ER-and PR-positive status than in ER-and PR-negative receptor status. According to HER2 status, there was a statistically significant difference in ADC5% and measurements of the lesions (p = 0.041; p < 0.05). Our study found no significant correlation between other prognostic factors, such as histological grade, Ki-67 indices, and ADC values.

CONCLUSION

Our study found a significant difference between tumor volume, ER- and, PR status, HER2, and lymph node involvement, and some ADC values among prognostic factors for breast cancer. Furthermore, ADC histogram analysis can provide additional value in predicting some prognostic factors.

A case of odontogenic keratocyst in the buccal space: characterization by multimodality imaging including computed tomography, diffusion-weighted magnetic resonance imaging, and ultrasonography

Odontogenic keratocyst (OKC) is a relatively common non-inflammatory jaw lesion. OKC is known to occur most often in the mandibular angle and mandibular ramus, but rarely outside the bone. In this report, we describe characteristic multimodality imaging of OKC in the buccal space, especially diffusion-weighted MR imaging (DWI) with apparent diffusion coefficient (ADC) mapping, extra-oral and intra-oral ultrasonography. On clinical examination, an approximately 20 mm in diameter mass with elastic hardness was found the left side of the buccal area. Contrast-enhanced CT showed areas of internal non-contrast lesions in the left buccal space. On T1-weighted image, the mass showed multilocular high signal intensity, and homogeneous internal. T2-weighted images revealed high signal at the marginal part and slightly median signal in the internal part. STIR images revealed a heterogeneous high signal in the interior. Furthermore, DWI and ADC map showed high signal and moderate-to-low signal intensity, respectively. ADC value of the lesion was 1.55 × 10-3 mm2 s-1. On extra-oral ultrasonography, the tumor showed clear boundary, hypoechoic, homogeneous internal architecture and vascular signals, and heterogeneous hard of the lesion. On intra-oral ultrasonography also showed clear boundary, hypoechoic, homogeneous internal architecture, heterogeneous hard of the tumor, and back echo enhance. The histopathologic diagnosis based on a full excisional specimen was odontogenic keratocyst. This case suggests that multimodality imaging, especially MR imaging with ADC and DWI, and extra and intra-oral ultrasonography with color Doppler imaging and elastography, could be effective for evaluating buccal lesions.

Mean ADC values and arterial phase hyperintensity discriminate small (≤ 3 cm) well-differentiated hepatocellular carcinoma from dysplastic nodule

BACKGROUND/AIM

This research endeavor sought to distinguish small (≤ 3 cm) well-differentiated hepatocellular carcinoma (WD-HCC) from dysplastic nodules (DN) by employing traditional imaging features and mean apparent diffusion coefficient (mADC) values derived from diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

In this retrospective analysis, we assessed a cohort of ninety patients with confirmed dysplastic nodules (DNs) (n = 71) or well-differentiated hepatocellular carcinoma (WD-HCC) (n = 41) who had undergone dynamic contrast-enhanced magnetic resonance imaging between March 2018 and June 2021. Multivariable logistic regression analyses were executed to pinpoint characteristics that can effectively differentiate histologic grades. A region-of-interest (ROI) encompassing all lesion voxels was delineated on each slice containing the mass in the ADC map. Subsequently, the whole-lesion mean ADC (mADC) were computed from these delineations. A receiver operating characteristic (ROC) curve was generated to assess the discriminatory efficacy of the mADC values in distinguishing between WD-HCC and DN.

RESULTS

Among the histopathological types from benign to malignant, mADC showed a significant decrease (P < 0.001). The mADCs were effective in distinguishing WD-HCC from DN [AUC, 0.903 (95% CI 0.849-0.958)]. The best cutoffs for the Youden index were 0.0012 mm2/s for mADC, with moderate sensitivity (70.7%) and high specificity (94.4%). MRI features including hyperintensity at arterial phase (odds ratio, 21.2; P = 0.009), mADC < 0.0012 mm2/s (odds ratio, 52.2; P < 0.001) were independent predictors for WD-HCC at multivariable analysis. The AUC value of hyperintensity at arterial phase was 0.857 (95% CI 0.786-0.928). The composite diagnostic criterion of arterial hyperintensity + mADC < 0.0012 mm2/s showed good performance [AUC, 0.926 (95% CI 0.878-0.975)], displaying increased sensitivity compared to individual assessments involving arterial hyperintensity (P = 0.013), mADC < 0.0012 mm2/s (P = 0.004), or LR-5 (P < 0.001), with similar specificity compared to LR-5 (P = 0.193).

CONCLUSION

DN and WD-HCC displayed contrasting diffusion characteristics, attainable to distinguish with satisfactory accuracy. The utilization of arterial phase hyperintensity and mADC < 0.0012 on MRI facilitated the differentiation of WD-HCC from DN.

Diffusion tensor imaging combined with the dual-echo steady-state (DESS) protocol for the evaluation of the median nerve in the carpal tunnel: A preliminary study

Background

Carpal tunnel syndrome (CTS) is diagnosed based on neurological, electrophysiology, and radiological findings. Due to the technical development of magnetic resonance imaging (MRI), the median nerve is evaluated with several MRI protocols. However, diffusion tensor imaging (DTI) combined with a dual-echo steady-state (DESS) protocol is not frequently used to evaluate the median nerve of CTS. This study aimed to evaluate the median nerve in the carpal tunnel using DTI combined with a DESS protocol.

Methods

Five healthy volunteers and seven patients with CTS were enrolled. The patients underwent MRI for CTS pre- and post-operatively. The median nerve was evaluated using a 3-T MRI scanner. The parameters of the DESS protocol were as follows: Repetition time (TR)/echo time (TE) = 10.83/3.32 ms, slice thickness = 0.45 mm, field of view (FoV) = 350 × 253 × 350 mm, and 3D voxel size = 0.5 × 0.5 ×0.4 mm. The parameters of the DTI sequence were as follows: TR/TE = 4000/86 ms, slice thickness = 3 mm, FoV = 160 × 993 × 90 mm, 3D voxel size = 1.2 × 1.2 ×3.0 mm, and b value = 0.1000 s/mm2. The apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values of the median nerve were statistically analyzed. Statistical significance was set at P< 0.05.

Results

The FA value of healthy volunteers was 0.576 ± 0.058, while those of the patients were 0.357 ± 0.094 and 0.395 ± 0.062 pre-and post-operatively, respectively. Statistically significant differences were identified between the FA values of healthy volunteers and pre-operative/post-operative patients. The ADC values of healthy volunteers and pre-operative patients were 0.931 ± 0.096 and 1.26 ± 0.282 (10-3 mm2/s), respectively (P< 0.05).

Conclusion

This MRI protocol may be useful for evaluating the median nerve in the carpal tunnel.

Quantitative Assessment of Breast Tumor: Comparison of Four Methods of Positioning Region of Interest for Synthetic Relaxometry and Diffusion Measurement

RATIONALE AND OBJECTIVES

To compare the differences in apparent diffusion coefficient (ADC) and synthetic magnetic resonance (MR) measurements of four region of interest (ROI) placement methods for breast tumor and to investigate their diagnostic performance.

METHODS

110 (70 malignant, 40 benign) newly diagnosed breast tumors were evaluated. The patients underwent 3.0 T MR examinations including diffusion-weighted imaging and synthetic MR. Two radiologists independently measured ADCs, T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) using four ROI methods: round, square, freehand, and whole-tumor volume (WTV). The interclass correlation coefficient (ICC) was used to assess their measurement reliability. Diagnostic performance was evaluated using multivariate logistic regression analysis and the receiver operating characteristic (ROC) curves.

RESULTS

The mean values of all ROI methods showed good or excellent interobserver reproducibility (0.79-0.99) and showed the best diagnostic performance compared to the minimum and maximum values. The square ROI exhibited superior performance in differentiating between benign from malignant breast lesions, followed by the freehand ROI. T2, PD, and ADC values were significantly lower in malignant breast lesions compared to benign ones for all ROI methods (p < 0.05). Multiparameters of T2 + ADC demonstrated the highest AUC values (0.82-0.95), surpassing the diagnostic efficacy of ADC or T2 alone (p < 0.05).

CONCLUSION

ROI placement significantly influences ADC and synthetic MR values measured in breast tumors. Square ROI and mean values showed superior performance in differentiating benign and malignant breast lesions. The multiparameters of T2 + ADC surpassed the diagnostic efficacy of a single parameter.

Apparent diffusion coefficient values predict response to brachytherapy in bulky cervical cancer

BACKGROUND

Diffusion-weighted magnetic resonance imaging (DWI) provides a measurement of tumor cellularity. We evaluated the potential of apparent diffusion coefficient (ADC) values obtained from post-external beam radiation therapy (EBRT) DWI and prior to brachytherapy (BT) to predict for complete metabolic response (CMR) in bulky cervical cancer.

METHODS

Clinical and DWI (b value = 500 s/mm2) data were obtained from patients undergoing interstitial BT with high-risk clinical target volumes (HR-CTVs) > 30 cc. Volumes were contoured on co-registered T2 weighted images and 90th percentile ADC values were calculated. Patients were stratified by CMR (defined by PET-CT at three months post-BT). Relation of CMR with 90th percentile ADC values and other clinical factors (International Federation of Gynecology and Obstetrics (FIGO) stage, histology, tumor and HR-CTV size, pre-treatment hemoglobin, and age) was assessed both in univariate and multivariate logistic regression analyses. Youden's J statistic was used to identify a threshold value.

RESULTS

Among 45 patients, twenty-eight (62%) achieved a CMR. On univariate analysis for CMR, only 90th percentile ADC value was significant (p = 0.029) while other imaging and clinical factors were not. Borderline significant factors were HR-CTV size (p = 0.054) and number of chemotherapy cycles (p = 0.078). On multivariate analysis 90th percentile ADC (p < 0.0001) and HR-CTV size (p < 0.003) were highly significant. Patients with 90th percentile ADC values above 2.10 × 10- 3 mm2/s were 5.33 (95% CI, 1.35-24.4) times more likely to achieve CMR.

CONCLUSIONS

Clinical DWI may serve to risk-stratify patients undergoing interstitial BT for bulky cervical cancer.

Repeatability quantification of brain diffusion-weighted imaging for future clinical implementation at a low-field MR-linac

BACKGROUND

Longitudinal assessments of apparent diffusion coefficients (ADCs) derived from diffusion-weighted imaging (DWI) during intracranial radiotherapy at magnetic resonance imaging-guided linear accelerators (MR-linacs) could enable early response assessment by tracking tumor diffusivity changes. However, DWI pulse sequences are currently unavailable in clinical practice at low-field MR-linacs. Quantifying the in vivo repeatability of ADC measurements is a crucial step towards clinical implementation of DWI sequences but has not yet been reported on for low-field MR-linacs. This study assessed ADC measurement repeatability in a phantom and in vivo at a 0.35 T MR-linac.

METHODS

Eleven volunteers and a diffusion phantom were imaged on a 0.35 T MR-linac. Two echo-planar imaging DWI sequence variants, emphasizing high spatial resolution ("highRes") and signal-to-noise ratio ("highSNR"), were investigated. A test-retest study with an intermediate outside-scanner-break was performed to assess repeatability in the phantom and volunteers' brains. Mean ADCs within phantom vials, cerebrospinal fluid (CSF), and four brain tissue regions were compared to literature values. Absolute relative differences of mean ADCs in pre- and post-break scans were calculated for the diffusion phantom, and repeatability coefficients (RC) and relative RC (relRC) with 95% confidence intervals were determined for each region-of-interest (ROI) in volunteers.

RESULTS

Both DWI sequence variants demonstrated high repeatability, with absolute relative deviations below 1% for water, dimethyl sulfoxide, and polyethylene glycol in the diffusion phantom. RelRCs were 7% [5%, 12%] (CSF; highRes), 12% [9%, 22%] (CSF; highSNR), 9% [8%, 12%] (brain tissue ROIs; highRes), and 6% [5%, 7%] (brain tissue ROIs; highSNR), respectively. ADCs measured with the highSNR variant were consistent with literature values for volunteers, while smaller mean values were measured for the diffusion phantom. Conversely, the highRes variant underestimated ADCs compared to literature values, indicating systematic deviations.

CONCLUSIONS

High repeatability of ADC measurements in a diffusion phantom and volunteers' brains were measured at a low-field MR-linac. The highSNR variant outperformed the highRes variant in accuracy and repeatability, at the expense of an approximately doubled voxel volume. The observed high in vivo repeatability confirms the potential utility of DWI at low-field MR-linacs for early treatment response assessment.

Evaluation of deep learning reconstruction on diffusion-weighted imaging quality and apparent diffusion coefficient using an ice-water phantom

This study assessed the influence of deep learning reconstruction (DLR) on the quality of diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) using an ice-water phantom. An ice-water phantom with known diffusion properties (true ADC = 1.1 × 10-3 mm2/s at 0 °C) was imaged at various b-values (0, 1000, 2000, and 4000 s/mm2) using a 3 T magnetic resonance imaging scanner with slice thicknesses of 1.5 and 3.0 mm. All DWIs were reconstructed with or without DLR. ADC maps were generated using combinations of b-values 0 and 1000, 0 and 2000, and 0 and 4000 s/mm2. Based on the quantitative imaging biomarker alliance profile, the signal-to-noise ratio (SNRs) in DWIs was calculated, and the accuracy, precision, and within-subject parameter variance (wCV) of the ADCs were evaluated. DLR improved the SNR in DWIs with b-values ranging from 0 to 2000s/mm2; however, its effectiveness was diminished at 4000 s/mm2. There was no noticeable difference in the ADCs of images generated with or without implementing DLR. For a slice thickness of 1.5 mm and combined b-values of 0 and 4000 s/mm2, the ADC values were 0.97 × 10-3and 0.98 × 10-3mm2/s with and without DLR, respectively, both being lower than the true ADC value. Furthermore, DLR enhanced the precision and wCV of the ADC measurements. DLR can enhance the SNR, repeatability, and precision of ADC measurements; however, it does not improve their accuracies.

Quantitative diffusion weighted imaging in patients with hepatocellular carcinoma: effects of simultaneous multi-slice acceleration and gadoxetic acid administration

PURPOSE

To investigate whether simultaneous multi-slice (SMS) acceleration and gadoxetic acid administration affect the quantitative apparent diffusion coefficient (ADC) and signal-to-noise ratio (SNR) measurement of DWI in patients with HCC.

METHODS

This prospective study initially enrolled 208 patients with clinically suspected HCC. Free breathing SMS-DWI and conventional DWI (CON-DWI) were performed before and after gadoxetic acid administration. Lesion conspicuity, ADCs and SNRs of the HCC lesion and normal liver parenchyma were independently measured by two radiologists. The paired t test or Wilcoxon signed rank test was used to evaluate the differences of lesion conspicuity, ADCs and SNRs between SMS-DWI and CON-DWI, as well as those before and after gadoxetic acid administration.

RESULTS

A total of 102 HCC patients (90 men and 12 women; mean age, 54.6 ± 11.7 years) were finally included for analysis. SMS-DWI and CON-DWI demonstrated comparable lesion conspicuity (P = 0.081-0.566). For the influence of SMS acceleration, the SNRs of liver parenchyma on enhanced SMS-DWI were significantly higher than enhanced CON-DWI (P = 0.015). For the influence of gadoxetic acid administration, the mean ADCs were significantly higher on enhanced SMS-DWI than unenhanced SMS-DWI (HCC, P = 0.013; liver parenchyma, P = 0.032).

CONCLUSION

Quantitative ADC measurements of HCC and liver parenchyma were not affected by SMS acceleration, and SMS-DWI can provide higher SNR than CON-DWI. However, the ADC measurements can be affected by gadoxetic acid administration on SMS-DWI, so it is recommended to perform SMS-DWI before gadoxetic acid administration.

Diagnostic value of cervical spine ZOOM-DWI in cervical spondylotic myelopathy

PURPOSE

To investigate the clinical application value of the non-shared incentive diffusion imaging technique (ZOOM-DWI) diagnoses of cervical spondylotic myelopathy (CSM).

METHODS

49 CSM patients who presented from January 2022 to December 2022 were selected as the patient group, and 50 healthy volunteers are recruited as the control group. All subjects underwent conventional MRI and ZOOM-DWI of the cervical spine and neurologic mJOA scores in patients with CSM. The spinal ADC values of segments C2-3, C4-5, C5-6, and C6-7 are measured and analyzed in all subjects, with C5-6 being the most severe level of spinal canal compression in the patient group. In addition, the study also analyzes and compares the relationship between the C5-6 ADC value and mJOA score in the patient group.

RESULTS

The mean ADC shows no significantly different levels in the control group. Among the ADC values at each measurement level in the patient group, except for C4-5 and C6-7 segments are not statistically significant, the remaining pair-wise comparisons all show statistically significant differences (F = 24.368, p < 0.001). And these individuals have the highest ADC value at C5-6. The C5-6 ADC value in the patient group is significantly higher compared with the ADC value in the control group (t = 9.414, p < 0.001), with statistical significance. The ADC value at the patient stenosis shows a significant negative correlation with the mJOA score (r = -0.493, p < 0.001).

CONCLUSION

Cervical ZOOM-DWI can be applied to diagnose CSM, and spinal ADC value can use as reliable imaging data for diagnosing cervical myelopathy.

Value of diffusion kurtosis MR imaging and conventional diffusion weighed imaging for evaluating response to first-line chemotherapy in unresectable pancreatic cancer

OBJECTIVE

To investigate the diagnostic value of diffusion kurtosis magnetic resonance imaging (DKI) and conventional diffusion-weighted imaging (DWI) for evaluating the response to first-line chemotherapy in unresectable pancreatic cancer.

MATERIALS AND METHODS

We retrospectively analyzed 21 patients with clinically and pathologically confirmed unresected pancreatic cancer who received palliative chemotherapy. Three-tesla MRI examinations containing DWI sequences with b values of 0, 100, 700, 1400, and 2100 s/mm2 were performed before and after chemotherapy. Parameters included the apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), and mean diffusional kurtosis (MK). The performances of the DWI and DKI parameters in distinguishing the response to chemotherapy were evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Overall survival (OS) was calculated from the date of first treatment to the date of death or the latest follow-up date.

RESULTS

The ADCchange and MDchange were significantly higher in the responding group (PR group) than in the nonresponding group (non-PR group) (ADCchange: 0.21 ± 0.05 vs. 0.11 ± 0.09, P = 0.02; MDchange: 0.37 ± 0.24 vs. 0.10 ± 0.12, P = 0.002). No statistical significance was shown when comparing ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost between the PR and non-PR groups. The ROC curve analysis indicated that MDchange (AUC = 0.898, cutoff value = 0.7143) performed better than ADCchange (AUC = 0.806, cutoff value = 0.1369) in predicting the response to chemotherapy.

CONCLUSION

The ADCchange and MDchange demonstrated strong potential for evaluating the response to chemotherapy in unresectable pancreatic cancer. The MDchange showed higher specificity in the classification of PR and non-PR than the ADCchange. Other parameters, including ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost, are not suitable for response evaluation. The combined model SUMchange demonstrated superior performance compared to the individual DWI and DKI models. Further experiments are needed to evaluate the potential of DWI and DKI parameters in predicting the prognosis of patients with unresectable pancreatic cancer.

Evaluation of cranial nerve involvement in chordomas and chondrosarcomas: a retrospective imaging study

PURPOSE

Cranial nerve involvement (CNI) influences the treatment strategies and prognosis of head and neck tumors. However, its incidence in skull base chordomas and chondrosarcomas remains to be investigated. This study evaluated the imaging features of chordoma and chondrosarcoma, with a focus on the differences in CNI.

METHODS

Forty-two patients (26 and 16 patients with chordomas and chondrosarcomas, respectively) treated at our institution between January 2007 and January 2023 were included in this retrospective study. Imaging features, such as the maximum diameter, tumor location (midline or off-midline), calcification, signal intensity on T2-weighted image, mean apparent diffusion coefficient (ADC) values, contrast enhancement, and CNI, were evaluated and compared using Fisher's exact test or the Mann-Whitney U-test. The odds ratio (OR) was calculated to evaluate the association between the histological type and imaging features.

RESULTS

The incidence of CNI in chondrosarcomas was significantly higher than that in chordomas (63% vs. 8%, P < 0.001). An off-midline location was more common in chondrosarcomas than in chordomas (86% vs. 13%; P < 0.001). The mean ADC values of chondrosarcomas were significantly higher than those of chordomas (P < 0.001). Significant associations were identified between chondrosarcomas and CNI (OR = 20.00; P < 0.001), location (OR = 53.70; P < 0.001), and mean ADC values (OR = 1.01; P = 0.002).

CONCLUSION

The incidence of CNI and off-midline location in chondrosarcomas was significantly higher than that in chordomas. CNI, tumor location, and the mean ADC can help distinguish between these entities.

Diffusion weighted imaging combining respiratory triggering and navigator echo tracking in the upper abdomen

OBJECTIVES

To evaluate a new motion correction method, named RT + NV Track, for upper abdominal DWI that combines the respiratory triggering (RT) method using a respiration sensor and the Navigator Track (NV Track) method using navigator echoes.

MATERIALS AND METHODS

To evaluate image quality acquired upper abdominal DWI and ADC images with RT, NV, and RT + NV Track in 10 healthy volunteers and 35 patients, signal-to-noise efficiency (SNRefficiency) and the coefficient of variation (CV) of ADC values were measured. Five radiologists independently performed qualitative image-analysis assessments.

RESULTS

RT + NV Track showed significantly higher SNRefficiency than RT and NV (14.01 ± 4.86 vs 12.05 ± 4.65, 10.05 ± 3.18; p < 0.001, p < 0.001). RT + NV Track was superior to RT and equal or better quality than NV in CV and visual evaluation of ADC values (0.033 ± 0.018 vs 0.080 ± 0.042, 0.057 ± 0.034; p < 0.001, p < 0.001). RT + NV Track tends to acquire only expiratory data rather than NV, even in patients with relatively rapid breathing, and can correct for respiratory depth variations, a weakness of RT, thus minimizing image quality degradation.

CONCLUSION

The RT + NV Track method is an efficient imaging method that combines the advantages of both RT and NV methods in upper abdominal DWI, providing stably good images in a short scan time.

Reproducibility of diffusion-weighted magnetic resonance imaging in head and neck cancer assessed on a 1.5 T MR-Linac and comparison to parallel measurements on a 3 T diagnostic scanner

BACKGROUND AND PURPOSE

Before quantitative imaging biomarkers (QIBs) acquired with magnetic resonance imaging (MRI) can be used for interventional trials in radiotherapy (RT), technical validation of these QIBs is necessary. The aim of this study was to assess the reproducibility of apparent diffusion coefficient (ADC) values, derived from diffusion-weighted (DW) MRI, in head and neck cancer using a 1.5 T MR-Linac (MRL) by comparison to a 3 T diagnostic scanner (DS).

MATERIAL AND METHODS

DW-MRIs were acquired on MRL and DS for 15 head and neck cancer patients before RT and in week 2 and rigidly registered to the planning computed tomography. Mean ADC values were calculated for submandibular (SG) and parotid (PG) glands as well as target volumes (TV, gross tumor volume and lymph nodes), which were delineated based on computed tomography. Mean absolute ADC differences as well as within-subject coefficient of variation (wCV) and intraclass correlation coefficients (ICCs) were calculated for all volumes of interest.

RESULTS

A total of 23 datasets were analyzed. Mean ADC difference (DS-MRL) for SG, PG and TV resulted in 142, 254 and 93·10-6 mm2/s. wCVs/ICCs, comparing MRL and DS, were determined as 13.7 %/0.26, 24.4 %/0.23 and 16.1 %/0.73 for SG, PG and TV, respectively.

CONCLUSION

ADC values, measured on the 1.5 T MRL, showed reasonable reproducibility with an ADC underestimation in contrast to the DS. This ADC shift must be validated in further experiments and considered for future translation of QIB candidates from DS to MRL for response adaptive RT.

Nomogram for Predicting Microvascular Invasion in Hepatocellular Carcinoma Using Gadoxetic Acid-Enhanced MRI and Intravoxel Incoherent Motion Imaging

RATIONALE AND OBJECTIVES

Microvascular invasion (MVI) is an important risk factor in hepatocellular carcinoma (HCC), but it can only be determined through histopathological results. The aim of this study was to develop and validate a nomogram for preoperative prediction MVI in HCC using gadoxetic acid-enhanced magnetic resonance imaging (MRI) and intravoxel incoherent motion imaging (IVIM).

MATERIALS AND METHODS

From July 2017 to September 2022, 148 patients with surgically resected HCC who underwent preoperative gadoxetic acid-enhanced MRI and IVIM were included in this retrospective study. Clinical indicators, imaging features, and diffusion parameters were compared between the MVI-positive and MVI-negative groups using the chi-square test, Mann-Whitney U test, and independent sample t test. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance in predicting MVI. Univariate and multivariate analyses were conducted to identify the significant clinical-radiological variables associated with MVI. Subsequently, a predictive nomogram that integrates clinical-radiological risk factors and diffusion parameters was developed and validated.

RESULTS

Serum alpha-fetoprotein level, tumor size, nonsmooth tumor margin, peritumoral hypo-intensity on hepatobiliary phase (HBP), apparent diffusion coefficient value and D value were statistically significant different between MVI-positive group and MVI-negative group. The results of multivariate analysis identified tumor size (odds ratio [OR], 0.786; 95% confidence interval [CI], 0.675-0.915; P < .01), nonsmooth tumor margin (OR, 2.299; 95% CI, 1.005-5.257; P < .05), peritumoral hypo-intensity on HBP (OR, 2.786; 95% CI, 1.141-6.802; P < .05) and D (OR, 0.293; 95% CI,0.089-0.964; P < .05) was the independent risk factor for the status of MVI. In ROC analysis, the combination of peritumoral hypo-intensity on HBP and D demonstrated the highest area under the curve value (0.902) in prediction MVI status, with sensitivity 92.8% and specificity 87.7%. The nomogram exhibited excellent predictive performance with C-index of 0.936 (95% CI 0.895-0.976) in the patient cohort, and had well-fitted calibration curve.

CONCLUSION

The nomogram incorporating clinical-radiological risk factors and diffusion parameters achieved satisfactory preoperative prediction of the individualized risk of MVI in patients with HCC.

Utilization of the corticomedullary difference in magnetic resonance imaging-derived apparent diffusion coefficient for noninvasive assessment of chronic kidney disease in type 2 diabetes

BACKGROUNDS

Accumulating data demonstrated that the cortico-medullary difference in apparent diffusion coefficient (ΔADC) of diffusion-weighted magnetic resonance imaging (DWI) was a better correlation with kidney fibrosis, tubular atrophy progression, and a predictor of kidney function evolution in chronic kidney disease (CKD).

OBJECTIVES

We aimed to assess the value of ΔADC in evaluating disease severity, differential diagnosis, and the prognostic risk stratification for patients with type 2 diabetes (T2D) and CKD.

METHODS

Total 119 patients with T2D and CKD who underwent renal MRI were prospectively enrolled. Of them, 89 patients had performed kidney biopsy for pathological examination, including 38 patients with biopsy-proven diabetic kidney disease (DKD) and 51 patients with biopsy-proven non-diabetic kidney disease (NDKD) and Mix (DKD + NDKD). Clinicopathological characteristics were compared according to different ΔADC levels. Moreover, univariate and multivariate-linear regression analyses were performed to explore whether ΔADC was independently associated with estimated glomerular filtration rate (eGFR) and urinary albumin creatinine ratio (UACR). The diagnostic performance of ΔADC for discriminating DKD from NDKD + Mix was evaluated by receiver operating characteristic (ROC) analysis. In addition, an individual's 2- or 5-year risk probability of progressing to end-stage kidney disease (ESKD) was calculated by the kidney failure risk equation (KFRE). The effect of ΔADC on prognostic risk stratification was assessed. Additionally, net reclassification improvement (NRI) was used to evaluate the model performance.

RESULTS

All enrolled patients had a median ΔADC level of 86 (IQR 28, 155) × 10-6 mm2/s. ΔADC significantly decreased across the increasing staging of CKD (P < 0.001). Moreover, those with pathological-confirmed DKD has a significantly lower level of ΔADC than those with NDKD and Mix (P < 0.001). It showed that ΔADC was independently associated with eGFR (β = 1.058, 95% CI = [1.002,1.118], P = 0.042) and UACR (β = -3.862, 95% CI = [-7.360, -0.365], P = 0.031) at multivariate linear regression analyses. Besides, ΔADC achieved an AUC of 0.707 (71% sensitivity and 75% specificity) and AUC of 0.823 (94% sensitivity and 67% specificity) for discriminating DKD from NDKD + Mix and higher ESKD risk categories (≥50% at 5 years; ≥10% at 2 years) from lower risk categories (<50% at 5 years; <10% at 2 years). Accordingly, the optimal cutoff value of ΔADC for higher ESKD risk categories was 66 × 10-6 mm2/s, and the group with the low-cutoff level of ΔADC group was associated with 1.232 -fold (95% CI 1.086, 1.398) likelihood of higher ESKD risk categories as compared to the high-cutoff level of ΔADC group in the fully-adjusted model. Reclassification analyses confirmed that the final adjusted model improved NRI.

CONCLUSIONS

ΔADC was strongly associated with eGFR and UACR in patients with T2D and CKD. More importantly, baseline ΔADC was predictive of higher ESKD risk, independently of significant clinical confounding. Specifically, ΔADC <78 × 10-6 mm2/s and <66 × 10-6 mm2/s would help to identify T2D patients with the diagnosis of DKD and higher ESKD risk categories, respectively.

Role of multiparametric MRI in predicting muscle invasiveness in urinary bladder neoplasms with pathological correlations

Urinary bladder cancer (BC) is one of the most frequent malignancies and the ninth most common malignancy worldwide. The objective of this study is to assess the role of multiparametric magnetic resonance imaging (mp-MRI) in predicting the invasiveness of urinary bladder space occupying lesions. Thirty-five patients diagnosed with bladder masses underwent an mp-MRI study. The results of three image sets were analysed and compared with the histopathological results as a reference standard: T2-weighted image (T2WI) plus dynamic contrast-enhanced (DCE), T2WI plus diffusion-weighted images (DWI), and mp-MRI, including T2WI plus DWI and DCE. The diagnostic accuracy of mp-MRI was evaluated using receiver operating characteristic curve analysis. We discovered a highly significant correlation between muscle invasiveness as staged by HPE (Histopathological examination) and mp-MRI utilising a VI-RADS score >3 (p 0.001) with a sensitivity of 100% and a specificity of 85.7%. With a diagnostic accuracy of 77.14%, a sensitivity of 92.31%, a specificity of 72.72%, a positive predictive value of 66.67%, and a negative predictive value of 94.11%, In terms of muscle invasiveness, there is good concordance between HPE staging and mp-MRI utilising the VI-RADS score. The mean apparent diffusion coefficient (ADC) values were higher in low grades than in high grades. The ROC curve study revealed a very strong correlation between HPE grade and ADC (p = 0.045). In 77.14% of patients, Mp-MRI correctly identified the local T stage. Mp-MRI is imaging biomarker for invasiveness and grade of tumour. The tumours with high grade are more invasive. However, the diagnostic accuracy of mp-MRI in determining muscle invasiveness is not very high and it overstages the disease in some cases (33.3%). Its clinical usefulness in determining muscle invasiveness before TURBT and histopathological examination can be questioned.

Diffusion weighted imaging with reverse encoding distortion correction: Improvement of image quality and distortion for accurate ADC evaluation in in vitro and in vivo studies

PURPOSE

The purpose of this in vivo study was to determine the effect of reverse encoding direction (RDC) on apparent diffusion coefficient (ADC) measurements and its efficacy for improving image quality and diagnostic performance for differentiating malignant from benign tumors on head and neck diffusion-weighted imaging (DWI).

METHODS

Forty-eight patients with head and neck tumors underwent DWI with and without RDC and pathological examinations. Their tumors were then divided into two groups: malignant (n = 21) and benign (n = 27). To determine the utility of RDC for DWI, the difference in the deformation ratio (DR) between DWI and T2-weighted images of each tumor was determined for each tumor area. To compare ADC measurement accuracy of DWIs with and without RDC for each patient, ADC values for tumors and spinal cord were determined by using ROI measurements. To compare DR and ADC between two methods, Student's t-tests were performed. Then, ADC values were compared between malignant and benign tumors by Student's t-test on each DWI. Finally, sensitivity, specificity and accuracy were compared by means of McNemar's test.

RESULTS

DR of DWI with RDC was significantly smaller than that without RDC (p < 0.0001). There were significant differences in ADC between malignant and benign lesions on each DWI (p < 0.05). However, there were no significant difference of diagnostic accuracy between the two DWIs (p > 0.05).

CONCLUSION

RDC can improve image quality and distortion of DWI and may have potential for more accurate ADC evaluation and differentiation of malignant from benign head and neck tumors.

The magnetic resonance imaging and age-adjusted matrix metalloproteinase-7 assist the diagnosis of biliary atresia

BACKGROUND

We investigated the utilities of the liver-to-psoas apparent diffusion coefficient ratios (LTPAR) yielded by diffusion-weighted magnetic resonance imaging (DWMRI) and the age-adjusted serum matrix metalloproteinase-7 (MMP-7) for the diagnosis of biliary atresia (BA) in cholestatic infants.

METHODS

In total, 170 cholestatic infants were recruited, of whom 50 (29.41%) were diagnosed with BA after cholestatic workups. The LTPAR and MMP7 levels were assessed.

RESULTS

The LTPAR was significantly lower in BA infants, and the age-adjusted MMP7 ratio was significantly higher, compared to other cholestatic infants (both p < 0.001). Receiver operating characteristic curve analysis yielded a cutoff > 0.1 ng/mL.day for the age-adjusted MMP-7 ratio, and an LTPAR < 1.01 for the optimal prediction of BA (both p < 0.001). Univariate logistic regression analysis revealed that both an age-adjusted MMP-7 ratio > 0.1 ng/mL.day and an LTPAR < 1.01 were significant predictors of BA among cholestatic infants (odds ratio = 30.98 and 13.28; p < 0.001 and < 0.001, respectively). The significance of the age-adjusted MMP-7 ratio and the LTPAR persisted on multivariate logistic regression analysis after adjusting for sex and the serum gamma-glutamyl transferase level (p < 0.001 and < 0.001, respectively). The negative predictive values (NPVs) for BA were 91.49% and 94.17%, respectively, for the LTPAR and age-adjusted MMP-7 ratio.

CONCLUSION

The age-adjusted MMP-7 ratio and the LTPAR are both significant non-invasive predictors of BA. The consideration of both serum and imaging parameters may enhance BA diagnostic performance in cholestatic infants.

Paediatric supratentorial tumours do not cause microstructural alterations in contralateral white matter: a preliminary study

BACKGROUND AND PURPOSE

Intracranial tumours in children can exhibit different characteristics compared to those in adults. Understanding the microstructural changes in the contralateral normal-appearing white matter (NAWM) in children with primary intracranial masses is essential for optimizing treatment strategies. This study aimed to investigate the apparent diffusion coefficient (ADC) changes in contralateral NAWM using fully automated methods and deep learning algorithms.

METHODS

We included 22 paediatric patients with primary supratentorial intracranial masses (23% high-grade) in the study. ADC values of the contralateral NAWM in the patient group were compared to those of a control group. Deep learning algorithms were utilized to analyse diffusion changes in NAWM.

RESULTS

The mean ADC values of contralateral NAWM in the patient group were 0.80 ± 0.03 × 10-3 mm2/s, while the control group had a mean ADC value of 0.81 ± 0.03 × 10-3 mm2/s. There was no statistically significant difference between the groups (p = 0.39). Our findings indicate that there are no significant diffusion changes in the contralateral white matter of children with supratentorial intracranial masses.

CONCLUSION

Primary supratentorial intracranial masses in children do not cause microstructural changes in contralateral normal-appearing white matter. This could be attributed to the less infiltrative nature and different biochemical profile of these tumour groups in the paediatric population. Further studies using advanced imaging techniques could provide additional insights into the distinct characteristics of paediatric intracranial tumours and improve patient management.

Short repetition time diffusion-weighted imaging improves visualization of prostate cancer

PURPOSE

This study aimed to assess whether short repetition time (TR) diffusion-weighted imaging (DWI) could improve diffusion contrast in patients with prostate cancer (PCa) compared with long TR (conventional) reference standard DWI.

MATERIALS AND METHODS

Our Institutional Review Board approved this retrospective study and waived the need for informed consent. Twenty-five patients with suspected PCa underwent multiparametric magnetic resonance imaging (mp-MRI) using a 3.0-T system. DWI was performed with TR of 1850 ms (short) and 6000 ms (long) with b-values of 0, 1000, and 2000s/mm2. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), visual score, apparent diffusion coefficient (ADC), and diagnostic performance were compared between short and long TR DWI for both b-values. The statistical tests included paired t-test for SNR and CNR; Wilcoxon signed-rank test for VA; Pearson's correlation and Bland-Altman plot analysis for ADC; and McNemar test and receiver operating characteristic analysis and Delong test for diagnostic performance.

RESULTS

Regarding b1000, CNR and visual score were significantly higher in short TR compared with long TR (P = .003 and P = .002, respectively), without significant difference in SNR (P = .21). Considering b2000, there was no significant difference in visual score between short and long TR (P = .07). However, SNR and CNR in long TR were higher (P = .01 and P = .04, respectively). ADC showed significant correlations, without apparent bias for ADC between short and long TR for both b-values. For diagnostic performance of DWI between short and long TR for both b-values, one out of five readers noted a significant difference, with the short TR for both b-values demonstrating superior performance.

CONCLUSIONS

Our data showed that the short TR DWI1000 may provide better image quality than did the long TR DWI1000 and may improve visualization and diagnostic performance of PCa for readers.

Two resected cases of benign adenomyoepithelioma

BACKGROUND

Adenomyoepithelioma (AME) of the breast is an uncommon tumor characterized by the proliferation of ductal epithelial and myoepithelial cells with the heterogeneity. Although benign AME is relatively easy to differentiate from breast cancer by core needle biopsy (CNB) alone, a definitive diagnosis is often difficult. The imaging findings of AME are also variable, and there are particularly few reports about radiological features, including contrast-enhanced magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) values in AME.

CASE PRESENTATION

We present two cases of benign AME. Case 1 is a 30-year-old woman with a history of asthma. The cystic tumor shows smooth borders, and the intracystic solid component is irregular in shape and high vascularity. The pathological findings of the tumor were benign on CNB. The MRI scan showed a decreased ADC value. Case 2 is a 60-year-old woman with only a history of arrhythmia. The tumor shows a lobulated mass with cystic space and coarse calcifications. The pathological findings of the tumor were found to be benign by CNB. Dynamic MRI scan showed a fast washout pattern with a decreased ADC value. Both patients underwent excisional biopsy to confirm the diagnosis, and the pathological diagnosis was benign AME in both cases.

CONCLUSIONS

The AME of the breast has little specific imaging information, so it can be difficult to diagnose based on pathological findings of biopsy specimen. In our case, the ADC values were exceptionally low, contrary to previous reports. It is essential to carefully diagnose AME, considering the discrepancies in imaging findings observed in this case.

Clinical Value of a Nomogram Model Based on Apparent Diffusion Coefficient Values Within 1 cm of the Tumor Cavity to Predict Postoperative Progression of Glioma

OBJECTIVE

To explore the clinical value of constructing a nomogram model based on apparent diffusion coefficient values within 1 cm of the residual tumor cavity to predict the postoperative progression of gliomas.

METHODS

Clinical data of patients with glioma who underwent surgery were retrospectively retrieved from the First Hospital of Qinhuangdao. The mean apparent diffusion coefficient (mADC) was measured using a picture archiving and communication system. The Kaplan-Meier survival curve was constructed with the optimal mADC threshold determined by the X-tile. A nomogram was developed based on the independent risk factors determined using the Cox proportional hazards model (Cox regression model) to predict the progression of postoperative glioma. A receiver operating characteristic curve was drawn to evaluate the prediction accuracy of the model, and decision curve analysis was performed to assess the clinical value of the nomogram.

RESULTS

There was good agreement between the mADC values of the 2 repeated measurements before and after, with a consistency correlation coefficient of 0.83. Multivariate Cox regression analysis showed that peritumoral mADC values, degree of peritumoral enhancement, age, pathological grading, and degree of tumor resection were independent risk factors for predicting postoperative progression of glioma (all P < 0.05). The receiver operating characteristic curves of the nomogram predicting 1, 2, and 3 years postoperative progression were 0.86, 0.82, and 0.91, respectively. The calibration curve showed good consistency between the observed and predicted values in the model. The curve showed that the nomogram model has a good clinical application value.

CONCLUSIONS

The peritumoral mADC values, degree of peritumoral enhancement, age, pathological grade, and degree of tumor resection were independent factors affecting the postoperative progression of glioma. The nomogram model established for the first time based on mADC values within 1 cm of the tumor can predict the postoperative condition of patients with glioma intuitively and comprehensively. It can provide a relatively accurate prediction tool for neurosurgeons to individualize the evaluation of survival and prognosis, and formulate treatment plans for patients.

Apparent diffusion coefficient histogram analysis for differentiating fibroblastic meningiomas from non-fibroblastic WHO grade 1 meningiomas

PURPOSE

To investigate the role of apparent diffusion coefficient (ADC) histogram analysis in differentiating fibroblastic meningiomas (FM) from non-fibroblastic WHO grade 1 meningiomas (nFM).

METHODS

This retrospective study analyzed the histopathological and diagnostic imaging data of 220 patients with histopathologically confirmed FM and nFM. The whole tumors were delineated on axial ADC images, and histogram parameters (mean, variance, skewness, kurtosis, as well as the 1st, 10th, 50th, 90th, and 99th percentile ADC [ADCp1, ADCp10, ADCp50, ADCp90, and ADCp99, respectively]) were obtained. Multivariate logistic regression analysis was used to identify the most valuable variables for discriminating FM from nFM WHO grade 1 meningiomas, and their diagnostic efficacy in differentiating FM from nFM before surgery was assessed using receiver operating characteristic (ROC) curves.

RESULTS

The mean, variance, ADCp50, ADCp90, and ADCp99 of the FM group were all lower than those of the nFM group (P < 0.05), there was significant difference in location and sex (P < 0.05). Multivariate logistic regression showed ADCp99 (P < 0.001) and location (P = 0.007) were the most valuable parameters in the discrimination of FM and nFM WHO grade 1 meningiomas. The diagnostic efficacy was achieved an AUC of 0.817(95% CI, 0.759-0.866), the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 66.4%, 83.6%, 75.0%, 80.2%, and 71.3%, respectively.

CONCLUSION

ADC histogram analysis is helpful in noninvasive differentiation of FM and nFM WHO grade 1 meningiomas, and combined ADCp99 and location have the best diagnostic efficacy.

The Added Value of ADC-based Nomogram in Assessing the Depth of Myometrial Invasion of Endometrial Endometrioid Adenocarcinoma

RATIONALE AND OBJECTIVES

To explore the potential value of the apparent diffusion coefficient (ADC)-based nomogram models in preoperatively assessing the depth of myometrial invasion of endometrial endometrioid adenocarcinoma (EEA).

MATERIALS AND METHODS

Preoperative magnetic resonance imaging (MRI) of 210 EEA patients were retrospectively analyzed. ADC histogram metrics derive from the whole-tumor regions of interest. Univariate and multivariate analyses were used to screen the ADC histogram metrics and clinical characteristics for nomogram model building. The diagnostic sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of two radiologists without and with the assistance of models were calculated and compared.

RESULTS

Two nomogram models were developed for predicting no myometrial invasion (NMI) and deep myometrial invasion (DMI) with area under the curves of 0.85 and 0.82, respectively. With the assistance of models, the overall accuracies were significantly improved [radiologist_1, 73.3% vs 86.2% (p = 0.001); radiologist_2, 80.0% vs 91.0% (p = 0.002)]. In determining NMI, the sensitivity and PPV were greatly improved but not significant for radiologist_1 (51.9% vs 77.8% and 46.7% vs 75.0%, p = 0.229 and 0.511), and under/near the significance level for radiologist_2 (59.3% vs 88.9% and 57.1% vs 82.8%, p = 0.041 and 0.065), while the specificity, accuracy, and NPV were significantly improved (all p < 0.001). In determining DMI, all sensitivity, specificity, accuracy, PPV, and NPV were significantly improved (all p < 0.001).

CONCLUSION

The ADC-based nomogram models can improve the diagnostic performance of radiologist in preoperatively assessing the depth of myometrial invasion and facilitate optimizing clinical individualized treatment decisions.

A Study of Diffusion Tensor Imaging in Central Post-Stroke Pain: Traveling Beyond the Pain Pathways

Introduction

Central post-stroke pain (CPSP), seen in the aftermath of a stroke, is an underdiagnosed entity but quite a disabling complication. All the postulated theories regarding the pathogenesis of CPSP point to its origin in the central pain pathways. However, this study attempts to demonstrate the role of other contributing areas in the generation of CPSP.

Materials and Methods

In this single-center tertiary care hospital-based study, 24 patients with both ischemic and hemorrhagic strokes of variable durations were recruited, and Magnetic Resonance Imaging (MRI) imaging with diffusion tensor imaging (DTI) acquisition was done. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of the spinothalamic tract (STT), corticospinal tract (CST), superior thalamic radiation (STR), basal ganglia (BG), and primary somatosensory cortex (SSC) were compared between normal and abnormal sides and also in extrathalamic lesions separately.

Results

Significant differences with lower FA were noted in STT, CST, STR, and SSC and higher ADC values in BG, STR, CST, and SSC on comparison between the normal and lesion sides. On individual sub-analysis, ischemic stroke had significant changes in the FA value of CST and the ADC value of STR and CST, while hemorrhagic stroke had significant changes in the FA and ADC values of STR and SSC, as well as the FA value of STT. In the analysis of the extrathalamic strokes, significance persisted in all the studied parameters except the BG. The CST abnormalities were evident even in patients with clinical motor improvement. On multivariate analysis, visual analogue scale score severity was correlated with thalamic lesions.

Conclusion

Contrary to the belief that STT is solely responsible for CPSP, the role of CST, STR, BG, and SSC as contributing areas is evident from this study and may be more well established if studied in a larger population.

Clinical feasibility of deep learning reconstruction in liver diffusion-weighted imaging: Improvement of image quality and impact on apparent diffusion coefficient value

PURPOSE

Diffusion-weighted imaging (DWI) of the liver suffers from low resolution, noise, and artifacts. This study aimed to investigate the effect of deep learning reconstruction (DLR) on image quality and apparent diffusion coefficient (ADC) quantification of liver DWI at 3 Tesla.

METHOD

In this prospective study, images of the liver obtained at DWI with b-values of 0 (DWI0), 50 (DWI50) and 800 s/mm2 (DWI800) from consecutive patients with liver lesions from February 2022 to February 2023 were reconstructed with and without DLR (non-DLR). Image quality was assessed qualitatively using Likert scoring system and quantitatively using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and liver/parenchyma boundary sharpness from region-of-interest (ROI) analysis. ADC value of lesion were measured. Phantom experiment was also performed to investigate the factors that determine the effect of DLR on ADC value. Qualitative score, SNR, CNR, boundary sharpness, and apparent diffusion coefficients (ADCs) for DWI were compared using paired t-test and Wilcoxon signed rank test. P < 0.05 was considered statistically significant.

RESULTS

A total of 85 patients with 170 lesions were included. DLR group showed a higher qualitative score than the non-DLR group. for example, with DWI800 the score was 4.77 ± 0.52 versus 4.30 ± 0.63 (P < 0.001). DLR group also showed higher SNRs, CNRs and boundary sharpness than the non-DLR group. DLR reduced the ADC of malignant tumors (1.105[0.904, 1.340] versus 1.114[0.904, 1.320]) (P < 0.001), but there was no significant difference in the diagnostic value of malignancy for DLR and non-DLR groups (P = 57.3). The phantom study confirmed a reduction of ADC in images with low resolution, and a stronger reduction of ADC in heterogeneous structures than in homogeneous ones (P < 0.001).

CONCLUSIONS

DLR improved image quality of liver DWI. DLR reduced the ADC value of lesions, but did not affect the diagnostic performance of ADC in distinguishing malignant tumors on a 3.0-T MRI system.

Accurate, repeatable, and geometrically precise diffusion-weighted imaging on a 0.35 T magnetic resonance imaging-guided linear accelerator

Background and purpose

Diffusion weighted imaging (DWI) allows for the interrogation of tissue cellularity, which is a surrogate for cellular proliferation. Previous attempts to incorporate DWI into the workflow of a 0.35 T MR-linac (MRL) have lacked quantitative accuracy. In this study, accuracy, repeatability, and geometric precision of apparent diffusion coefficient (ADC) maps produced using an echo planar imaging (EPI)-based DWI protocol on the MRL system is illustrated, and in vivo potential for longitudinal patient imaging is demonstrated.

Materials and methods

Accuracy and repeatability were assessed by measuring ADC values in a diffusion phantom at three timepoints and comparing to reference ADC values. System-dependent geometric distortion was quantified by measuring the distance between 93 pairs of phantom features on ADC maps acquired on a 0.35 T MRL and a 3.0 T diagnostic scanner and comparing to spatially precise CT images. Additionally, for five sarcoma patients receiving radiotherapy on the MRL, same-day in vivo ADC maps were acquired on both systems, one of which at multiple timepoints.

Results

Phantom ADC quantification was accurate on the 0.35 T MRL with significant discrepancies only seen at high ADC. Average geometric distortions were 0.35 (±0.02) mm and 0.85 (±0.02) mm in the central slice and 0.66 (±0.04) mm and 2.14 (±0.07) mm at 5.4 cm off-center for the MRL and diagnostic system, respectively. In the sarcoma patients, a mean pretreatment ADC of 910x10-6 (±100x10-6) mm2/s was measured on the MRL.

Conclusions

The acquisition of accurate, repeatable, and geometrically precise ADC maps is possible at 0.35 T with an EPI approach.

Correlation between synthetic MRI relaxometry and apparent diffusion coefficient in breast cancer subtypes with different neoadjuvant therapy response

BACKGROUND

To evaluate the correlation between synthetic MRI (syMRI) relaxometry and apparent diffusion coefficient (ADC) maps in different breast cancer subtypes and treatment response subgroups.

METHODS

Two hundred sixty-three neoadjuvant therapy (NAT)-treated breast cancer patients with baseline MRI were enrolled. Tumor annotations were obtained by drawing regions of interest (ROIs) along the lesion on T1/T2/PD and ADC maps respectively. Histogram features from T1/T2/PD and ADC maps were respectively calculated, and the correlation between each pair of identical features was analyzed. Meanwhile, features between different NAT treatment response groups were compared, and their discriminatory power was evaluated.

RESULTS

Among all patients, 20 out of 27 pairs of features weakly correlated (r = - 0.13-0.30). For triple-negative breast cancer (TNBC), features from PD map in the pathological complete response (pCR) group (r = 0.60-0.86) showed higher correlation with ADC than that of the non-pCR group (r = 0.30-0.43), and the mean from the ADC and PD maps in the pCR group strongly correlated (r = 0.86). For HER2-positive, few correlations were found both in the pCR and non-pCR groups. For luminal HER2-negative, T2 map correlated more with ADC than T1 and PD maps. Significant differences were seen in T2 low percentiles and median in the luminal-HER2 negative subtype, yielding moderate AUCs (0.68/0.72/0.71).

CONCLUSIONS

The relationship between ADC and PD maps in TNBC may indicate different NAT responses. The no-to-weak correlation between the ADC and syMRI suggests their complementary roles in tumor microenvironment evaluation.

CRITICAL RELEVANCE STATEMENT

The relationship between ADC and PD maps in TNBC may indicate different NAT responses, and the no-to-weak correlation between the ADC and syMRI suggests their complementary roles in tumor microenvironment evaluation.

KEY POINTS

• The relationship between ADC and PD in TNBC indicates different NAT responses. • The no-to-weak correlations between ADC and syMRI complementarily evaluate tumor microenvironment. • T2 low percentiles and median predict NAT response in luminal-HER2-negative subtype.

Whole-tumor histogram analysis of multi-parametric MRI for differentiating brain metastases histological subtypes in lung cancers: relationship with the Ki-67 proliferation index

This study aims to investigate the predictive value of preoperative whole-tumor histogram analysis of multi-parametric MRI for histological subtypes in patients with lung cancer brain metastases (BMs) and explore the correlation between histogram parameters and Ki-67 proliferation index. The preoperative MRI data of 95 lung cancer BM lesions obtained from 73 patients (42 men and 31 women) were retrospectively analyzed. Multi-parametric MRI histogram was used to distinguish small-cell lung cancer (SCLC) from non-small cell lung cancer (NSCLC), and adenocarcinoma (AC) from squamous cell carcinoma (SCC), respectively. The T1-weighted contrast-enhanced (T1C) and apparent diffusion coefficient (ADC) histogram parameters of the volumes of interest (VOIs) in all BMs lesions were extracted using FireVoxel software. The following histogram parameters were obtained: maximum, minimum, mean, standard deviation (SD), variance, coefficient of variation (CV), skewness, kurtosis, entropy, and 1st-99th percentiles. Then investigated their relationship with the Ki-67 proliferation index. The skewness-T1C, kurtosis-T1C, minimum-ADC, mean-ADC, CV-ADC and 1st - 90th ADC percentiles were significantly different between the SCLC and NSCLC groups (all p < 0.05). When the 10th-ADC percentile was 668, the sensitivity, specificity, and accuracy (90.80%, 76.70% and 86.32%, respectively) for distinguishing SCLC from NSCLC reached their maximum values, with an AUC of 0.895 (0.824 - 0.966). Mean-T1C, CV-T1C, skewness-T1C, 1st - 50th T1C percentiles, maximum-ADC, SD-ADC, variance-ADC and 75th - 99th ADC percentiles were significantly different between the AC and SCC groups (all p < 0.05). When the CV-T1C percentiles was 3.13, the sensitivity, specificity and accuracy (75.00%, 75.60% and 75.38%, respectively) for distinguishing AC and SCC reached their maximum values, with an AUC of 0.829 (0.728-0.929). The 5th-ADC and 10th-ADC percentiles were strongly correlated with the Ki-67 proliferation index in BMs. Multi-parametric MRI histogram parameters can be used to identify the histological subtypes of lung cancer BMs and predict the Ki-67 proliferation index.

Analysis of Pancreatobiliary and Intestinal Type Periampullary Carcinomas Using Volumetric Apparent Diffusion Coefficient Histograms

RATIONALE AND OBJECTIVES

Magnetic resonance imaging plays an important role in the evaluation of patients with known or suspected periampullary masses. The utilization of volumetric apparent diffusion coefficient (ADC) histogram evaluation for the entire lesion eradicates the potential for subjectivity in the region of interest placement, thus guaranteeing the accuracy of computation and repeatability.

PURPOSE

To investigate the value of volumetric ADC histogram analysis in the differentiation of intestinal-type (IPAC) and pancreatobiliary-type periampullary adenocarcinomas (PPAC).

MATERIALS AND METHODS

This retrospective study included 69 patients with histopathologically confirmed periampullary adenocarcinoma (54 PPAC and 15 IPAC). Diffusion-weighted imaging was obtained at b values of 1000 mm²/s. The histogram parameters of ADC values, comprising the mean, minimum, maximum, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles, as well as skewness, kurtosis, and variance, were calculated independently by two radiologists. Using the interclass correlation coefficient, the interobserver agreement was evaluated.

RESULTS

The ADC parameters for the PPAC group were all lower than those of the IPAC group. The PPAC group had higher variance, skewness, and kurtosis than the IPAC group. However, the difference between the kurtosis (P = .003), the 5th (P = .032), 10th (P = .043), and 25th (P = .037) percentiles of ADC values was statistically significant. The area under the curve (AUC) of the kurtosis was the highest (AUC=0.752; cut-off value=-0.235; sensitivity=61.1%; specificity=80.0%).

CONCLUSION

Volumetric ADC histogram analysis with b values of 1000 mm²/s can discriminate subtypes noninvasively before surgery.

Association of quantifiable prostate MRI parameters with any and large cribriform pattern in prostate cancer patients undergoing radical prostatectomy

PURPOSE

Cribriform pattern has recently been recognized as an important independent risk factor for prostate cancer (PCa) outcome. This study aimed to identify the association of quantifiable prostate magnetic resonance imaging (MRI) parameters with any and large cribriform pattern at radical prostatectomy (RP) specimens.

METHODS

Preoperative prostate MRI's from 188 men undergoing RP between 2010 and 2018 were retrospectively acquired. RP specimens of the patients were revised for Gleason score (GS), and presence of any and large cribriform pattern. MRI parameters such as MRI visibility, PI-RADS score, lowest apparent diffusion coefficient (ADC) value, lesion size, and radiologic extra-prostatic extension (EPE) were reviewed. The association of prostate MRI parameters for presence of any and large cribriform pattern at RP was analysed using logistic regression.

RESULTS

116/188 (61.7%) PCa patients had any cribriform and 36/188 (19.1%) large cribriform pattern at RP. 171/188 (91.0%) men had MRI-visible lesions; 111/116 (95.7%) tumours with any and 36/36 (100%) with large cribriform pattern were visible at MRI. PCa with any and large cribriform pattern both had lower ADC values than those without (p < 0.001). In adjusted analysis, lowest ADC value was as an independent predictor for any cribriform (Odds Ratio (OR) 0.2, 95% Confidence Interval (CI) 0.1-0.8; p = 0.01) and large cribriform pattern (OR 0.2, 95% CI 0.1-0.7; p = 0.01), while other parameters were not.

CONCLUSIONS

The majority of PCa with cribriform pattern at RP were visible at MRI, and lowest ADC value was an independent predictor for both any and large cribriform pattern.

Relationship between apparent diffusion coefficient and survival as a function of distance from gross tumor volume on radiation planning MRI in newly diagnosed glioblastoma

PURPOSE

To investigate the changes in apparent diffusion coefficient (ADC) within incrementally-increased margins beyond the gross tumor volume (GTV) on post-operative radiation planning MRI and their prognostic utility in glioblastoma.

METHODS

Radiation planning MRIs of adult patients with newly diagnosed glioblastoma from 2017 to 2020 were assessed. The ADC values were normalized to contralateral normal white matter (nADC). Using 1 mm isotropic incremental margin increases from the GTV, the nADC values were calculated at each increment. Age, ECOG performance status, extent of resection and MGMT promoter methylation status were obtained from medical records. Using univariate and multivariable Cox regression analysis, association of nADC to progression-free and overall survival (PFS, OS) was assessed at each increment.

RESULTS

Seventy consecutive patients with mean age of 53.6 ± 10.3 years, were evaluated. The MGMT promoter was methylated in 31 (44.3%), unmethylated in 36 (51.6%) and unknown in 3 (4.3%) patients. 11 (16%) underwent biopsy, 41 (44%) subtotal resection and 18 (26%) gross total resection. For each 1 mm increase in distance from GTV, the nADC decreased by 0.16% (p < 0.0001). At 1-5 mm increment, the nADC was associated with OS (p < 0.01). From 6 to 11 mm increment the nADC was associated with OS with the p-value gradually increasing from 0.018 to 0.046. nADC was not associated with PFS.

CONCLUSION

The nADC values at 1-11 mm increments from the GTV margin were associated with OS. Future prospective multicenter studies are needed to validate the findings and to pave the way for the utilization of ADC for margin reduction in radiation planning.

Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group

BACKGROUND AND PURPOSE

The apparent diffusion coefficient (ADC), a potential imaging biomarker for radiotherapy response, needs to be reproducible before translation into clinical use. The aim of this study was to evaluate the multi-centre delineation- and calculation-related ADC variation and give recommendations to minimize it.

MATERIALS AND METHODS

Nine centres received identical diffusion-weighted and anatomical magnetic resonance images of different cancerous tumours (adrenal gland, pelvic oligo metastasis, pancreas, and prostate). All centres delineated the gross tumour volume (GTV), clinical target volume (CTV), and viable tumour volume (VTV), and calculated ADCs using both their local calculation methods and each of the following calculation conditions: b-values 0-500 vs. 150-500 s/mm2, region-of-interest (ROI)-based vs. voxel-based calculation, and mean vs. median. ADC variation was assessed using the mean coefficient of variation across delineations (CVD) and calculation methods (CVC). Absolute ADC differences between calculation conditions were evaluated using Friedman's test. Recommendations for ADC calculation were formulated based on observations and discussions within the Elekta MRI-linac consortium image analysis working group.

RESULTS

The median (range) CVD and CVC were 0.06 (0.02-0.32) and 0.17 (0.08-0.26), respectively. The ADC estimates differed 18% between b-value sets and 4% between ROI/voxel-based calculation (p-values < 0.01). No significant difference was observed between mean and median (p = 0.64). Aligning calculation conditions between centres reduced CVC to 0.04 (0.01-0.16). CVD was comparable between ROI types.

CONCLUSION

Overall, calculation methods had a larger impact on ADC reproducibility compared to delineation. Based on the results, significant sources of variation were identified, which should be considered when initiating new studies, in particular multi-centre investigations.

Prospective evaluation of in vivo and phantom repeatability and reproducibility of diffusion-weighted MRI sequences on 1.5 T MRI-linear accelerator (MR-Linac) and MR simulator devices for head and neck cancers

INTRODUCTION

Diffusion-weighted imaging (DWI) on MRI-linear accelerator (MR-linac) systems can potentially be used for monitoring treatment response and adaptive radiotherapy in head and neck cancers (HNC) but requires extensive validation. We performed technical validation to compare six total DWI sequences on an MR-linac and MR simulator (MR sim) in patients, volunteers, and phantoms.

METHODS

Ten human papillomavirus-positive oropharyngeal cancer patients and ten healthy volunteers underwent DWI on a 1.5 T MR-linac with three DWI sequences: echo planar imaging (EPI), split acquisition of fast spin echo signals (SPLICE), and turbo spin echo (TSE). Volunteers were also imaged on a 1.5 T MR sim with three sequences: EPI, BLADE (vendor tradename), and readout segmentation of long variable echo trains (RESOLVE). Participants underwent two scan sessions per device and two repeats of each sequence per session. Repeatability and reproducibility within-subject coefficient of variation (wCV) of mean ADC were calculated for tumors and lymph nodes (patients) and parotid glands (volunteers). ADC bias, repeatability/reproducibility metrics, SNR, and geometric distortion were quantified using a phantom.

RESULTS

In vivo repeatability/reproducibility wCV for parotids were 5.41%/6.72%, 3.83%/8.80%, 5.66%/10.03%, 3.44%/5.70%, 5.04%/5.66%, 4.23%/7.36% for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE. Repeatability/reproducibility wCV for EPIMR-linac, SPLICE, TSE were 9.64%/10.28%, 7.84%/8.96%, 7.60%/11.68% for tumors and 7.80%/9.95%, 7.23%/8.48%, 10.82%/10.44% for nodes. All sequences except TSE had phantom ADC biases within ± 0.1x10-3 mm2/s for most vials (EPIMR-linac, SPLICE, and BLADE had 2, 3, and 1 vials out of 13 with larger biases, respectively). SNR of b = 0 images was 87.3, 180.5, 161.3, 171.0, 171.9, 130.2 for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE.

CONCLUSION

MR-linac DWI sequences demonstrated near-comparable performance to MR sim sequences and warrant further clinical validation for treatment response assessment in HNC.

Application value of simultaneous multislice readout-segmented echo-planar imaging for diffusion-weighted MRI in differentiation of rectal cancer grade

OBJECTIVE

To analyze the association of apparent diffusion coefficient (ADC) values measured by readout-segmented echo-planar imaging (rs-EPI) using different simultaneous multislice (SMS) acceleration factors and the differentiation of rectal cancer grade.

MATERIALS AND METHODS

Patients with non-mucinous rectal adenocarcinoma diagnosed by biopsy (endoscope-guided biopsy or surgical resection) were retrospectively collected, and each patient underwent an MRI examination. ADC values of rs-EPI, 2 × SMS rs-EPI, and 3 × SMS rs-EPI were recorded as ADC1, ADC2, and ADC3, respectively.

RESULTS

The scanning time of 2 × SMS rs-EPI was 60 s, 56.2% shorter than 137 s of rs-EPI sequence, while that of 3 × SMS rs-EPI was 51 s, 72.8% less than that of rs-EPI time. The ADC value of the three groups dropped with the decrease in cancer grade (p < 0.05). The AUC values of ADC1, ADC2, and ADC3 in predicting highly differentiated rectal cancer were 0.74, 0.729, and 0.687, respectively. The difference in AUC values between ADC1 and ADC2 was not statistically significant (p = 0.889).

DISCUSSION

SMS technology with an acceleration factor of 2 could be applied clinically to evaluate the pathological differentiation of rectal cancer grade.

Same-day repeatability and Between-Sequence reproducibility of Mean ADC in PI-RADS lesions

PURPOSE

This study aimed to assess repeatability after repositioning (inter-scan), intra-rater, inter-rater and inter-sequence variability of mean apparent diffusion coefficient (ADC) measurements in MRI-detected prostate lesions.

METHOD

Forty-three patients with suspicion for prostate cancer were included and received a clinical prostate bi-/multiparametric MRI examination with repeat scans of the T2-weighted and two DWI-weighted sequences (ssEPI and rsEPI). Two raters (R1 and R2) performed single-slice, 2D regions of interest (2D-ROIs) and 3D-segmentation-ROIs (3D-ROIs). Mean bias, corresponding limits of agreement (LoA), mean absolute difference, within-subject coefficient of variation (CoV) and repeatability/reproducibility coefficient (RC/RDC) were calculated. Bradley & Blackwood test was used for variance comparison. Linear mixed models (LMM) were used to account for multiple lesions per patient.

RESULTS

Inter-scan repeatability, intra-rater and inter-sequence reproducibility analysis of ADC showed no significant bias. 3D-ROIs demonstrated significantly less variability than 2D-ROIs (p < 0.01). Inter-rater comparison demonstrated small significant systematic bias of 57 × 10-6 mm2/s for 3D-ROIs (p < 0.001). Intra-rater RC, with the lowest variation, was 145 and 189 × 10-6 mm2/s for 3D- and 2D-ROIs, respectively. For 3D-ROIs of ssEPI, RCs and RDCs were 190-198 × 10-6 mm2/s for inter-scan, inter-rater and inter-sequence variation. No significant differences were found for inter-scan, inter-rater and inter-sequence variability.

CONCLUSIONS

In a single-scanner setting, single-slice ADC measurements showed considerable variation, which may be lowered using 3D-ROIs. For 3D-ROIs, we propose a cut-off of ∼ 200 × 10-6 mm2/s for differences introduced by repositioning, rater or sequence effects. The results suggest that follow-up measurements should be possible by different raters or sequences.

Objective Value of the Apparent Diffusion Coefficient (ADC) Map from Ultrahigh b-value Diffusion-weighted Imaging (DWI) in 3T MRI could be a Non-invasive Specific Biomarker for Prostate Cancer

OBJECTIVE

This article aims to explore the ADC value of ultrahigh b-value DWI and the diagnostic cutoff point in prostate cancer.

METHODS

A total of 78 patients were included in this study. T2 weighted imaging (T2WI), conventional diffusion-weighted imaging (DWI) (1000 s/mm2), and DWI with ultrahigh b-values of 2000 s/mm2 and 3000 s/mm2 were performed in each patient. With reference biopsy as the gold standard, the apparent diffusion coefficient (ADC)s of each b-value DWI image were analyzed. According to different b-value receiver operating characteristic (ROC) curves, the ADC diagnostic cutoff point for prostate cancer was determined.

RESULTS

A total of 154 lesions were identified as prostate cancer. The ADC values for conventional DWI and ultrahigh b-value DWI with 2000 s/mm2 and 3000 s/mm2 were 1.097×10-3 mm2/s (1.040-1.153), 0.809×10-3 mm2/s (0.766-0.851) and 0.622×10-3 mm2/s (0.591-0.652), respectively, in the peripheral zone and 1.085×10-3 mm2/s (1.022-1.147), 0.815×10-3 mm2/s (0.770-0.861) and 0.651×10-3 mm2/s (0.617-0.685) in the transition zone. The area under the curve (AUC)s of the ADC values from ultrahigh b-value DWI (2000 s/mm2 and 3000 s/mm2) were 0.824 and 0.852 in the peripheral zone and 0.905 for the ADC values from ultrahigh b-value DWI (3000 s/mm2) in the transition zone. In the peripheral zone, the ADC diagnostic cutoff values for prostate cancer were 0.75×10-3 mm2/s and 0.685×10-3 mm2/s in DWI at 2000 s/mm2 and 3000 s/mm2, respectively, and the diagnosis of transition zone cancer was 0.8×10-3 mm2/s and 0.634×10-3 mm2/s, respectively.

CONCLUSION

The ADC values from ultrahigh b-value DWI demonstrated better consistency and diagnostic efficacy in the diagnosis of prostate cancer.

Variabilities in apparent diffusion coefficient (ADC) measurements of the spleen and the paraspinal muscle: A single center large cohort study

Purpose

Evaluation of the variabilities in apparent diffusion coefficient (ADC) measurements of the spleen (ADC_spleen) and the paraspinal muscles (ADC_muscle) to identify the reference organ for normalizing the ADC from the abdominal diffusion weighted imaging (DWI).

Methods

Two MRI scanners, with 314 abdominal exams on the GE and 929 on the Siemens system, were used for MRI examinations including DWI (b-values, 50 and 800 s/mm²). For a subset of 73 exams on the Siemens system a second exam was conducted. Four regions of interest (ROIs) in each exam were placed to measure the ADC_spleen and the bilateral ADC_muscle. ADC variability between patients (on each scanner separately), ADC variability due to ROI placement between the two ROIs in each organ, and variability in the subset between the first and second exams were assessed.

Results

The ADC_spleen was more scattered and variable than the ADC_muscle in the comparability (n = 929 and 314 for two MRI scanners, respectively) and repeatability (n = 73) datasets. The Bland-Altmann bias and limits of agreement (LoAs) for the ADC_spleen (ICC, 0.47; CV, 0.070) and ADC_muscle (ICC, 0.67; CV, 0.023) in the repeatability datasets (n = 73) were -0.1 (-25.7%-25.6%) and -0.3 (-8.8%-8.1%), respectively. For the Siemens system, the Bland-Altmann bias and LoAs for the ADC_spleen (ICC, 0.72; CV, 0.061) and ADC_muscle (ICC, 0.53; CV, 0.030) in the comparability datasets (n = 929) were 2.1 (-20.0%-24.2%) and 0.7 (-10.0%-11.4%), respectively. Similar findings have been found in the GE system (n = 314). The CVs for the ADC_muscle measurements were lower than those of the ADC_spleen both in the repeatability and the comparability analyses (all p < 0.001).

Conclusion

Paraspinal muscles demonstrate better reference characteristics than the spleen in estimating ADC variability of abdominal DWI.

Utility of apparent diffusion coefficient histogram analysis in differentiating microcystic meningioma from intracranial solitary fibrous tumor

PURPOSE

To investigate the possibility of histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating microcystic meningioma (MM) from intracranial solitary fibrous tumor (SFT).

MATERIALS AND METHODS

Eighteen patients with MM and 23 patients with SFT were enrolled in this retrospective study. Conventional magnetic resonance imaging (MRI) features and nine ADC histogram parameters (including mean, 1st (ADC1), 10th (ADC10), 50th (ADC50), 90th (ADC90), and 99th (ADC99) percentiles ADC, as well as variance, skewness, and kurtosis) between MM and SFT were compared. The diagnostic performance of the optimal parameter was determined by the receiver operating characteristic analysis.

RESULTS

SFT showed a significantly lower mean, ADC1, ADC10, ADC50, ADC90, and ADC99 than MM (all P < 0.05). while no significant difference was found in conventional MRI features or other ADC histogram parameters (all P > 0.05). ADC1 was identified as the optimal parameter in differentiating between MM and SFT, which achieved an area under the curve of 0.861, with sensitivity, specificity, and accuracy of 78.26%, 88.89%, and 82.93%, respectively.

CONCLUSIONS

MM and SFT show overlapping conventional MRI features. ADC histogram analysis helps to differentiate between MM and SFT, with ADC1 being the optimal parameter with the best discrimination performance.

Detection of bone marrow metastases in children and young adults with solid cancers with diffusion-weighted MRI

OBJECTIVE

To compare the diagnostic accuracy of diffusion-weighted (DW)-MRI with b-values of 50 s/mm2 and 800 s/mm2 for the detection of bone marrow metastases in children and young adults with solid malignancies.

METHODS

In an institutional review board-approved prospective study, we performed 51 whole-body DW-MRI scans in 19 children and young adults (14 males, 5 females; age range: 1-25 years) with metastasized cancers before (n = 19 scans) and after (n = 32 scans) chemotherapy. Two readers determined the presence of focal bone marrow lesions in 10 anatomical areas. A third reader measured ADC and SNR of focal lesions and normal marrow. Simultaneously acquired 18F-FDG-PET scans served as the standard of reference. Data of b = 50 s/mm2 and 800 s/mm2 images were compared with the Wilcoxon signed-rank test. Inter-reader agreement was evaluated with weighted kappa statistics.

RESULTS

The SNR of bone marrow metastases was significantly higher compared to normal bone marrow on b = 50 s/mm2 (mean ± SD: 978.436 ± 1239.436 vs. 108.881 ± 109.813, p < 0.001) and b = 800 s/mm2 DW-MRI (499.638 ± 612.721 vs. 86.280 ± 89.120; p < 0.001). On 30 out of 32 post-treatment DW-MRI scans, reconverted marrow demonstrated low signal with low ADC values (0.385 × 10-3 ± 0.168 × 10-3mm2/s). The same number of metastases (556/588; 94.6%; p > 0.99) was detected on b = 50 s/mm2 and 800 s/mm2 images. However, both normal marrow and metastases exhibited low signals on ADC maps, limiting the ability to delineate metastases. The inter-reader agreement was substantial, with a weighted kappa of 0.783 and 0.778, respectively.

CONCLUSION

Bone marrow metastases in children and young adults can be equally well detected on b = 50 s/mm2 and 800 s/mm2 images, but ADC values can be misleading.

Dependence of apparent diffusion coefficient on slice position in magnetic resonance diffusion imaging

PURPOSE

The position dependence of the apparent diffusion coefficient (ADC) in magnetic resonance imaging (MRI) by echo-planar imaging (EPI)- and turbo spin echo (TSE)-diffusion-weighted imaging (DWI) was assessed using phantoms.

METHODS

Six pure water-filled containers were placed parallel to the direction of the static magnetic field from the center of the magnetic field to the foot direction (five containers) and the head direction (one container). Six slice positions were set, and a cross-section image was scanned at the center of each container using a 1.5-T MRI scanner. Diffusion times for both EPI- and TSE-DWI were matched as much as possible. The slice thickness was adjusted to match the signal-to-noise ratio (SNR) at the center of the magnetic field for both sequences. A B₁ map was analyzed. The ADC and SNR at each position of both sequences were tested using the Wilcoxon signed-rank test (P = 0.05) and compared using Friedman and Steel-Dwass multiple comparison tests (P = 0.05). Pearson correlation coefficients between ADC and SNR and between ADC and flip angle (FA) were calculated.

RESULTS

ADC decreased significantly with distance from the center of the magnetic field for both EPI-DWI and TSE-DWI (P < 0.05). TSE-ADC was significantly higher than EPI-ADC for all combinations (P < 0.01). Based on the Friedman test, the SNR of EPI- and TSE-DWI was significantly different and depended on the slice position (P < 0.01). The Pearson correlation coefficient between ADC and SNR was 0.78 in EPI-DWI and 0.60 in TSE-DWI, whereas that between ADC and FA was 0.97 in EPI-DWI and 0.94 in TSE-DWI. The FA decreased by 0.048 and 0.047° per mm from the center of the magnetic field to head and foot directions, respectively.

CONCLUSION

ADC depends on the slice position and decreases with an increase in distance from the magnetic field center. Caution should be taken when comparing and quantitatively evaluating the ADC at sites shifted in the long-axis direction.

Diffusion kurtosis imaging and diffusion weighted imaging comparison in diagnosis of early hypoxic-ischemic brain edema

BACKGROUND

Hypoxic-ischemic encephalopathy (HIE) refers to cerebral hypoxic-ischemic injury caused by asphyxia during perinatal period, which is one of the important causes of neonatal death and sequelae. Early and accurate diagnosis of HIE is of great significance for the prognostic evaluation of patients. The purpose of this study is to explore the efficacy of diffusion-kurtosis imaging (DKI) and diffusion-weighted imaging (DWI) in the diagnosis of early HIE.

METHODS

Twenty Yorkshire newborn piglets (3-5 days) were randomly divided into control group and experimental group. DWI and DKI scanning were performed at timepoints of 3, 6, 9, 12, 16, and 24 h after hypoxic-ischemic exposure. At each timepoint, the parameter values obtained by each group scan were measured, and the lesion area of the apparent diffusion coefficient (ADC) map and mean diffusion coefficient (MDC) map were measured. (For better interpretation of this study, we replaced the description of MD with MDC). Then, we completely removed the brain for pathological examination, and observed the state of cells and mitochondria in the ADC/MDC matching area (the actual area of the lesion), and the mismatch area (the area around the lesion).

RESULTS

In the experimental group, the ADC and MDC values decreased with time, but the MDC decreased more significantly and the change rate was higher. Both MDC and ADC values changed rapidly from 3 to 12 h and slowly from 12 to 24 h. The MDC and ADC images showed obvious lesions at 3 h for the first time. At this time, the area of ADC lesions was larger than that of MDC. As the lesions developed, the area of ADC maps was always larger than that of the MDC maps within 24 h. By observing the microstructure of the tissues by light microscopy, we found that the ADC and MDC matching area in the experimental group showed swelling of neurons, infiltration of inflammatory cells, and local necrotic lesions. Consistent with the observation under light microscope, pathological changes were observed in the matching ADC and MDC regions under electron microscopy as well, including collapse of mitochondrial membrane, fracture of partial mitochondrial ridge, and emergence of autophagosomes. In the mismatching region, the above pathological changes were not observed in the corresponding region of the ADC map.

CONCLUSIONS

DKI's characteristic parameter MDC is better than ADC (parameter of DWI) to reflect the real area of the lesion. Therefore, DKI is superior to DWI in diagnosing early HIE.

Clinical value of minimum apparent diffusion coefficient for prediction of clinically significant prostate cancer in the transition zone

BACKGROUND

This study investigated the association between apparent diffusion coefficients in Prostate Imaging Reporting and Data System 4/5 lesions and clinically significant prostate cancer in the transition zone.

METHODS

We included 102 patients who underwent transperineal cognitive fusion targeted biopsy for Prostate Imaging Reporting and Data System 4/5 lesions in the transition zone between 2016 and 2020. The association between apparent diffusion coefficients and prostate cancers in the transition zone was analyzed.

RESULTS

The detection rate of prostate cancer was 49% (50/102), including clinically significant prostate cancer in 37.3% (38/102) of patients. The minimum apparent diffusion coefficients in patients with clinically significant prostate cancer were 494.5 ± 133.6 µm2/s, which was significantly lower than 653.8 ± 172.5 µm2/s in patients with benign histology or clinically insignificant prostate cancer. Age, prostate volume, transition zone volume, and mean and minimum apparent diffusion coefficients were associated with clinically significant prostate cancer. Multivariate analysis demonstrated that only the minimum apparent diffusion coefficient value (odds ratio: 0.994; p < 0.001) was an independent predictor of clinically significant prostate cancer. When the cutoff value of the minimum apparent diffusion coefficient was less than 595 µm2/s, indicating the presence of prostate cancer in the transition zone, the detection rate increased to 59.2% (29/49) in this cohort.

CONCLUSION

The minimum apparent diffusion coefficient provided additional value to indicate the presence of clinically significant prostate cancer in the transition zone. It may help consider the need for subsequent biopsies in patients with Prostate Imaging Reporting and Data System 4/5 lesions and an initial negative targeted biopsy.

Predictive role of magnetic resonance imaging in the distinction of isocitrate dehydrogenase (IDH) mutant grade 4 astrocytomas versus glioblastomas

BACKGROUND

Isocitrate dehydrogenase (IDH) mutation status is a crucial prognostic factor in high-grade glial tumors.

PURPOSE

To investigate whether magnetic resonance imaging (MRI) features can display a diagnostic performance in the determination of IDH mutation in high-grade gliomas.

MATERIAL AND METHODS

A total of 170 patients including 24 IDH mutant grade 4 astrocytomas and 146 glioblastomas (GBM) were retrospectively examined via contrast-enhanced (CE) MRI before surgery. Immunohistochemistry and genomic sequence analyses were performed on specimen materials for the determination of IDH mutational status. Certain morphological and diffusion-weighted imaging (DWI) parameters were utilized to see if they could play a role to be non-invasive potential imaging predictors in the discrimination of IDH mutant versus wild-type (WT) high-grade gliomas.

RESULTS

On histopathological examination, IDH mutation was detected in 24 patients with high-grade glioma and 146 of the patients were found to be WT. Certain morphological criteria of tumor location and involvement, tumor margins, visual detection of diffusion restriction on DWI, and quantitative apparent diffusion coefficient (ADC) parameters consisting of ADC_mean, ADC_min, and ADC_r could be used as imaging predictors in the discrimination of high-grade IDH mutant versus WT tumors.

CONCLUSION

Certain MRI morphologic features and visual detection of diffusion restriction on DWI and quantitative ADC parameters consisting of ADC_mean, ADC_min, and ADC_r can be considered non-invasive, significant independent imaging predictors in the discrimination and can obviate invasive procedures for histopathological diagnosis.

Diffusion-weighted MRI for predicting and assessing treatment response of liver metastases from CRC - A systematic review and meta-analysis

The evaluation of response to chemotherapy and targeted therapies in colorectal liver metastases has traditionally been based on size changes, as per the RECIST criteria. However, therapy may alter tissue composition and not only tumor size, therefore, functional imaging techniques such as diffusion-weighted magnetic resonance imaging (DWI) may offer a more comprehensive assessment of treatment response. The aim of this systematic review and meta-analysis was to evaluate the use of DWI in the prediction and assessment of response to treatment in colorectal liver metastases and to determine if there is a baseline apparent diffusion coefficient (ADC) cut-off value that can predict a favorable response. A literature search was conducted using the MEDLINE/PubMed database, and risk of bias was evaluated using the QUADAS-2 tool. The mean differences between responders and non-responders were pooled. A total of 16 studies met the inclusion criteria, and various diffusion-derived techniques and coefficients were found to have potential for predicting and assessing treatment response. However, discrepancies were noted between studies. The most consistent predictor of response was a lower baseline ADC value calculated using traditional mono-exponential methods. Non-mono-exponential techniques for calculating DWI-derived parameters were also reported. A meta-analysis of a subset of studies failed to establish a cut-off value of ADC due to heterogeneity, but revealed a pooled mean difference of -0.12 × 10^-3 mm²/s between responders and non-responders. The results of this systematic review suggest that diffusion-derived techniques and coefficients may contribute to the evaluation and prediction of treatment response in colorectal liver metastases. Further controlled prospective studies are needed to confirm these findings and to guide clinical and radiological decision-making in the management of patients with CRC liver metastases.

Apparent diffusion coefficient values effectively predict cell proliferation and determine oligodendroglioma grade

This study aims to evaluate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) values in differentiating oligodendroglioma of various grades and explore the correlation between ADC and Ki-67. The preoperative MRI data of 99 patients with World Health Organization (WHO) grades 2 (n = 42) and 3 (n = 57) oligodendroglioma confirmed by surgery and pathology were retrospectively analyzed. Conventional MRI features, ADCmean, ADCmin, and normalized ADC (nADC) were compared between the two groups. A receiver operating characteristic curve was used to evaluate each parameter's diagnostic efficacy in differentiating the two tumor types. Each tumor's Ki-67 proliferation index was also measured to explore its relationship with the ADC value. Compared with WHO2 grade tumors, WHO3 grade tumors had a larger maximum diameter and more significant cystic degeneration/necrosis, edema, and moderate/severe enhancement (all P < 0.05). The ADCmin, ADCmean, and nADC values of the WHO3 and WHO2 grade tumors were significantly different, and the ADCmin value most accurately distinguished the two tumor types, yielding an area under the curve value of 0.980. When 0.96 × 10^-3 mm²/s was used as the differential diagnosis threshold, the sensitivity, specificity, and accuracy of the two groups were 100%, 93.00%, and 96.96%, respectively. The ADCmin (r = -0.596), ADCmean (r =  - 0.590), nADC (r =  - 0.577), and Ki-67 proliferation index values had significantly negative correlations (all P < 0.05). Conventional MRI features and ADC values are beneficial in the noninvasive prediction of the WHO grade and tumor proliferation rate of oligodendroglioma.

Apparent diffusion coefficients of 31P metabolites in the human calf muscle at 7 T

PURPOSE

In this study, we aimed to measure the apparent diffusion coefficients (ADCs) of major phosphorous metabolites in the human calf muscle at 7 T with a diffusion-weighted (DW)-STEAM sequence.

METHODS

A DW-STEAM sequence with bipolar gradients was implemented at 7 T, and DW MR spectra were acquired in three orthogonal directions in the human calf muscle of six healthy volunteers (TE/TM/TR = 15 ms/750 ms/5 s) at three b-values (0, 800, and 1200 s/mm²). Frequency and phase alignments were applied prior to spectral averaging. Averaged DW MR spectra were analyzed with LCModel, and ADCs of ³¹P metabolites were estimated.

RESULTS

Four metabolites (phosphocreatine (PCr), adenosine triphosphate (ATP), inorganic phosphate (Pi) and glycerol phosphorylcholine (GPC)) were quantified at all b-values with mean CRLBs below 10%. The ADC values of PCr, ATP, Pi, and GPC were (0.24 ± 0.02, 0.15 ± 0.04, 0.43 ± 0.14, 0.40 ± 0.09) × 10^-3 mm²/s, respectively.

CONCLUSION

The ADCs of four ³¹P metabolites were successfully measured in the human calf muscle at 7 T, among which those of ATP, Pi and GPC were reported for the first time in humans. This study paves the way to investigate ³¹P metabolite diffusion properties in health and disease on the clinical MR scanner.