Investigating the prediction value of multiparametric magnetic resonance imaging at 3 T in response to neoadjuvant chemotherapy in breast cancer

Objective

To explore the predictive value of parameters derived from diffusion-weighted imaging (DWI) and contrast-enhanced (CE)-MRI at different time-points during neoadjuvant chemotherapy (NACT) in breast cancer.

Methods

Institutional review board approval and written, informed consent from 42 breast cancer patients were obtained. The patients were investigated before and at three different time-points during neoadjuvant chemotherapy (NACT) using tumour diameter and volume from CE-MRI and ADC values obtained from drawn 2D and segmented 3D regions of interest. Prediction of pathologic complete response (pCR) was evaluated using the area under the curve (AUC) of receiver operating characteristic analysis.

Results

There was no significant difference between pathologic complete response and non-pCR in baseline size measures (p?>?0.39). Diameter change was significantly different in pCR (p?<?0.02) before the mid-therapy point. The best predictor was lesion diameter change observed before mid-therapy (AUC?=?0.93). Segmented volume was not able to differentiate between pCR and non-pCR at any time-point. The ADC values from 3D-ROI were not significantly different from 2D data (p?=?0.06). The best AUC (0.79) for pCR prediction using DWI was median ADC measured before mid-therapy of NACT.

Conclusions

The results of this study should be considered in NACT monitoring planning, especially in MRI protocol designing and time point selection.

Key Points

? Mid-therapy diameter changes are the best predictors of pCR in neoadjuvant chemotherapy. ? Volumetric measures are not strictly superior in therapy monitoring to lesion diameter. ? Size measures perform as a better predictor than ADC values.

     

Multiparametric voxel-based analyses of standardized uptake values and apparent diffusion coefficients of soft-tissue tumours with a positron emission tomography/magnetic resonance system: Preliminary results

Objectives

To investigate the usefulness of voxel-based analysis of standardized uptake values (SUVs) and apparent diffusion coefficients (ADCs) for evaluating soft-tissue tumour malignancy with a PET/MR system.

Methods

Thirty-five subjects with either ten low/intermediate-grade tumours or 25 high-grade tumours were prospectively enrolled. Zoomed diffusion-weighted and fluorodeoxyglucose (¹⁸FDG)-PET images were acquired along with fat-suppressed T2-weighted images (FST2WIs). Regions of interest (ROIs) were drawn on FST2WIs including the tumour in all slices. ROIs were pasted onto PET and ADC-maps to measure SUVs and ADCs within tumour ROIs. Tumour volume, SUVmax, ADCminimum, the heterogeneity and the correlation coefficients of SUV and ADC were recorded. The parameters of high- and low/intermediate-grade groups were compared, and receiver operating characteristic (ROC) analysis was also performed.

Results

The mean correlation coefficient for SUV and ADC in high-grade sarcomas was lower than that of low/intermediate-grade tumours (?0.41?±?0.25 vs. ?0.08?±?0.34, P?<?0.01). Other parameters did not differ significantly. ROC analysis demonstrated that correlation coefficient showed the best diagnostic performance for differentiating the two groups (AUC 0.79, sensitivity 96.0%, specificity 60%, accuracy 85.7%).

Conclusions

SUV and ADC determined via PET/MR may be useful for differentiating between high-grade and low/intermediate-grade soft tissue tumours.

Key Points

? PET/MR allows voxel-based comparison of SUVs and ADCs in soft-tissue tumours. ? A comprehensive assessment of internal heterogeneity was performed with scatter plots. ? SUVmax or ADCminimum could not differentiate high-grade sarcoma from low/intermediate-grade tumours. ? Only the correlation coefficient between SUV and ADC differentiated the two groups. ? The correlation coefficient showed the best diagnostic performance by ROC analysis.

     

Apparent diffusion coefficient measurements in diffusion-weighted magnetic resonance imaging of the anterior mediastinum: inter-observer reproducibility of five different methods of region-of-interest positioning

Objectives

To investigate inter-reader reproducibility of five different region-of-interest (ROI) protocols for apparent diffusion coefficient (ADC) measurements in the anterior mediastinum.

Methods

In eighty-one subjects, on ADC mapping, two readers measured the ADC using five methods of ROI positioning that encompassed the entire tissue (whole tissue volume [WTV], three slices observer-defined [TSOD], single-slice [SS]) or the more restricted areas (one small round ROI [OSR]), multiple small round ROI [MSR]). Inter-observer variability was assessed with interclass correlation coefficient (ICC), coefficient of variation (CoV), and Bland-Altman analysis. Nonparametric tests were performed to compare the ADC between ROI methods. The measurement time was recorded and compared between ROI methods.

Results

All methods showed excellent inter-reader agreement with best and worst reproducibility in WTV and OSR, respectively (ICC, 0.937/0.874; CoV, 7.3 %/16.8 %; limits of agreement, ±0.44/±0.77?×?10^-3 mm²/s). ADC values of OSR and MSR were significantly lower compared to the other methods in both readers (p?<?0.001). The SS and OSR methods required less measurement time (14?±?2 s) compared to the others (p?<?0.0001), while the WTV method required the longest measurement time (90?±?56 and 77?±?49 s for each reader) (p?<?0.0001).

Conclusions

All methods demonstrate excellent inter-observer reproducibility with the best agreement in WTV, although it requires the longest measurement time.

Key Points

? All ROI protocols show excellent inter-observer reproducibility. ? WTV measurements provide the most reproducible ADC values. ? ROI size and positioning influence ADC measurements in the anterior mediastinum. ? ADC values of OSR and MSR are significantly lower than other methods. ? OSR and WTV methods require the shortest and longest measurement time, respectively.

     

Potential of MR histogram analyses for prediction of response to chemotherapy in patients with colorectal hepatic metastases

Purpose

To determine if magnetic resonance imaging (MRI) histogram analyses can help predict response to chemotherapy in patients with colorectal hepatic metastases by using response evaluation criteria in solid tumours (RECIST1.1) as the reference standard.

Materials and methods

Standard MRI including diffusion-weighted imaging (b=0, 500 s/mm²) was performed before chemotherapy in 53 patients with colorectal hepatic metastases. Histograms were performed for apparent diffusion coefficient (ADC) maps, arterial, and portal venous phase images; thereafter, mean, percentiles (1st, 10th, 50th, 90th, 99th), skewness, kurtosis, and variance were generated. Quantitative histogram parameters were compared between responders (partial and complete response, n=15) and non-responders (progressive and stable disease, n=38). Receiver operator characteristics (ROC) analyses were further analyzed for the significant parameters.

Results

The mean, 1st percentile, 10th percentile, 50th percentile, 90th percentile, 99th percentile of the ADC maps were significantly lower in responding group than that in non-responding group (p=0.000–0.002) with area under the ROC curve (AUCs) of 0.76–0.82. The histogram parameters of arterial and portal venous phase showed no significant difference (p>0.05) between the two groups.

Conclusion

Histogram-derived parameters for ADC maps seem to be a promising tool for predicting response to chemotherapy in patients with colorectal hepatic metastases.

Key Points

? ADC histogram analyses can potentially predict chemotherapy response in colorectal liver metastases. ? Lower histogram-derived parameters (mean, percentiles) for ADC tend to have good response. ? MR enhancement histogram analyses are not reliable to predict response.

     

Hypervascular solid-appearing serous cystic neoplasms of the pancreas: Differential diagnosis with neuroendocrine tumours

Purpose

To describe imaging findings of arterial hypervascular solid-appearing serous cystic neoplasms (SCNs) of the pancreas on CT and MR and determine imaging features differentiating them from neuroendocrine tumours (NETs).

Materials and methods

We retrospectively identified 15 arterial hypervascular solid-appearing SCNs and randomly chose 30 size-matched pancreatic NETs. On CT, two radiologists in consensus assessed the size, morphology, and CT attenuation. On MR, predominant signal intensity and the amount of the cystic component on T2-weighted images and ADC maps were evaluated and compared using Fisher’s exact and Student’s t-test.

Results

The mean SCN size was 2.6 cm (range, 0.8–8.3). The CT findings were similar between the two tumours: location, shape, margin, and enhancement pattern. SCNs were significantly more hypodense on non-enhanced CT images than NETs (P?=?.03). They differed significantly on MR: bright signal intensity (P?=?.01) and more than a 10 % cystic component on T2-weighted images (P?=?.01) were more common in SCNs than in NETs. All SCNs showed a non-restrictive pattern on the ADC map, while NETs showed diffusion restriction (P?<?.01).

Conclusion

Arterial hypervascular solid-appearing SCNs and NETs share similar imaging features. Non-enhanced CT and MR images with T2-weighted images and ADC maps can facilitate the differentiation.

Key points

? Frequency of hypervascular solid-appearing SCNs was 7.3?% among surgically confirmed SCNs.? Hypervascular solid-appearing SCN of the pancreas can mimic pancreatic NETs.? Unenhanced CT and MR features help to differentiate the two tumours.

     

Differentiation of malignant from benign soft tissue tumours: use of additive qualitative and quantitative diffusion-weighted MR imaging to standard MR imaging at 3.0 T

Objectives

To determine the added value of diffusion-weighted imaging (DWI) to standard magnetic resonance imaging (MRI) to differentiate malignant from benign soft tissue tumours at 3.0 T.

Methods

3.0 T MR images including DWI in 63 patients who underwent surgery for soft tissue tumours were retrospectively analyzed. Two readers independently interpreted MRI for the presence of malignancy in two steps: standard MRI alone, standard MRI and DWI with qualitative and quantitative analysis combined.

Results

There were 34 malignant and 29 non-malignant soft tissue tumours. In qualitative analysis, hyperintensity relative to skeletal muscle was more frequent in malignant than benign tumours on DWI (P=0.003). In quantitative analysis, ADCs of malignant tumours were significantly lower than those of non-malignant tumours (P≤0.002): 759±385 vs. 1188±423 μm²/sec minimum ADC value, 941±440 vs. 1310±440 μm²/sec average ADC value. The mean sensitivity, specificity and accuracy of both readers were 96 %, 72 %, and 85 % on standard MRI alone and 97 %, 90 %, and 94 % on standard MRI with DWI.

Conclusions

The addition of DWI to standard MRI improves the diagnostic accuracy for differentiation of malignant from benign soft tissue tumours at 3.0 T.

Key Points

? DWI has added value for differentiating malignant from benign soft tissue tumours. ? Addition of DWI to standard MRI at 3.0 T improves the diagnostic accuracy. ? Measurements of both ADC _min within solid portion and ADC _av are helpful.

     

Diffusion-weighted (DW) MRI in lung cancers: ADC test-retest repeatability

Purpose

To determine the test-retest repeatability of Apparent Diffusion Coefficient (ADC) measurements across institutions and MRI vendors, plus investigate the effect of post-processing methodology on measurement precision.

Methods

Thirty malignant lung lesions >2 cm in size (23 patients) were scanned on two occasions, using echo-planar-Diffusion-Weighted (DW)-MRI to derive whole-tumour ADC (b?=?100, 500 and 800smm^-2). Scanning was performed at 4 institutions (3 MRI vendors). Whole-tumour volumes-of-interest were copied from first visit onto second visit images and from one post-processing platform to an open-source platform, to assess ADC repeatability and cross-platform reproducibility.

Results

Whole-tumour ADC values ranged from 0.66-1.94x10^-3mm²s^-1 (mean?=?1.14). Within-patient coefficient-of-variation (wCV) was 7.1% (95% CI 5.7–9.6%), limits-of-agreement (LoA) -18.0 to 21.9%. Lesions >3 cm had improved repeatability: wCV 3.9% (95% CI 2.9–5.9%); and LoA -10.2 to 11.4%. Variability for lesions <3 cm was 2.46 times higher. ADC reproducibility across different post-processing platforms was excellent: Pearson’s R²?=?0.99; CoV 2.8% (95% CI 2.3-3.4%); and LoA -7.4 to 8.0%.

Conclusion

A free-breathing DW-MRI protocol for imaging malignant lung tumours achieved satisfactory within-patient repeatability and was robust to changes in post-processing software, justifying its use in multi-centre trials. For response evaluation in individual patients, a change in ADC >21.9% will reflect treatment-related change.

Key Points

? In lung cancer, free-breathing DWI-MRI produces acceptable images with evaluable ADC measurement. ? ADC repeatability coefficient-of-variation is 7.1% for lung tumours >2 cm. ? ADC repeatability coefficient-of-variation is 3.9% for lung tumours >3 cm. ? ADC measurement precision is unaffected by the post-processing software used. ? In multicentre trials, 22% increase in ADC indicates positive treatment response.

     

Assessment of early treatment response to neoadjuvant chemotherapy in breast cancer using non-mono-exponential diffusion models: a feasibility study comparing the baseline and mid-treatment MRI examinations

Objectives

To assess the feasibility of the mono-exponential, bi-exponential and stretched-exponential models in evaluating response of breast tumours to neoadjuvant chemotherapy (NACT) at 3 T.

Methods

Thirty-six female patients (median age 53, range 32–75 years) with invasive breast cancer undergoing NACT were enrolled for diffusion-weighted MRI (DW-MRI) prior to the start of treatment. For assessment of early response, changes in parameters were evaluated on mid-treatment MRI in 22 patients. DW-MRI was performed using eight b values (0, 30, 60, 90, 120, 300, 600, 900 s/mm²). Apparent diffusion coefficient (ADC), tissue diffusion coefficient (D _t), vascular fraction (?), distributed diffusion coefficient (DDC) and alpha (α) parameters were derived. Then t tests compared the baseline and changes in parameters between response groups. Repeatability was assessed at inter- and intraobserver levels.

Results

All patients underwent baseline MRI whereas 22 lesions were available at mid-treatment. At pretreatment, mean diffusion coefficients demonstrated significant differences between groups (p?<?0.05). At mid-treatment, percentage increase in ADC and DDC showed significant differences between responders (49 % and 43 %) and non-responders (21 % and 32 %) (p?=?0.03, p?=?0.04). Overall, stretched-exponential parameters showed excellent repeatability.

Conclusion

DW-MRI is sensitive to baseline and early treatment changes in breast cancer using non-mono-exponential models, and the stretched-exponential model can potentially monitor such changes.

Key points

? Baseline diffusion coefficients demonstrated significant differences between complete pathological responders and non-responders. ? Increase in ADC and DDC at mid-treatment can discriminate responders and non-responders. ? The ? fraction at mid-treatment decreased in responders whereas increased in non-responders. ? The mono- and stretched-exponential models showed excellent inter- and intrarater repeatability. ? Treatment effects can potentially be assessed by non-mono-exponential diffusion models.

     

Correlation between conventional MR imaging combined with diffusion-weighted imaging and histopathologic findings in eyes primarily enucleated for advanced retinoblastoma: a retrospective study

Objectives

To determine the diagnostic accuracy of conventional MRI in detecting tumour invasion of advanced intraocular retinoblastoma and to correlate ADC values with high-risk prognostic parameters.

Method

The sensitivities, specificities, positive predictive values (PPV), negative predictive values (NPV) and accuracies of MRI in detecting tumour-extent parameters of 63 retinoblastomas were determined. Furthermore, ADC values were correlated with high-risk prognostic parameters.

Results

MRI detected postlaminar optic nerve with a sensitivity of 73.3% (95% CI 44.9–92.2%) and a specificity of 89.6% (77.3–96.5%), while the specificity for choroidal invasion was only 31.8% (13.9-54.9%). Likewise, MRI failed to predicted early optic nerve invasion in terms of low sensitivity and PPV. In contrast, scleral and ciliary body invasion could be correctly excluded with high NPV. ADC values were significantly lower in patients with undifferentiated tumours, large tumour size, as with optic nerve and scleral invasion (all p?<?0.05). However, no correlation was found between ADC values and the degree of choroidal or ciliary body infiltration. Additionally, ADC values were negatively correlated with Ki-67 index (r?=??0.62, P?=?0.002).

Conclusions

Conventional MRI has some limitations in reliably predicting microscopic infiltration, with the diagnostic efficiency showing room for improvement, whereas ADC values correlated well with certain high-risk prognostic parameters for retinoblastoma.

Key points

? Conventional MRI failed to predicted microscopic infiltration of the retinoblastoma.? Scleral and ciliary body invasion could be excluded with high NPV.? ADC values correlated well with some high-risk pathological prognostic parameters.

     

Dynamic contrast-enhanced and diffusion-weighted MR imaging in the characterisation of small,non-palpable solid testicular tumours

Objectives

To explore the role of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), using semiquantitative and quantitative parameters, and diffusion-weighted (DW) MRI in differentiating benign from malignant small, non-palpable solid testicular tumours.

Methods

We calculated the following DCE-MRI parameters of 47 small, non-palpable solid testicular tumours: peak enhancement (PE), time to peak (TTP), percentage of peak enhancement (Epeak), wash-in-rate (WIR), signal enhancement ratio (SER), volume transfer constant (K_trans), rate constant (K_ep), extravascular extracellular space volume fraction (V_e) and initial area under the curve (_iAUC). DWI signal intensity and apparent diffusion coefficient (ADC) values were evaluated.

Results

E_peak, WIR, K_trans , K_ep and iAUC were higher and TTP shorter in benign compared to malignant lesions (p?<?0.05). All tumours had similar ADC values (p > 0.07). Subgroup analysis limited to the most frequent histologies – Leydig cell tumours (LCTs) and seminomas – replicated the findings of the entire set. Best diagnostic cutoff value for identification of seminomas: K_trans ≤0.135 min^?1, K_ep ≤0.45 min^?1, iAUC ≤10.96, WIR ≤1.11, Epeak ≤96.72, TTP >99 s.

Conclusions

DCE-MRI parameters are valuable in differentiating between benign and malignant small, non-palpable testicular tumours, especially when characterising LCTs and seminomas.

Key Points

? DCE-MRI may be used to differentiate benign from malignant non-palpable testicular tumours. ? Seminomas show lower Ktrans, Kep and iAUC values. ? ADC values are not valuable in differentiating seminomas from LCTs. ? Semiquantitative DCE-MRI may be used to characterise small, solid testicular tumours.

     

Primary central nervous system lymphoma and atypical glioblastoma: differentiation using the initial area under the curve derived from dynamic contrast-enhanced MR and the apparent diffusion coefficient

Objectives

To evaluate the ability of the initial area under the curve (IAUC) derived from dynamic contrast-enhanced MR imaging (DCE-MRI) and apparent diffusion coefficient (ADC) in differentiating between primary central nervous system lymphoma (PCNSL) and atypical glioblastoma (GBM).

Methods

We retrospectively identified 19 patients with atypical GBM (less than 13 % necrosis of the enhancing tumour), and 23 patients with PCNSL. The histogram parameters of IAUC at 30, 60, 90 s (IAUC30, IAUC60, and IAUC90), and ADC were compared between PCNSL and GBM. The diagnostic performances and added values of the IAUC and ADC for differentiating between PCNSL and GBM were evaluated. Interobserver agreement was assessed via intraclass correlation coefficient (ICC).

Results

The IAUC and ADC parameters were higher in GBM than in PCNSL. The 90th percentile (p90) of IAUC30 and 10th percentile (p10) of ADC showed the best diagnostic performance. Adding p90 of IAUC30 to p10 of ADC improved the differentiation between PCNSL and GBM (area under the ROC curve [AUC]?=?0.886), compared to IAUC30 or ADC alone (AUC?=?0.789 and 0.744; P?<?0.05 for all). The ICC was 0.96 for p90 of IAUC30.

Conclusions

The IAUC may be a useful parameter together with ADC for differentiating between PCNSL and atypical GBM.

Key Points

? High reproducibility is essential for practical implementation of advanced MRI parameters. ? IAUC and ADC are highly reproducible parameters. ? IAUC values were higher in atypical GBM than in PCNSL. ? Adding IAUC to ADC improved the differentiation between PCNSL and GBM. ? IAUC with ADC are useful for differentiating PCNSL from GBM.

     

Diffusion-weighted imaging versus contrast-enhanced MR imaging for the differentiation of renal oncocytomas and chromophobe renal cell carcinomas

Objectives

To compare the performance of diffusion-weighted imaging (DWI) with that of contrast-enhanced MRI in differentiating renal oncocytomas from chromophobe renal cell carcinomas (RCCs).

Methods

We recruited 48 patients with histopathologically confirmed renal oncocytomas (n=16) and chromophobe RCCs (n=32). All patients underwent preoperative DWI and contrast-enhanced MRI. Apparent diffusion coefficient (ADC) and signal intensity were measured in each patient. ADC ratio and percentage of signal intensity change were calculated.

Results

Mean ADC values for renal oncoctytomas were significantly higher than those for chromophobe RCCs (1.59±0.21 vs. 1.09±0.29× 10^?3 mm²/s, p < 0.001). Area under the ROC curve, sensitivity and specificity were 0.931, 87.5% and 84.4%, respectively, for ADC measurement of DW imaging; 0.825, 87.5% and 75%, respectively, for enhancement ratio (p > 0.05). Adding ADC values to the enhancement ratios in the ROC, analysis to differentiate renal oncocytoma from chromophobe RCCs increased specificity from 75 to 87.5% at 87.5% sensitivity without significantly increasing the AUC (0.930).

Conclusions

Both DWI and contrast-enhanced MRI may assist in differentiating renal oncocytomas from chromophobe RCCs, with DWI showing higher diagnostic value. The combination of the two parameters could potentially provide better performance in distinguishing these two tumours.

Key Points

? ADC values can assist in differentiating renal oncocytomas from chromophobe RCCs. ? DW imaging possesses better specificity than does contrast-enhanced MR imaging. ? Combining the two parameters provides higher specificity regarding the differential diagnosis.

     

Roles of the apparent diffusion coefficient and tumor volume in predicting tumor grade in patients with choroid plexus tumors

Purpose

To explore the utility of the apparent diffusion coefficient (ADC) and tumor volume to predict histological grade and prognosis in patients with choroid plexus tumors.

Methods

ADC and tumor volumes were retrospectively evaluated in 25 patients with choroid plexus papilloma (CPP; WHO grade 1 [n?=?13]), atypical CPP (aCPP; grade 2 [n?=?8]), or choroid plexus carcinoma (grade 3 [n?=?4]) The prognostic roles of ADC and tumor volume were assessed.

Results

There were significant differences in mean and minimum ADC values, and tumor volume among the WHO grades (p?=?0.033, p?=?0.044, and p?=?0.014, respectively). Receiver-operating characteristic analysis revealed a mean cutoff ADC value ≤?1.397?×?10^?3 mm²/s for aCPP (sensitivity?=?0.667, specificity?=?0.923). Multiple linear regression analysis demonstrated that both mean ADC (β?=???0.455, p?=?0.005) and tumor volume (β?=?0.513, p?=?0.002) were correlated with WHO grade (adjusted R²?=?0.520, p?=?0.005). Kaplan-Meier curve analysis identified poorer survival in patients with WHO grade 2 and 3 tumors than in those with WHO grade 1 disease (p?=?0.049 and p?=?0.012, respectively). A mean ADC?≤?1.397?×?10^?3 mm²/s (p?=?0.001) and tumor volume 21.05 ml (p?=?0.031) predicted significantly poorer survival.

Conclusion

Mean ADC and tumor volume were correlated with WHO grade of choroid plexus tumors. A lower ADC value and a larger tumor volume predicted a poorer prognosis.

     

Grading diffuse gliomas without intense contrast enhancement by amide proton transfer MR imaging: comparisons with diffusion- and perfusion-weighted imaging

Objectives

To investigate whether amide proton transfer (APT) MR imaging can differentiate high-grade gliomas (HGGs) from low-grade gliomas (LGGs) among gliomas without intense contrast enhancement (CE).

Methods

This retrospective study evaluated 34 patients (22 males, 12 females; age 36.0?±?11.3 years) including 20 with LGGs and 14 with HGGs, all scanned on a 3T MR scanner. Only tumours without intense CE were included. Two neuroradiologists independently performed histogram analyses to measure the 90th-percentile (APT₉₀) and mean (APT_mean) of the tumours’ APT signals. The apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) were also measured. The parameters were compared between the groups with Student’s t-test. Diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis.

Results

The APT₉₀ (2.80?±?0.59 % in LGGs, 3.72?±?0.89 in HGGs, P?=?0.001) and APT_mean (1.87?±?0.49 % in LGGs, 2.70?±?0.58 in HGGs, P?=?0.0001) were significantly larger in the HGGs compared to the LGGs. The ADC and rCBV values were not significantly different between the groups. Both the APT₉₀ and APT_mean showed medium diagnostic performance in this discrimination.

Conclusions

APT imaging is useful in discriminating HGGs from LGGs among diffuse gliomas without intense CE.

Key Points

? Amide proton transfer (APT) imaging helps in grading non-enhancing gliomas ? High-grade gliomas showed higher APT signal than low-grade gliomas ? APT imaging showed better diagnostic performance than diffusion- and perfusion-weighted imaging

     

PI-RADS version 2: quantitative analysis aids reliable interpretation of diffusion-weighted imaging for prostate cancer

Objectives

To determine whether apparent diffusion coefficient (ADC) ratio aids reliable interpretation of diffusion-weighted imaging (DWI) for prostate cancer (PCa).

Methods

Seventy-six consecutive patients with PCa who underwent DWI and surgery were included. Based on pathologic tumour location, two readers independently performed DWI scoring according to the revised Prostate Imaging Reporting and Data System (PI-RADSv2). ADC ratios of benign to cancerous prostatic tissue were then measured independently and compared between cases showing concordant and discordant DWI scores ≥4. Area under the curve (AUC) and threshold of ADC ratio were analyzed for DWI scores ≥4.

Results

The rate of inter-reader disagreement for DWI score ≥4 was 11.8% (9/76). ADC ratios were higher in concordant vs. discordant DWI scores ≥4 (median, 1.7 vs. 1.1–1.2; p?<?0.001). For DWI scores ≥4, the AUCs of ADC ratios were 0.970 for reader 1 and 0.959 for reader 2. In patients with an ADC ratio >1.3, the rate of inter-reader disagreement for DWI score ≥4 decreased to 5.9–6.0%. An ADC ratio >1.3 yielded 100% (reader 1, 54/54; reader 2, 51/51) positive predictive value for clinically significant cancer.

Conclusion

ADC ratios may be useful for reliable interpretation of DWI score ≥4 in PI-RADSv2.

Key points

? The ADC ratio correlated positively with DWI score of PI-RADSv2.? ADC ratio >1.3 was associated with concordant interpretation of DWI score ≥4.? ADC ratio >1.3 was associated with high PPV for clinically significant cancer.? ADC ratio is useful for reliable interpretation of DWI scoring in PI-RADSv2.

     

Added value of diffusion-weighted magnetic resonance imaging for the detection of pancreatic fluid collection infection

Objectives

To investigate the added value of diffusion-weighted (DW) magnetic resonance (MR) imaging in the detection of infection in pancreatic fluid collections (PFC).

Methods

Forty-patients with PFC requiring endoscopic-transmural drainage underwent conventional-MR and DW-MR imaging (b?=?1000 s/mm²) before endoscopy. MR images were divided into two sets (set1, conventional-MR; set2, conventional-MR, DW-MR and ADC maps) and randomized. Two independent readers performed qualitative and quantitative (apparent diffusion coefficient, ADC) image analysis. Bacteriological analysis of PFC content was the gold standard. Non-parametric tests were used for comparisons. Sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) and accuracy were calculated for the two sets for both readers. Receiver operating characteristic curves (ROC) were drawn to assess quantitative DW-MR imaging diagnostic performance.

Results

For both readers, sensitivity, specificity, NPV, PPV and accuracy for infected PFCs were higher for set2 (P?>?.05). ADC were lower in infected versus non-infected PFCs (P?≤?.031). Minimum ADC cut-off: 1,090×10^-3 mm²/s for reader 1 and 1,012×10^-3 mm²/s for reader 2 (sensitivity and specificity 67 % and 96 % for both readers).

Conclusion

Qualitative information provided by DW-MR may help to assess PFCs infection. Infected PFCs show significantly lower ADCs compared to non-infected ones.

Key Points

? DW improves MR diagnostic accuracy to detect infection of PFC ? Infected PFCs show lower ADC compared to non-infected ones (P?<?.031) ? DW-MR images are easy to interpret especially for non-experienced radiologist

     

Correlation between electrical conductivity and apparent diffusion coefficient in breast cancer: effect of necrosis on magnetic resonance imaging

Objectives

To investigate the correlation between conductivity and ADC in invasive ductal carcinoma according to the presence of necrosis on MRI.

Methods

Eighty-one women with invasive ductal carcinoma ≥1 cm on T2-weighted fast spin echo sequence of preoperative MRI were included. Phase-based MR electric properties tomography was used to reconstruct conductivity. Mean ADC was measured. Necrosis was defined as an area with very high T2 signal intensity. The relationship between conductivity and ADC was examined using Spearman’s correlation coefficient (r). Multiple linear regression analysis was performed to identify factors associated with conductivity or ADC.

Results

In the total group, conductivity showed negative correlation with ADC (r = –0.357, p = 0.001). This correlation was maintained in the subgroup without necrosis (n = 53, r = –0.455, p = 0.001), but not in the subgroup with necrosis (n = 28, r = –0.080, p = 0.687). The correlation between the two parameters was different according to necrosis (r = -0.455 vs -0.080, p = 0.047). HER2 enriched subtype was independently associated with conductivity (p = 0.029). Necrosis on MRI was independently associated with ADC (p = 0.027).

Conclusions

Conductivity shows negative correlation with ADC that is abolished by the presence of necrosis on MRI.

Key Points

? Electric conductivity showed negative correlation with ADC? However, the correlation was abolished by the presence of necrosis on MRI? HER2-enriched subtype was independently associated with conductivity? Necrosis on MRI was independently associated with ADC

     

Diffusion-weighted imaging for the cellularity assessment and matrix characterization of soft tissue tumour

Purpose

To evaluate whether apparent diffusion coefficient (ADC) of diffusion-weighted imaging (DWI) is able to investigate the histological features of soft tissue tumours.

Methods

We reviewed MRIs of soft tissue tumours performed from 2012 to 2015 to calculate the average ADCs. We included 46 patients (27 male; mean age: 57 years, range 12–85 years) with histologically proven soft tissue tumours (10 benign, 2 intermediate 34 malignant) grouped into eight tumour type classes. An experienced pathologist assigned a semi-quantitative cellularity score (very high, high, medium and low) and tumour grading. The t test, ANOVA and linear regression were used to correlate ADC with clinicopathological data. Approximate receiver operating characteristic curves were created to predict possible uses of ADC to differentiate benign from malignant tumours.

Results

There was a significant difference (p < 0.01) in ADCs between these three groups excluding myxoid sarcomas. A significant difference was also evident between the tumour type classes (p < 0.001), grade II and III myxoid lesions (p < 0.05), tumour grading classes (p < 0.001) and cellularity scores classes (p < 0.001), with the lowest ADCs in the very high cellularity. While the linear regression analysis showed a significant relationship between ADC and tumour cellularity (r = 0.590, p ≤ 0.05) and grading (r = 0.437, p ≤ 0.05), no significant relationship was found with age, gender, tumour size and histological subtype. An optimal cut-off ADC value of 1.45 × 10^?3 mm²/s with 76.8% accuracy was found to differentiate benign from malignant tumours.

Conclusions

DWI may offer adjunctive information about soft tissue tumours, but its clinical role is still to be defined.

     

Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status,histological subtype,and molecular prognostic factors

Purpose

To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis.

Materials and methods

This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44?±?11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (D_t), perfusion fraction (f_p), and pseudo-diffusivity (D_p) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann–Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman’s rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression.

Results

The average values of the ADC and IVIM biomarkers, D_t and f_p, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly f_p and D_p, showed significant correlation with hormonal factor expression.

Conclusion

Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients.

Key Points

? Novel IVIM biomarkers characterize heterogeneous breast cancer.? Histogram analysis enables quantification of tumour heterogeneity.? IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.