Applying patient characteristics, stent-graft selection, and pre-operative computed tomographic angiography data to a machine learning algorithm: Is endoleak prediction possible?

INTRODUCTION

This study aims to predict endoleak after endovascular aneurysm repair (EVAR) using machine learning (ML) integration of patient characteristics, stent-graft configuration, and a selection of vessel lengths, diameters and angles measured using pre-operative computed tomography angiography (CTA).

METHODS

We evaluated 1-year follow-up CT scans (arterial and delayed phases) in patients who underwent EVAR for the presence or absence of an endoleak. We also obtained data on the patient characteristics, stent-graft selection, and preoperative CT vessel morphology (diameter, length, and angle). The extreme gradient boosting (XGBoost) for the ML system was trained on 30 patients with endoleaks and 81 patients without. We evaluated 5217 items in 111 patients with abdominal aortic aneurysms, including the patient characteristics, stent-graft configuration and vascular morphology acquired using pre-EVAR abdominal CTA. We calculated the area under the curve (AUC) of our receiver operating characteristic analysis using the ML method.

RESULTS

The AUC, accuracy, 95% confidence interval (CI), sensitivity, and specificity were 0.88, 0.88, 0.79-0.97, 0.85, and 0.91 for ML applying XGBoost, respectively.

CONCLUSIONS

The diagnostic performance of the ML method was useful when factors such as the patient characteristics, stent-graft configuration and vessel length, diameter and angle of the vessels were considered from pre-EVAR CTA.

IMPLICATIONS FOR PRACTICE

Based on our findings, we suggest that this is a potential application of ML for the interpretation of abdominal CTA scans in patients with abdominal aortic aneurysms scheduled for EVAR.

Radiation dose reduction method combining the ECG-Edit function and high helical pitch in retrospectively-gated CT angiography

INTRODUCTION

The purpose of this study was to demonstrate that dose reduction does not compromise image quality when combining high helical pitch (HP) and the ECG-Edit function during low HP retrospectively gated computed tomography angiography (CTA).

METHODS

This study made use of a pulsating cardiac phantom (ALPHA 1 VTPC). The heart rate (HR) of the cardiac phantom was changed in five intervals, every 5 beats per minute (bpm), from 40 to 60 bpm. Evaluation of a range of HR was important because data loss might occur when combining a low HR and high HP. We performed retrospectively gated CTA scans five times using a low HP (0.16) and high HP (0.24), for each of the five HR intervals, using a 64-detector row CT scanner. The CT volume dose index (CTDI_vol) was recorded from the CT console of each scan. For the images with data loss, data were repaired using the ECG-Edit function. We compared the CTDI_vol, estimated cardiac phantom volume, and the visualization of the coronary ladder phantom between HP 0.16, with or without repaired HP 0.24, using the ECG-Edit function.

RESULTS

Data loss occurred with a HR of 40 bpm and 45 bpm when using HP 0.24. The CTDI_vol was reduced by approximately 33% with HP 0.24 when compared with HP 0.16. There were no significant differences in the mean cardiac motion phantom volume and visualization scores between HP 0.16 and with and without repaired HP 0.24 using the ECG-Edit function (p < 0.05).

CONCLUSION

The ECG-Edit function is potential useful for repairing the lost data in patients with a low HR, and when combined with a high HP, it is possible to reduce the radiation dose by approximately 33%.

IMPLICATIONS FOR PRACTICE

The ECG-Edit function and high HP may be a viable option in pediatric CTA studies.

Effect of injection duration on contrast enhancement during cardiac computed tomography angiography in newborns and infants

INTRODUCTION

To investigate how changing the injection duration at cardiac computed tomography angiography (CCTA) affects contrast enhancement in newborns and infants.

METHODS

Included were 142 newborns and infants with confirmed congenital heart disease who underwent CCTA between January 2015 and December 2018. In group 1 (n = 71 patients), the injection duration was 8 s; in group 2 (n = 71) it was 16 s. Our findings were assessed by one-to-one matching analysis to estimate the propensity score of each patient. We compare the CT number for the pulmonary artery (PA), ascending aorta (AAO), left superior vena cava (SVC), AAO and PA enhancement ratio, and the scores for visualization between the two groups.

RESULTS

In group 1, median CT number and ranges was 345 (211-591) HU in the AAO, 324 (213-567) HU in the PA, and 62 (1-70) HU in the SVC. These values were 465 (308-669) HU, 467 (295-638) HU, and 234 (67-443) HU, respectively, in group 2 (p < 0.05). The median score for volume-rendering visualization on 3D images of the CCTA was 2 in group 1 and 3 in group 2; the score for visualization of the left SVC of the maximum intensity projection images was 2 in group 1 and 3 in group 2 (p < 0.05). The CT number for the AAO and PA enhancement ratio was 15.2 in group 1 and 9.2 in group 2 (p < 0.05).

CONCLUSION

The 16-sec injection protocol yielded significantly higher CT numbers for the AAO, PA, and the SVC than the 8-sec injection protocol; the visualization scores were also significantly higher in group 2.

IMPLICATIONS FOR PRACTICE

In newborns and infants, the longer injection time for CCTA yields stable and higher contrast enhancement at identical CM concentrations.

Virtual magnetic resonance lumbar spine images generated from computed tomography images using conditional generative adversarial networks

INTRODUCTION

The aim of this study was to generate virtual Magnetic resonance (MR) from computed tomography (CT) using conditional generative adversarial networks (cGAN).

METHODS

We selected examinations from 22 adults who obtained their CT and MR lumbar spine examinations. Overall, 4 examinations were used as test data, and 18 examinations were used as training data. A cGAN was trained to generate virtual MR images from the CT images using the corresponding MR images as targets. After training, the generated virtual MR images from test data in epochs 1, 10, 50, 100, 500, and 1000 were compared with the original ones using the mean square error (MSE) and structural similarity index (SSIM). Additionally, two radiologists also performed qualitative assessments.

RESULTS

The MSE of the virtual MR images decreased as the epoch of the cGANs increased from the original CT images: 8876.7 ± 1192.9 (original CT), 1567.5 ± 433.9 (Epoch 1), 1242.4 ± 442.0 (Epoch 10), 1065.8 ± 478.1 (Epoch 50), 1276.1 ± 718.9 (Epoch 100), 1046.7 ± 488.2 (Epoch 500), and 1031.7 ± 400.0 (Epoch 1000). No considerable differences were observed in the qualitative evaluation between the virtual MR images and the original ones, except in the structure of the spinal canal.

CONCLUSION

Virtual MR lumbar spine images using cGANs could be a feasible technique to generate near-MR images from CT without MR examinations for evaluation of the vertebral body and intervertebral disc.

IMPLICATIONS FOR PRACTICE

Virtual MR lumbar spine images using cGANs can offer virtual CT images with sufficient quality for attenuation correction for PET or dose planning in radiotherapy.

Enhancement rate of venous phase to portal venous phase computed tomography and its correlation with ultrasound elastography determination of liver fibrosis

INTRODUCTION

This study aimed to compare the correlation between the computed tomography (CT) enhancement rate of the venous to portal venous phase (VP-ER) and the extracellular volume (ECV) fraction with shear-wave ultrasound elastography (USE) findings in patients with liver fibrosis.

METHODS

We included 450 patients with clinically suspected liver cirrhosis who underwent triphasic dynamic CT studies and USE. We compared the USE results with the unenhanced CT phase, with enhancement in the hepatic artery phase (HAP), portal venous phase (PVP), and venous phase (VP), and with the ECV fraction and the VP-ER. We also compared the area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the ECV fraction and VP-ER with that of the values obtained with USE.

RESULTS

The VP-ER was the most highly correlated with the liver stiffness value determined with USE (Pearson's correlation coefficient: r = 0.37), followed by enhancement in the PVP (r = -0.25), CT number on unenhanced CT scans (r = -0.22), the ECV fraction (r = 0.19), enhancement in the VP (r = 0.059), and enhancement in the HAP (r = -0.023) (all p < 0.01). The VP-ER showed a significantly higher AUC than the ECV fraction (0.75 vs 0.62) when the liver stiffness was >15 kPa in USE studies (p = 0.04).

CONCLUSION

Compared to the ECV fraction, the VP-ER is more useful for predicting all degrees of liver fibrosis on routine triphasic dynamic CT images.

IMPLICATIONS FOR PRACTICE

Although improvement is needed, the VP-ER has a higher diagnostic ability for liver fibrosis than the ECV fraction in clinical practice.

Efficacy of the spiral flow generating extended tube during paediatric CCTA

INTRODUCTION

To compare the computed tomography (CT) number for paediatric cardiac computed tomography angiography (CCTA) and visualisation score of the three-dimensional (3D) images using the conventional T-shaped extended tube (T-tube) and spiral flow-generating extended tube (spiral-tube) connected between the contrast injector and cannula.

METHODS

In total, 108 patients suspected to have congenital heart disease (CHD) were considered for inclusion. We utilised the T-tube for intravenous contrast and spiral-tube in 54 patients each. Observers individually inspected randomized volume rendering images of the internal thoracic artery, each acquired from the with or without spiral-tube groups, using a four-point scale. We compared the mean CT number of the ascending aorta (AAO) and pulmonary artery (PA), contrast noise ratio (CNR), CT number for the AAO and PA enhancement ratio, and the visualisation scores between the groups.

RESULTS

There were no significant differences in patient characteristics between the with or without spiral-tube groups (p > 0.05). The mean CT number ±standard deviation for the AAO and PA, and the CNR without or with spiral-tube groups were 441.2 ± 89.2 and 489.8 ± 86.1 HU for the AAO, 436.3 ± 100.6 and 475.3 ± 85.2 HU for the PA, and 9.5 ± 2.2 and 10.8 ± 2.4 for the CNR, respectively (p < 0.05). In the spiral-tube group, the CT number, CNR, and visualisations score of the 3D images were significantly higher for the AAO and PA than those in the T-tube group (p < 0.05).

CONCLUSION

The spiral-tube proved to be beneficial in improving the CT number for the AAO and PA, CNR, and visualisation score compared with the conventional T-tube during paediatric CCTA.

IMPLICATIONS FOR PRACTICE

The spiral-tube may allow the visualisation of smaller blood vessels than those visualised by the conventional T-tube for paediatric patients in CCTA.

Deep learning with convolutional neural network for estimation of the characterisation of coronary plaques: Validation using IB-IVUS

INTRODUCTION

Deep learning approaches have shown high diagnostic performance in image classifications, such as differentiation of malignant tumors and calcified coronary plaque. However, it is unknown whether deep learning is useful for characterizing coronary plaques without the presence of calcification using coronary computed tomography angiography (CCTA). The purpose of this study was to compare the diagnostic performance of deep learning with a convolutional neural network (CNN) with that of radiologists in the estimation of coronary plaques.

METHODS

We retrospectively enrolled 178 patients (191 coronary plaques) who had undergone CCTA and integrated backscatter intravascular ultrasonography (IB-IVUS) studies. IB-IVUS diagnosed 81 fibrous and 110 fatty or fibro-fatty plaques. We manually captured vascular short-axis images of the coronary plaques as Portable Network Graphics (PNG) images (150 × 150 pixels). The display window level and width were 100 and 700 Hounsfield units (HU), respectively. The deep-learning system (CNN; GoogleNet Inception v3) was trained on 153 plaques; its performance was tested on 38 plaques. The area under the curve (AUC) obtained by receiver operating characteristic analysis of the deep learning system and by two board-certified radiologists was compared.

RESULTS

With the CNN, the AUC and the 95% confidence interval were 0.83 and 0.69-0.96, respectively; for radiologist 1 they were 0.61 and 0.42-0.80; for radiologist 2 they were 0.68 and 0.51-0.86, respectively. The AUC for CNN was significantly higher than for radiologists 1 (p = 0.04); for radiologist 2 it was not significantly different (p = 0.22).

CONCLUSION

DL-CNN performed comparably to radiologists for discrimination between fatty and fibro-fatty plaque on CCTA images.

IMPLICATIONS FOR PRACTICE

The diagnostic performance of the CNN and of two radiologists in the assessment of 191 ROIs on CT images of coronary plaques whose type corresponded with their IB-IVUS characterization was comparable.

Diagnostic performance of computed tomography digital subtraction angiography of the lower extremities during haemodialysis in patients with suspected peripheral artery disease

INTRODUCTION

With intra-arterial digital subtraction angiography (DSA) considered as the gold standard, we compared the diagnostic value of computed tomography angiography (CTA) and computed tomography-digital subtraction angiography (CT-DSA in hemodialysis (HD) patients suspected of having lower limb peripheral artery disease (PAD).

METHODS

In this retrospective study, we enrolled 220 HD patients with suspected PAD. CT-DSA images were obtained by subtracting unenhanced images from enhanced images. The research team calculated the area under the curve (AUC), sensitivity, specificity, positive and negative predictive value (PPV, NPV), and recorded the diagnostic accuracy between the CTA and CT-DSA images using the DSA as gold standard. Visual evaluation of calcifications in the peripheral arteries were also compared between CTA and CT-DSA images.

RESULTS

At the above-knee level, the CTA AUC [95% confidence interval (CI)] was 0.68 (CI 0.64-0.72), sensitivity and specificity were 60 and 81%, PPV and NPV were 85 and 53%, and accuracy was 67%. Below the knee, these values were 0.66 (CI 0.62-0.70), 71 and 79%, 79 and 47%, and 66%. For CT-DSA, above-knee, the AUC [95% CI] was 0.88 (CI 0.85-0.91), sensitivity and specificity were 84 and 92%, PPV and NPV were 89 and 97%, and accuracy was 93%. Below the knee, these values were 0.95 (CI 0.93-0.97), 95 and 93%, 96 and 83%, and 93%. The scores for the visualization of calcification in the peripheral arteries was significantly higher for CT-DSA than CTA (p < 0.05).

CONCLUSIONS

CT-DSA helps to assess stenotic PAD with high calcification in the lower extremities of HD patients.

IMPLICATIONS FOR PRACTICE

On CT-DSA images, the severity of vascular calcification can be assessed for HD patients suspected of PAD of the lower extremities.

Machine learning to identify lymph node metastasis from thyroid cancer in patients undergoing contrast-enhanced CT studies

INTRODUCTION

We compared the diagnostic performance of morphological methods such as the major axis, the minor axis, the volume and sphericity and of machine learning with texture analysis in the identification of lymph node metastasis in patients with thyroid cancer who had undergone contrast-enhanced CT studies.

METHODS

We sampled 772 lymph nodes with histology defined tissue types (84 metastatic and 688 benign lymph nodes) that were visualised on CT images of 117 patients. A support vector machine (SVM), free programming software (Python), and the scikit-learn machine learning library were used to discriminate metastatic-from benign lymph nodes. We assessed 96 texture and 4 morphological features (major axis, minor axis, volume, sphericity) that were reported useful for the differentiation between metastatic and benign lymph nodes on CT images. The area under the curve (AUC) obtained by receiver operating characteristic analysis of univariate logistic regression and SVM classifiers were calculated for the training and testing datasets.

RESULTS

The AUC for all classifiers in training and testing datasets was 0.96 and 0.86, at the SVM for machine learning. When we applied conventional methods to the training and testing datasets, the AUCs were 0.63 and 0.48 for the major axis, 0.70 and 0.44 for the minor axis, 0.66 and 0.43 for the volume, and 0.69 and 0.54 for sphericity, respectively. The SVM using texture features yielded significantly higher AUCs than univariate logistic regression models using morphological features (p = 0.001).

CONCLUSION

For the identification of metastatic lymph nodes from thyroid cancer on contrast-enhanced CT images, machine learning combined with texture analysis was superior to conventional diagnostic methods with the morphological parameters.

IMPLICATIONS FOR PRACTICE

Our findings suggest that in patients with thyroid cancer and suspected lymph node metastasis who undergo contrast-enhanced CT studies, machine learning using texture analysis is high diagnostic value for the identification of metastatic lymph nodes.

The combined application of the contrast-to-noise index and 80 kVp for cardiac CTA scanning before atrial fibrillation ablation reduces radiation dose exposure

INTRODUCTION

To compare the radiation dose, diagnostic accuracy, and the resultant ablation procedures using 80 and 120-kVp cardiac computed tomography angiography (CCTA) protocols with the same contrast-to-noise ratio in patients scheduled for atrial fibrillation (AF) ablation.

METHODS

This retrospective study was performed following institutional review board approval. We divided 140 consecutive patients who had undergone CCTA using a 64-MDCT scanner into two equal groups. Standard deviation (SD) of the CT number was set at 25 Hounsfield units (HU) for the 120-kVp protocol. To facilitate a reduction in radiation dose it was set at 40 HU for the 80 kVp protocol. We compared the two protocols with respect to the radiation dose, the diagnostic accuracy for detecting left atrial appendage (LAA) thrombi, matching for surface registration, and the resultant ablation procedures.

RESULTS

At 120 kVp, the dose length product (DLP) was 2.2 times that at 80 kVp (1269.0 vs 559.0 mGy cm, p < 0.01). The diagnostic accuracy for thrombus detection was 100% using both protocols. There was no difference between the two protocols with respect to matching for surface registration. The protocols did not differ with respect to the subsequent time required for the ablation procedures and the ablation fluoroscopy time, and the radiation dose (p = 0.54, 0.33, and 0.32, respectively).

CONCLUSION

For the same CNR, the DLP at 80 kVp (559.0 mGy cm) was 56% of that delivered at 120 kVp (1269.0 mGy cm). There was no reduction in diagnostic accuracy.

IMPLICATIONS FOR PRACTICE

Maintaining CNR allows for a reduction in the radiation dose without reducing the image quality.

Metal Artifact Reduction in Head CT Performed for Patients with Deep Brain Stimulation Devices: Effectiveness of a Single-Energy Metal Artifact Reduction Algorithm

BACKGROUND AND PURPOSE

Deep brain stimulation electrodes induce massive artifacts on CT images, deteriorating the diagnostic value of examinations. We aimed to investigate the usefulness and potential limitations of a single-energy metal artifact reduction algorithm in head CT performed in patients with implanted deep brain stimulation devices.

MATERIALS AND METHODS

Thirty-four patients with deep brain stimulation (bilateral, n = 28) who underwent head CT on a 320-detector row scanner and whose images were reconstructed with and without single-energy metal artifact reduction at the examinations were retrospectively included. The severity of artifacts around electrodes was assessed objectively using SDs and an artifact index. Two radiologists subjectively evaluated the severity of artifacts from electrodes, the visibility of electrode localization and surrounding structures, and overall diagnostic confidence on 4-point scales. Background image quality (GM-WM contrast and image noise) was subjectively and objectively assessed. The presence and location of artifacts newly produced by single-energy metal artifact reduction were analyzed.

RESULTS

Single-energy metal artifact reduction provided lower objective and subjective metal artifacts and improved visualization of electrode localization and surrounding structures and diagnostic confidence compared with non-single-energy metal artifact reduction images, with statistical significance (all, P < .01). No significant differences were observed in GM-WM contrast and image noise (all, P ≥ .11). The new artifacts from single-energy metal artifact reduction were prominently observed in patients with bilateral deep brain stimulation at high convexity, possibly induced by deep brain stimulation leads placed under the parietal scalp.

CONCLUSIONS

Single-energy metal artifact reduction substantially reduces the metal artifacts from deep brain stimulation electrodes and improves the visibility of intracranial structures without affecting background image quality. However, non-single-energy metal artifact reduction images should be simultaneously reviewed to accurately assess the entire intracranial area, particularly in patients with bilateral deep brain stimulation.

A multiparametric MRI-based machine learning to distinguish between uterine sarcoma and benign leiomyoma: comparison with 18F-FDG PET/CT

AIM

To compare the performance of machine learning using multiparametric magnetic resonance imaging (mp-MRI) and positron-emission tomography (PET) to distinguish between uterine sarcoma and leiomyoma.

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board and informed consent was waived. Sixty-seven consecutive patients with uterine sarcoma or leiomyoma who underwent pelvic 3 T MRI and PET were included. Of 67 patients, 11 had uterine sarcomas and 56 had leiomyomas. Seven different parameters were measured in the tumours, from T2-weighted, T1-weighted, contrast-enhanced, and diffusion-weighted MRI, and PET. The areas under the receiver operating characteristic curves (AUC) with a leave-one-out cross-validation were used to compare the diagnostic performances of the univariate and multivariate logistic regression (LR) model with those of two board-certified radiologists.

RESULTS

The AUCs of the univariate models using MRI parameters (0.68-0.8) were inferior to that of the maximum standardised uptake value (SUVmax) of PET (0.85); however, the AUC of the multivariate LR model (0.92) was superior to that of SUVmax, and comparable to that of the board-certified radiologists (0.97 and 0.89).

CONCLUSION

The diagnostic performance of the machine learning using mp-MRI was superior to PET and comparable to that of experienced radiologists.

Value of 100 kVp scan with sinogram-affirmed iterative reconstruction algorithm on a single-source CT system during whole-body CT for radiation and contrast medium dose reduction: an intra-individual feasibility study

AIM

To perform an intra-individual investigation of the usefulness of a contrast medium (CM) and radiation dose-reduction protocol using single-source computed tomography (CT) combined with 100 kVp and sinogram-affirmed iterative reconstruction (SAFIRE) for whole-body CT (WBCT; chest-abdomen-pelvis CT) in oncology patients.

MATERIALS AND METHODS

Forty-three oncology patients who had undergone WBCT under both 120 and 100 kVp protocols at different time points (mean interscan intervals: 98 days) were included retrospectively. The CM doses for the 120 and 100 kVp protocols were 600 and 480 mg iodine/kg, respectively; 120 kVp images were reconstructed with filtered back-projection (FBP), whereas 100 kVp images were reconstructed with FBP (100 kVp-F) and the SAFIRE (100 kVp-S). The size-specific dose estimate (SSDE), iodine load and image quality of each protocol were compared.

RESULTS

The SSDE and iodine load of 100 kVp protocol were 34% and 21%, respectively, lower than of 120 kVp protocol (SSDE: 10.6±1.1 versus 16.1±1.8 mGy; iodine load: 24.8±4versus 31.5±5.5 g iodine, p<0.01). Contrast enhancement, objective image noise, contrast-to-noise-ratio, and visual score of 100 kVp-S were similar to or better than of 120 kVp protocol.

CONCLUSION

Compared with the 120 kVp protocol, the combined use of 100 kVp and SAFIRE in WBCT for oncology assessment with an SSCT facilitated substantial reduction in the CM and radiation dose while maintaining image quality.

Early glottic squamous cell carcinoma: Predictive value of MR imaging for the rate of 5-year local control with radiation therapy

Purpose: To evaluate MR findings in early (T1 and T2 stages) glottic carcinomas and the predictive value of MR imaging for the rate of 5-year local control with radiation therapy.

Material and Methods: Eighty-three patients with early glottic carcinomas were prospectively examined with MR at 1.5 T. MR investigation included unenhanced T1-weighted, T2-weighted, dynamic and contrast-enhanced T1-weighted images. Three patients with presumed advanced diseases on MR were initially treated with total laryngectomy and were excluded from the study. The remaining 80 patients were treated with radiation therapy with curative intent. Tumor detectability, size and relationship to the thyroid cartilage were determined on MR images. The MR findings were then correlated with the rate of local control.

Results: Forty-eight of 80 lesions (60%) were detected on MR imaging. All detected lesions but 1 demonstrated increased signal on T2-weighted images. The lesions were best delineated on dynamic images (statistically significant). The 5-year local control rate with radiation therapy was 72%. Univariate analysis revealed clinical T stage, MR detectability, tumor size and relationship to the thyroid cartilage as significant predictors. Multivariate analysis revealed that the relationship to the thyroid cartilage was an independent factor.

Conclusion: MR provides prognostic information about the results of definitive radiation therapy. To evaluate the tumor extension in lesions detected on precontrast MR images, contrast-enhanced dynamic images should be obtained.

Negative predictive value of multiparametric MRI for prostate cancer detection: outcome of 5-year follow-up in men with negative findings on initial MRI studies

OBJECTIVE

To assess the clinical negative predictive value (NPV) of multiparametric MRI (mp-MRI) for prostate cancer in a 5-year follow-up.

MATERIALS AND METHODS

One hundred ninety-three men suspected of harboring prostate cancer with negative MRI findings were included. Patients with positive transrectal ultrasound (TRUS)-guided biopsy findings were defined as false-negative. Patients with negative initial TRUS-guided biopsy findings were followed up and only patients with negative findings by digital rectal examination, MRI, and repeat biopsy and no increase in PSA at 5-year follow-up were defined as "clinically negative". The clinical NPV of mp-MRI was calculated. For quantitative analysis, mean signal intensity on T2-weighted images and the mean apparent diffusion coefficient value on ADC maps of the initial MRI studies were compared between peripheral-zone (PZ) cancer and the normal PZ based on pathologic maps of patients who had undergone radical prostatectomy.

RESULTS

The clinical NPV of mp-MRI was 89.6% for significant prostate cancer. Small cancers, prostatitis, and benign prostatic hypertrophy masking prostate cancer returned false-negative results. Quantitative analysis showed that there was no significant difference between PZ cancer and the normal PZ.

CONCLUSION

The mp-MRI revealed a high clinical NPV and is a useful tool to rule out clinically significant prostate cancer before biopsy.

Optimal contrast medium injection protocols for the depiction of the Adamkiewicz artery using 64-detector CT angiography

AIM

To determine the optimal contrast medium injection protocol for demonstrating the Adamkiewicz artery (AKA) using 64-detector CT angiography (CTA).

MATERIALS AND METHODS

CTA was performed using 64-detector CT. The study population consisted of 80 patients (mean age 67.2 years) with aortoiliac diseases. In the first 60 patients 540 mg I/kg body weight was administered over 25s. The patients were randomly assigned to three protocols with imaging started at 15 (protocol A-1), 18 (A-2), or 21s (A-3) after triggering (threshold 150 HU). The other 20 received 720 mg I/kg body weight with an imaging delay of 18s (protocol B). Two radiologists evaluated the presence of the AKA and measured the attenuation of the aorta and AKA.

RESULTS

Aortic enhancement was 360.4, 348, 279.3, and 372 HU for protocols A-1, A-2, A-3, and B, respectively. There was no significant difference between the A-1 and A-2 protocols (Tukey-Kramer test, p=0.73); however, aortic enhancement was significantly lower in A-3 than A-1 and A-2 (p<0.01). There was no significant difference between A-2 and B (p=0.40). AKA attenuation was 69.3, 91.9, 94.6, and 105.4 HU for protocols A-1, A-2, A-3, and B, respectively. There was no significant difference between the A-2 and A-3 protocols (p=0.91); however, AKA attenuation was significantly lower with A-1 than A-2 or A-3 (p=0.01). AKA attenuation was significantly lower with A-2 than B (p=0.03) and there was a significant difference between A-2 (50%) and B (95%) in the depiction of the hairpin configuration of the AKA (p=0.02).

CONCLUSION

For the demonstration of the AKA at CTA, the optimal protocol used an imaging delay of 18s after triggering and an iodine dose of 720 mg I/kg body weight.

Clinical evaluation of aortic diseases using nonenhanced MRA with ECG-triggered 3D half-Fourier FSE

The efficacy of the nonenhanced magnetic resonance angiography (MRA) technique known as fresh-blood imaging (FBI), using electrocardiograph (ECG)-triggered 3D half-Fourier fast spin-echo (FSE), was evaluated for the detection and characterization of aortic diseases. Seventy-five consecutive patients with aortic disease underwent the FBI examination on a 1.5-T clinical imager. The results showed that the FBI technique permits clear visualization of aortic diseases, and the vessel branches and their relationship, which provides valuable information. Therefore, the nonenhanced FBI technique is appropriate to use for screening purposes.

Early glottic squamous cell carcinoma. Predictive value of MR imaging for the rate of 5-year local control with radiation therapy

PURPOSE

To evaluate MR findings in early (T1 and T2 stages) glottic carcinomas and the predictive value of MR imaging for the rate of 5-year local control with radiation therapy.

MATERIAL AND METHODS

Eighty-three patients with early glottic carcinomas were prospectively examined with MR at 1.5 T. MR investigation included unenhanced T1-weighted, T2-weighted, dynamic and contrast-enhanced T1-weighted images. Three patients with presumed advanced diseases on MR were initially treated with total laryngectomy and were excluded from the study. The remaining 80 patients were treated with radiation therapy with curative intent. Tumor detectability, size and relationship to the thyroid cartilage were determined on MR images. The MR findings were then correlated with the rate of local control.

RESULTS

Forty-eight of 80 lesions (60%) were detected on MR imaging. All detected lesions but 1 demonstrated increased signal on T2-weighted images. The lesions were best delineated on dynamic images (statistically significant). The 5-year local control rate with radiation therapy was 72%. Univariate analysis revealed clinical T stage, MR detectability, tumor size and relationship to the thyroid cartilage as significant predictors. Multivariate analysis revealed that the relationship to the thyroid cartilage was an independent factor.

CONCLUSION

MR provides prognostic information about the results of definitive radiation therapy. To evaluate the tumor extension in lesions detected on precontrast MR images, contrast-enhanced dynamic images should be obtained.

MR imaging of squamous cell carcinoma of the floor of the mouth. Appearance of the sublingual and submandibular glands

PURPOSE

To determine the diagnostic value of MR imaging for tumors of the floor of the mouth and the effects of the tumors on the sublingual and submandibular glands.

MATERIAL AND METHODS

Thirty-seven patients with proven squamous cell carcinoma of the floor of the mouth underwent MR imaging, including unenhanced T1-weighted, T2-weighted, dynamic, and contrast-enhanced T1-weighted images. The appearance of the tumor and the sublingual and submandibular glands was assessed qualitatively and quantitatively.

RESULTS

All tumors demonstrated replacement of the normal signal intensity in the adjacent sublingual gland. Twenty-one patients (57%) had abnormal signal intensity of the submandibular gland without tumor invasion, presumably secondary to submandibular duct obstruction by the tumor. Unenhanced T1-weighted images provided high contrast between tumor and sublingual gland. Tumors limited within the gland were well detected on unenhanced T1-weighted images. Large tumors extending beyond the gland were well delineated on dynamic images, but no better than on T2-weighted images.

CONCLUSION

At MR imaging for tumor of the floor of the mouth, one must carefully evaluate the appearance of the sublingual and submandibular glands. Contrast-enhanced studies are unnecessary when the tumor is limited within the sublingual gland on precontrast MR images.