Maximum Intensity Projection Images Research Articles

Evaluation of the Contrast Enhancement Performance of Gadopiclenol for Magnetic Resonance Angiography in Healthy Rabbits and Pigs.

Unexpected accumulations of gadolinium in various organs were reported after the administration of gadolinium-based contrast agents, making desirable to reduce the dose while maintaining equivalent diagnostic performance. The aim of this study was to evaluate the contrast enhancement performance of high relaxivity gadopiclenol compared with gadoterate meglumine in abdominal contrast-enhanced magnetic resonance angiography (CE-MRA). In a first study in healthy rabbits, axial 3D gradient echo sequences were applied at 4.7 T to study arterial enhancement as a function of gadopiclenol dose (0.025, 0.05, 0.075, and 0.1 mmol Gd/kg) or gadoterate meglumine at 0.1 mmol Gd/kg (n = 5-6/group). The increase in signal-to-noise ratio (ΔSNR) in the aorta at the first pass was measured and compared. In a second, crossover study in 6 healthy pigs, abdominal CE-MRA sequences were acquired at 3 T with gadopiclenol at 0.05 mmol Gd/kg or gadoterate meglumine at 0.1 mmol Gd/kg at a 1-week interval. Quantitatively on the maximum intensity projection (MIP) images, the mean MIP SNR within the aorta of both groups was compared. Qualitatively, a blinded comparison of the angiograms was performed by an experienced radiologist to determine the preferred contrast agent. In the rabbit, ∆SNR is linearly correlated with the gadopiclenol dose (P = 0.0010). Compared with gadoterate meglumine 0.1 mmol Gd/kg, an increase in the ∆SNR is observed after 0.05, 0.075, and 0.1 mmol Gd/kg of gadopiclenol (+63% P = 0.0731, +78% P = 0.0081, and +72% P = 0.0773, respectively), whereas at 0.025 mmol Gd/kg, ∆SNR is in the same range as with gadoterate meglumine 0.1 mmol Gd/kg (+15% P > 0.9999). In pigs, contrast enhancement after gadopiclenol at 0.05 mmol/kg is +22% superior to MIP SNR after gadoterate meglumine at 0.1 mmol Gd/kg (P = 0.3095). Qualitatively, a preference was shown for gadopiclenol images (3/6) over the gadoterate meglumine examinations (1/6), with no preference being shown for the remainder (2/6). First-pass CE-MRA is feasible with gadopiclenol at 0.05 mmol Gd/kg with at least the same arterial signal enhancement and image quality as gadoterate meglumine at 0.1 mmol Gd/kg.

Computerized assessment of background parenchymal enhancement on breast dynamic contrast-enhanced-MRI including electronic lesion removal.

Current clinical assessment qualitatively describes background parenchymal enhancement (BPE) as minimal, mild, moderate, or marked based on the visually perceived volume and intensity of enhancement in normal fibroglandular breast tissue in dynamic contrast-enhanced (DCE)-MRI. Tumor enhancement may be included within the visual assessment of BPE, thus inflating BPE estimation due to angiogenesis within the tumor. Using a dataset of 426 MRIs, we developed an automated method to segment breasts, electronically remove lesions, and calculate scores to estimate BPE levels. A U-Net was trained for breast segmentation from DCE-MRI maximum intensity projection (MIP) images. Fuzzy -means clustering was used to segment lesions; the lesion volume was removed prior to creating projections. U-Net outputs were applied to create projection images of both, affected, and unaffected breasts before and after lesion removal. BPE scores were calculated from various projection images, including MIPs or average intensity projections of first- or second postcontrast subtraction MRIs, to evaluate the effect of varying image parameters on automatic BPE assessment. Receiver operating characteristic analysis was performed to determine the predictive value of computed scores in BPE level classification tasks relative to radiologist ratings. Statistically significant trends were found between radiologist BPE ratings and calculated BPE scores for all breast regions (Kendall correlation, ). Scores from all breast regions performed significantly better than guessing ( from the -test). Results failed to show a statistically significant difference in performance with and without lesion removal. BPE scores of the affected breast in the second postcontrast subtraction MIP after lesion removal performed statistically greater than random guessing across various viewing projections and DCE time points. Results demonstrate the potential for automatic BPE scoring to serve as a quantitative value for objective BPE level classification from breast DCE-MR without the influence of lesion enhancement.

Treatment planning and delivery practice of lung SBRT: Results of the 2022 ESTRO physics survey

Background and purposeThe use of Stereotactic Body Radiation Therapy (SBRT) in lung cancer is increasing. However, there is no consensus on the most appropriate treatment planning and delivery practice for lung SBRT. To gauge the range of practice, quantify its variability and identify where consensus might be achieved, ESTRO surveyed the medical physics community. Materials and methodsAn online survey was distributed to ESTRO’s physicist membership in 2022, covering experience, dose and fractionation, target delineation, dose calculation and planning practice, imaging protocols, and quality assurance. ResultsTwo-hundred and forty-four unique answers were collected after data cleaning. Most respondents were from Europe the majority of which had more than 5 years’ experience in SBRT. The large majority of respondents deliver lung SBRT with the VMAT technique on C-arm Linear Accelerators (Linacs) employing daily pre-treatment CBCT imaging. A broad spectrum of fractionation schemes were reported, alongside an equally wide range of dose prescription protocols. A clear preference was noted for prescribing to 95% or greater of the PTV. Several issues emerged regarding the dose calculation algorithm: 22% did not state it while 24% neglected to specify the conditions under which the dose was calculated. Contouring was usually performed on Maximum or Average Intensity Projection images while dose was mainly computed on the latter. No clear indications emerged for plan homogeneity, complexity, and conformity assessment. Approximately 40% of the responders participated in inter-centre credentialing of SBRT in the last five years. Substantial differences emerged between high and low experience centres, with the latter employing less accurate algorithms and older equipment. ConclusionThe survey revealed an evident heterogeneity in numerous aspects of the clinical implementation of lung SBRT treatments. International guidelines and codes of practice might promote harmonisation.

[Automatic detection method of intracranial aneurysms on maximum intensity projection images based on SE-CaraNet].

Conventional maximum intensity projection (MIP) images tend to ignore some morphological features in the detection of intracranial aneurysms, resulting in missed detection and misdetection. To solve this problem, a new method for intracranial aneurysm detection based on omni-directional MIP image is proposed in this paper. Firstly, the three-dimensional magnetic resonance angiography (MRA) images were projected with the maximum density in all directions to obtain the MIP images. Then, the region of intracranial aneurysm was prepositioned by matching filter. Finally, the Squeeze and Excitation (SE) module was used to improve the CaraNet model. Excitation and the improved model were used to detect the predetermined location in the omni-directional MIP image to determine whether there was intracranial aneurysm. In this paper, 245 cases of images were collected to test the proposed method. The results showed that the accuracy and specificity of the proposed method could reach 93.75% and 93.86%, respectively, significantly improved the detection performance of intracranial aneurysms in MIP images.

Posterior cerebral artery (PCA)-accessory PCA (hyperplastic anterior choroidal artery) anastomosis detected on magnetic resonance angiography.

To describe a case of posterior cerebral artery (PCA)-accessory PCA (hyperplastic anterior choroidal artery) anastomosis detected on magnetic resonance angiography. A 76-year-old man with a history of cerebral infarction underwent cranial magnetic resonance (MR) imaging and MR angiography of the intracranial region for the evaluation of brain and vascular lesions. The MR machine was a 3-Tesla scanner. MR angiography was performed using a standard three-dimensional time-of-flight technique. There were two right PCAs. The parieto-occipital and calcarine arteries of the right PCA arose from the right ICA, indicative of accessory PCA, and there were three stenotic lesions at the proximal segment of this artery. The temporal artery of the right PCA originated from the basilar artery. A small anastomotic channel between these two arteries was identified on partial maximum intensity projection (MIP) images. Computed tomography angiography was additionally performed and the findings were confirmed. We speculated that the pressure gradient between the PCA and the accessory PCA enlarged the anastomotic channel. Partial MIP images are useful for diagnosing small arterial variations using MR angiography.

Lesion-conditioning of synthetic MRI-derived subtraction-MIPs of the breast using a latent diffusion model

The purpose of this feasibility study is to investigate if latent diffusion models (LDMs) are capable to generate contrast enhanced (CE) MRI-derived subtraction maximum intensity projections (MIPs) of the breast, which are conditioned by lesions. We trained an LDM with n = 2832 CE-MIPs of breast MRI examinations of n = 1966 patients (median age: 50 years) acquired between the years 2015 and 2020. The LDM was subsequently conditioned with n = 756 segmented lesions from n = 407 examinations, indicating their location and BI-RADS scores. By applying the LDM, synthetic images were generated from the segmentations of an independent validation dataset. Lesions, anatomical correctness, and realistic impression of synthetic and real MIP images were further assessed in a multi-rater study with five independent raters, each evaluating n = 204 MIPs (50% real/50% synthetic images). The detection of synthetic MIPs by the raters was akin to random guessing with an AUC of 0.58. Interrater reliability of the lesion assessment was high both for real (Kendall’s W = 0.77) and synthetic images (W = 0.85). A higher AUC was observed for the detection of suspicious lesions (BI-RADS ≥\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge $$\\end{document} 4) in synthetic MIPs (0.88 vs. 0.77; p = 0.051). Our results show that LDMs can generate lesion-conditioned MRI-derived CE subtraction MIPs of the breast, however, they also indicate that the LDM tended to generate rather typical or ‘textbook representations’ of lesions.

Diagnosis of a Dural Arteriovenous Fistula Involving the Superior Sagittal Sinus: The MMA Sign on Routine 3D-TOF MR Angiography

The main feeding artery of a dural arteriovenous fistula (DAVF) involving the superior sagittal sinus (SSS) is the middle meningeal artery (MMA). MMA extends continuously from the proximal part to SSS in DAVF involving SSS. It is possible to diagnose DAVF involving SSS by evaluating the proximal part of MMA on routine three-dimensional time-of-flight MR angiography (MRA). We termed the finding in an anteroposterior maximum intensity projection (MIP) image of routine MRA in which MMA was continuously visualized at the top of the imaging slab (the upper corpus callosum level) without tapering as the MMA sign. The purpose of the present study was to examine the frequency of the MMA sign on routine MRA in patients with DAVF involving SSS and control patients. Subjects comprised 18 patients with DAVF involving SSS confirmed by angiography and 871 control subjects who underwent routine MRA. The presence of the MMA sign was retrospectively evaluated using an anteroposterior MIP image of routine MRA in patients with DAVF involving SSS and control patients. The MMA sign was observed in 17 of the 18 (94%) patients with DAVF involving SSS. In one patient with DAVF involving the posterior part of SSS without the MMA sign, the main feeding artery was the occipital artery, not MMA. The MMA sign was observed in 13 of the 871 (1.5%) control patients. The MMA sign on routine MRA is useful, suggesting DAVF involving SSS.

Adult age estimation from the sternum using maximum intensity projection images of CT and data mining in a Chinese population.

This study aimed to explore and develop data mining models for adult age estimation based on CT reconstruction images from the sternum. Maximum intensity projection (MIP) images of chest CT were retrospectively collected from a modern Chinese population, and data from 2700 patients (1349 males and 1351 females) aged 20 to 70years were obtained. A staging technique within four indicators was applied. Several data mining models were established, and mean absolute error (MAE) was the primary comparison parameter. The intraobserver and interobserver agreement levels were good. Within internal validation, the optimal data mining model obtained the lowest MAE of 9.08 in males and 10.41 in females. For the external validation (N = 200), MAEs were 7.09 in males and 7.15 in females. In conclusion, the accuracy of our model for adult age estimation was among similar studies. MIP images of the sternum could be a potential age indicator. However, it should be combined with other indicators since the accuracy level is still unsatisfactory.

Evaluation of renal arteries in hypertensive patients by multi-detector computed tomography

Introduction: Among various causes of hypertension, only 1 to 2% is renovascular hypertension which may be characterized by the various reasons in renal vascular supply. Multi-detector computed tomography is used to know about the details of the vascular structures in patients. This study aims to evaluate the renal arteries in hypertensive patients. Methods: A prospective observational study was conducted among 93 hypertensive patients. Contrastenhanced computed tomography of the abdomen and pelvis was conducted, and measurements were obtained from the axial section of the maximum intensity projection image. Data were analyzed using SPSS version 23.0. Independent t-test and Pearson’s Correlation were used. The level of statistical significance was set at p<0.05. Results: The study found mean lengths for the right and left main renal arteries to be 40.33±10.26 mm and 32.36±9.55 mm, and diameters were 4.31±0.86 mm and 4.16±0.81 mm. No significant sex-based differences were observed. However, a significant age-related difference was noted in the length (p=0.012) and diameter (p=0.036) of the right main artery within the 20 to 29 and 80 to 89 years age groups. Weak correlations were observed between left renal artery length and age (r=0.221, p=0.33) and mean right renal artery diameter and age (r=-0.218, p=0.036). Prevalence of accessory renal arteries and early branches was 19.35% and 16.10% respectively. Conclusions: This study found that there were no statistically significant differences in renal arteries dimensions of hypertensive patients with different age groups and genders. Although the proportion of early renal artery branching and accessory arteries are found to be similar to previous studies there may be other associated factors for all hypertensive patients who don’t have early renal branches or accessory arteries.

Radiological evaluation of middle meningeal artery by 3D rotational angiography.

This study aimed to evaluate the topographic features and branches of the middle meningeal artery (MMA) by three-dimensional rotational angiography (3DRA) and describe its variations' radiological classification based on previous clinical examples of cadaver studies and literature. We consecutively evaluated 87 cerebral hemispheres, including 32 females and 49 right sides between May 2020 and December 2021 who had undergone unilateral or bilateral cerebral and carotid artery 3D rotational angiography imaging by CCA injection and between 18 and 76-years-old. Maximum intensity projection images with 10-30 mm slice thickness were used for the morphological evaluations and measurements of MMA and its foramen, canal, and branches. The diameters of the common carotid artery, internal carotid artery, and external carotid artery were significantly smaller in females than in men (p = 0.021, 0.021, and <0.001, respectively). According to the branching pattern, the most common pattern of the MMA was Type Ia (49.4%). The ophthalmic artery completely originated from MMA in the 1 (1.1%) cerebral hemisphere. The MMA arises from the ophthalmic artery in 2 cerebral hemispheres (2.3%), and the ophthalmic artery and maxillary artery in 2 cerebral hemispheres (2.3%). It was observed that the branching pattern may show differences when compared to the cadaver studies with a radiologic evaluation with 3D-RA.

Evaluation of Venous Structures that Are Involved in Transsylvian Approach Using 3D Rotational Venography.

In the transsylvian (TS) approach, as characterized by clipping surgery, the presurgical visualization of the superficial middle cerebral vein (SMCV) can help change the surgical approach to ensure safe microsurgery. Nevertheless, identifying preoperatively the venous structures that are involved in this approach is difficult. In this study, we investigated the venous structures that are involved in the TS approach using three-dimensional (3D) rotational venography (3D-RV) and evaluated the effectiveness of this method for presurgical simulation. Patients who underwent 3D-RV between August 2018 and June 2020 were involved in this retrospective study. The 3D-RV and partial maximum intensity projection images with a thickness of 5 mm were computationally reconstructed. The venous structures were subdivided into the following three portions according to the anatomic location: superficial, intermediate, and basal portions. In the superficial portion, predominant frontosylvian veins were observed on 31 (41%) sides, predominant temporosylvian veins on seven (9%) sides, and equivalent fronto- and temporosylvian veins on 28 (37%) sides. The veins in the intermediate (deep middle cerebral and uncal veins) and basal portions (frontobasal bridging veins) emptied into the SMCV on 57 (75%) and 34 (45%) sides, respectively. The 3D-RV images were highly representative of the venous structures observed during microsurgery. In this study, 3D-RV was utilized to capture the details of the venous structures from the superficial to the deep portions. Presurgical simulation of the venous structures that are involved in the TS approach using 3D-RV may increase the safety of microsurgical approaches.

The guiding value of the cinematic volume rendering technique in the preoperative diagnosis of brachial plexus schwannoma.

This study aimed to explore and compare the guiding value of Maximum Intensity Projection (MIP) and Cinematic Volume Rendering Technique (cVRT) in the preoperative diagnosis of brachial plexus schwannomas. We retrospectively analyzed the clinical and imaging data of 45 patients diagnosed with brachial plexus schwannomas at the First Affiliated Hospital of Zhengzhou University between January 2020 and December 2022. The enhanced three-dimensional short recovery time inversion-recovery fast spin-echo imaging (3D-STIR-SPACE) sequence served as source data for the reconstruction of MIP and cVRT. Two independent observers scored the image quality and evaluated the location of the tumor and the relationship between the tumor and the brachial plexus. The image quality scores of the two reconstruction methods were compared using the nonparametric Wilcoxon signed-rank test, and the consistency between the image and surgical results was assessed using the weighted kappa. Compared to MIP images, cVRT images had a better performance of overall image quality (p < 0.001), nerve and lump visualization (p < 0.001), spatial positional relationship conspicuity (p < 0.001), and diagnostic confidence (p < 0.001). Additionally, the consistency between the cVRT image results and surgical results (kappa =0.913, P<0.001) was higher than that of the MIP images (kappa =0.829, P<0.001). cVRT provides a high guiding value in the preoperative diagnosis of brachial plexus schwannomas and is an important basis for formulating surgical plans.

MEDS-Net: Multi-encoder based self-distilled network with bidirectional maximum intensity projections fusion for lung nodule detection

Early detection of lung cancer increases cure rates, making precise detection of lung nodules in computed tomography (CT) images crucial. However, creating an accurate computer-aided detection (CADe) system is challenging due to lung structure complexity and nodule heterogeneity. We present a lung nodule detection scheme, inspired by radiologist workflow, fusing CT scan sub-volumes with bidirectional maximum intensity projection (MIP) images within a single architecture. We have developed a novel multi-encoder-based network (MEDS-Net) using self-distillation to learn from three types of inputs: 3D sub-volume, forward, and backward MIP images. MEDS-Net utilizes three encoders to extract insights, passed to the decoder via attention units to suppress redundant features. The decoder employs a self-distillation mechanism, connecting to a distillation block with four auxiliary lung nodule detectors, accelerating convergence and enhancing learning ability. The auxiliary detectors are used during inference to reduce false positives. Our scheme, tested on 888 LIDC-IDRI dataset scans, achieved a 93.6% competition performance metric score, illustrating that fusing bidirectional MIP images with raw CT slices and auxiliary detectors empowers MEDS-Net to accurately detect lung nodules while minimizing false positives.

Improved small vessel visibility in diabetic foot arteriography using dual-energy CT

To test the feasibility and performance of dual-energy computed tomography (DECT) in foot arteriography of diabetic patients, where contrast medium is largely reduced within the small vessels. A total of 50 diabetic patients were enrolled prospectively, where DECT was acquired immediately after the CT angiography (CTA, group A) of the lower extremity. Two images were derived from the DECT data, one optimal virtual monochromatic image (VMI, group B) and one fusion image (group C), both of which were compared against the CTA image for visualising the foot arteries. The contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were evaluated. The arterial course and contrast were graded each using a five-point scale. The clarity of small vessel depiction was quantified by comparing the number of plantar metatarsal arteries found in the maximum intensity projection image. The median CNRs and SNRs obtained in group B were approximately 45% and 20% higher than those in groups A and C, respectively (p<0.05). Group B also received higher subjective scores on the posterior tibial artery and the foot arteries (all >3) than groups A and C. The number of visible branches of the plantar metatarsal arteries was found to be substantially higher (p<0.05) in group B (median=6) than in groups A (median=2) and C (median=4). DECT was found to be superior to conventional CTA in foot arteriography, and beyond the lower extremity, it might be a general favourable solution for imaging regions with small vessels and reduced contrast medium.

Facilitating cell segmentation with the projection-enhancement network

Contemporary approaches to instance segmentation in cell science use 2D or 3D convolutional networks depending on the experiment and data structures. However, limitations in microscopy systems or efforts to prevent phototoxicity commonly require recording sub-optimally sampled data that greatly reduces the utility of such 3D data, especially in crowded sample space with significant axial overlap between objects. In such regimes, 2D segmentations are both more reliable for cell morphology and easier to annotate. In this work, we propose the projection enhancement network (PEN), a novel convolutional module which processes the sub-sampled 3D data and produces a 2D RGB semantic compression, and is trained in conjunction with an instance segmentation network of choice to produce 2D segmentations. Our approach combines augmentation to increase cell density using a low-density cell image dataset to train PEN, and curated datasets to evaluate PEN. We show that with PEN, the learned semantic representation in CellPose encodes depth and greatly improves segmentation performance in comparison to maximum intensity projection images as input, but does not similarly aid segmentation in region-based networks like Mask-RCNN. Finally, we dissect the segmentation strength against cell density of PEN with CellPose on disseminated cells from side-by-side spheroids. We present PEN as a data-driven solution to form compressed representations of 3D data that improve 2D segmentations from instance segmentation networks.

New Data-Driven Gated (DDG) PET/CT for Radiation Treatment Planning of NSCLC

PET/CT for RT simulation of NSCLC is typically conducted in two separate imaging sessions of gated 4D-CT in radiation oncology and fusion with non-gated PET/CT in diagnostic imaging, making treatment response assessment (TRA) with PET/CT and radiation treatment planning (RTP) challenging. To remedy this short-coming, we designed a new data-driven gated (DDG) PET/CT, based on the self-gated PET and self-gated CT data to derive the gated PET/CT data free of tumor blurring and misregistration artifacts without any respiratory monitoring device (ease of use and cost reduction). The new DDG PET/CT also provides the important 4D-CT information of end-inspiratory (EI), end-expiratory (EE), maximum-intensity-projection (MIP) and average-intensity-projection (AIP) CT's. The total imaging time is < 15 min, which makes DDG PET/CT simulation in a single session without any respiratory monitoring device possible. Acquisition is standard PET/CT imaging protocol followed by a cine CT imaging of the tumor area. We utilized the commercial DDG PET from GE Discovery PET/CT and designed a new DDG CT for attenuation correction of the DDG PET for reduction of tumor motion and mis-registration. The AIP and MIP images were from the average and maximum pixel values of the cine CT images, respectively. The cine CT images with the largest and smallest average CT number in the lung region were identified as the EE and EI CT images, respectively. For the image slices without any lung region present, the largest and smallest expansions of the body outline contour were selected to be the EE and EI CT phases, respectively. The AIP and EE CT images were used for attenuation correction of the PET and DDG PET data, respectively. Both DDG PET/CT and 4D-CT of (EI, EE, AIP and MIP) are for RT simulation of NSCLC. 38 4D-CT patient data sets were compared at the EE and EI phases between our DDG CT and 4D-CT to demonstrate the applicability of the newly designed DDG CT. A prototype software on a Dell PC of i5-6500 CPU has been successfully developed to enable DDG PET/CT and 4D-CT on seven GE Discovery PET/CT scanners. The operating system was Ubuntu and the computer language was Python. In the EE phase, the images selected by DDG CT and 4D CT were identical 62.5±21.6% of the time. In the EI phase, the images selected by DDG CT and 4D CT were identical 68.2±18.9% of the time. Inspection of the EE and EI phases of DDG CT and 50% and 0% of 4D-CT demonstrated both data sets of DDG CT and 4D CT were almost identical. A new DDG PET/CT and 4D-CT in a single imaging session without any hardware gating has been developed for TRA and RTP of NSCLC. The utility is available on the network and it enables all PET/CT scanners on the network for TRA and RTP. The new DDG CT provides the benefits of 4D-CT without any requirement of external hardware gating and make possible DDG PET/CT free of tumor motion and misregistration artifacts.

Convolutional neural network-based program to predict lymph node metastasis of non-small cell lung cancer using 18F-FDG PET.

To develop a convolutional neural network (CNN)-based program to analyze maximum intensity projection (MIP) images of 2-deoxy-2-[F-18]fluoro-D-glucose (FDG) positron emission tomography (PET) scans, aimed at predicting lymph node metastasis of non-small cell lung cancer (NSCLC), and to evaluate its effectiveness in providing diagnostic assistance to radiologists. We obtained PET images of NSCLC from public datasets, including those of 435 patients with available N-stage information, which were divided into a training set (n = 304) and a test set (n = 131). We generated 36 maximum intensity projection (MIP) images for each patient. A residual network (ResNet-50)-based CNN was trained using the MIP images of the training set to predict lymph node metastasis. Lymph node metastasis in the test set was predicted by the trained CNN as well as by seven radiologists twice: first without and second with CNN assistance. Diagnostic performance metrics, including accuracy and prediction error (the difference between the truth and the predictions), were calculated, and reading times were recorded. In the test set, 67 (51%) patients exhibited lymph node metastases and the CNN yielded 0.748 predictive accuracy. With the assistance of the CNN, the prediction error was significantly reduced for six of the seven radiologists although the accuracy did not change significantly. The prediction time was significantly reduced for five of the seven radiologists with the median reduction ratio 38.0%. The CNN-based program could potentially assist radiologists in predicting lymph node metastasis by increasing diagnostic confidence and reducing reading time without affecting diagnostic accuracy, at least in the limited situations using MIP images.

Deep Learning Reconstruction Improves the Image Quality of CT Angiography Derived From 80-kVp Cerebral CT Perfusion Data

To investigate the impact of the deep learning reconstruction (DLR) technique on the image quality of CT angiography (CTA) derived from 80-kVp cerebral CT perfusion (CTP) data and compare it with hybrid-iterative reconstruction (HIR). Thirty-three patients underwent CTP at 80 kVp were prospectively enrolled. CTP data were reconstructed with HIR and DLR. Four image datasets were reconstructed: HIRpeak and DLRpeak were single arterial phase images derived from the time point showing the peak value, HIRtMIP and HIRtAve were time-resolved maximum intensity projection image and time-resolved average image derived from three time points with the greatest enhancement of HIR. The mean CT values, standard deviation, signal-to-noise ratio, and contrast-to-noise ratio of the internal carotid artery and basilar artery were compared among the four image dataset. Image quality was performed using a five-point rating scale. Arterial stenosis was evaluated. DLRpeak had the highest CT value and contrast-to-noise ratio in the internal carotid artery and basilar artery (all p < 0.001). DLRpeak showed the best subjective image quality and had the highest score (4.93 ± 0.4) compared to the other three HIR CTA images (all p < 0.001). The degree of vascular stenosis was consistent among the four evaluated sequences (HIRtAve, HIRpeak, and HIRtMIP DLRpeak). For CTA derived from 80-kVp cerebral CTP data, images reconstructed with deep learning showed better image quality and improved intracranial artery visualization than those processed with HIR and other currently used techniques.

Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks

ObjectivesTo develop a deep learning–based method for contrast-enhanced breast lesion detection in ultrafast screening MRI.Materials and methodsA total of 837 breast MRI exams of 488 consecutive patients were included. Lesion’s location was independently annotated in the maximum intensity projection (MIP) image of the last time-resolved angiography with stochastic trajectories (TWIST) sequence for each individual breast, resulting in 265 lesions (190 benign, 75 malignant) in 163 breasts (133 women). YOLOv5 models were fine-tuned using training sets containing the same number of MIP images with and without lesions. A long short-term memory (LSTM) network was employed to help reduce false positive predictions. The integrated system was then evaluated on test sets containing enriched uninvolved breasts during cross-validation to mimic the performance in a screening scenario.ResultsIn five-fold cross-validation, the YOLOv5x model showed a sensitivity of 0.95, 0.97, 0.98, and 0.99, with 0.125, 0.25, 0.5, and 1 false positive per breast, respectively. The LSTM network reduced 15.5% of the false positive prediction from the YOLO model, and the positive predictive value was increased from 0.22 to 0.25.ConclusionsA fine-tuned YOLOv5x model can detect breast lesions on ultrafast MRI with high sensitivity in a screening population, and the output of the model could be further refined by an LSTM network to reduce the amount of false positive predictions.Clinical relevance statementThe proposed integrated system would make the ultrafast MRI screening process more effective by assisting radiologists in prioritizing suspicious examinations and supporting the diagnostic workup.Key Points• Deep convolutional neural networks could be utilized to automatically pinpoint breast lesions in screening MRI with high sensitivity.• False positive predictions significantly increased when the detection models were tested on highly unbalanced test sets with more normal scans.• Dynamic enhancement patterns of breast lesions during contrast inflow learned by the long short-term memory networks helped to reduce false positive predictions.

Imaging features of cardioembolic stroke on 4-dimensional computed tomography angiography.

Identifying cardioembolic stroke is important for the decision-making of endovascular treatment and anticoagulation therapy. We aimed to explore the features of cardioembolic stroke on 4-dimensional (4D) computed tomography angiography (4D-CTA) and assess whether these features can assist in classifying stroke etiology. In this retrospective study, we analyzed the images of 294 patients with acute ischemic stroke (AIS) from July 2020 to February 2022 at the First Affiliated Hospital of Chongqing Medical University, which had been consecutively collected. The data of 110 patients with occlusion of the M1/M2 segment of the middle cerebral artery (MCA) with/without intracranial internal carotid artery (ICA) occlusion were analyzed to calculate the clot burden score (CBS) and collateral score (CS), and the data of 88 patients with a clear origin and distal part were analyzed to measure clot length. Maximum intensity projection (MIP) and time MIP (tMIP) post-processing were used to assess the clot features. The Mann-Whitney U test was used to compare the clot characteristics between the 2 groups. Binary logistic regression was performed to assess the association between the image characteristics and cardioembolic stroke. Moreover, the receiver operating characteristic (ROC) curve was used to test the diagnostic efficacy of MIP/tMIP clot features in classifying cardioembolic stroke. Age, high-risk factors for cerebrovascular disease, high/medium-risk sources of cardioembolic stroke, clot length, CBS, and CS were significantly different between the cardioembolic stroke group and non-cardioembolic stroke group (P<0.05). In the cardioembolic stroke group, the median MIP and tMIP clot length was 12 mm [interquartile range (IQR), 8.3-17.4 mm] and 9.3 mm (IQR, 6.8-14.3 mm), respectively. In the non-cardioembolic stroke group, the median MIP and tMIP clot length was 6.5 mm (IQR, 4.7-11.5 mm) and 5.8 mm (IQR, 3.9-10.6 mm), respectively. Binary logistic regression showed that cardioembolic stroke was significantly associated with MIP-clot length [odds ratio (OR), 1.15; 95% confidence interval (CI): 1.02-1.29; P<0.05], tMIP-clot length (OR, 1.18; 95% CI: 1.02-1.36; P<0.05), and tMIP-CBS (OR, 3.96; 95% CI: 1.08-14.58; P<0.05). The area under the ROC curve (AUC) values of MIP clot length for identifying cardioembolic stroke were 0.75 (95% CI: 0.65-0.84, P<0.05), with a cut-off value of >7.4 mm [sensitivity: 84.62% (95% CI: 69.50-94.10%); specificity: 59.18% (95% CI: 44.20-73.00%)]. The AUC value of tMIP clot length was 0.72 (95% CI: 0.61-0.81, P<0.05), with a cut-off value of >5.4 mm [sensitivity: 92.31% (95% CI: 79.10-98.40%); specificity: 48.98% (95% CI: 34.40-63.70%)]. Clot length and CBS were overestimated on MIP images. Among the clot characteristics, clot length could identify cardioembolic stroke.