Short Acquisition Time Research Articles

Need for objective task-based evaluation of deep learning-based denoising methods: A study in the context of myocardial perfusion SPECT.

Artificial intelligence-based methods have generated substantial interest in nuclear medicine. An area of significant interest has been the use of deep-learning (DL)-based approaches for denoising images acquired with lower doses, shorter acquisition times, or both. Objective evaluation of these approaches is essential for clinical application. DL-based approaches for denoising nuclear-medicine images have typically been evaluated using fidelity-based figures of merit (FoMs) such as root mean squared error (RMSE) and structural similarity index measure (SSIM). However, these images are acquired for clinical tasks and thus should be evaluated based on their performance in these tasks. Our objectives were to: (1) investigate whether evaluation with these FoMs is consistent with objective clinical-task-based evaluation; (2) provide a theoretical analysis for determining the impact of denoising on signal-detection tasks; and (3) demonstrate the utility of virtual imaging trials (VITs) to evaluate DL-based methods. A VIT to evaluate a DL-based method for denoising myocardial perfusion SPECT (MPS) images was conducted. To conduct this evaluation study, we followed the recently published best practices for the evaluation of AI algorithms for nuclear medicine (the RELAINCE guidelines). An anthropomorphic patient population modeling clinically relevant variability was simulated. Projection data for this patient population at normal and low-dose count levels (20%, 15%, 10%, 5%) were generated using well-validated Monte Carlo-based simulations. The images were reconstructed using a 3-D ordered-subsets expectation maximization-based approach. Next, the low-dose images were denoised using a commonly used convolutional neural network-based approach. The impact of DL-based denoising was evaluated using both fidelity-based FoMs and area under the receiver operating characteristic curve (AUC), which quantified performance on the clinical task of detecting perfusion defects in MPS images as obtained using a model observer with anthropomorphic channels. We then provide a mathematical treatment to probe the impact of post-processing operations on signal-detection tasks and use this treatment to analyze the findings of this study. Based on fidelity-based FoMs, denoising using the considered DL-based method led to significantly superior performance. However, based on ROC analysis, denoising did not improve, and in fact, often degraded detection-task performance. This discordance between fidelity-based FoMs and task-based evaluation was observed at all the low-dose levels and for different cardiac-defect types. Our theoretical analysis revealed that the major reason for this degraded performance was that the denoising method reduced the difference in the means of the reconstructed images and of the channel operator-extracted feature vectors between the defect-absent and defect-present cases. The results show the discrepancy between the evaluation of DL-based methods with fidelity-based metrics versus the evaluation on clinical tasks. This motivates the need for objective task-based evaluation of DL-based denoising approaches. Further, this study shows how VITs provide a mechanism to conduct such evaluations computationally, in a time and resource-efficient setting, and avoid risks such as radiation dose to the patient. Finally, our theoretical treatment reveals insights into the reasons for the limited performance of the denoising approach and may be used to probe the effect of other post-processing operations on signal-detection tasks.

Time Coding-Based Single-Photon-Counting Lidar for Obtaining Spatial Location

This paper proposes a single-photon-counting lidar based on time coding that can obtain the target’s spatial location and measure the distance and azimuth angle in real time without needing a scanning device. Multiple optical fibers were used to introduce laser echo photons into a single-pixel single-photon detector. According to the deviation in the detection time of the echo photons passing through different optical fibers, multiple distances can be obtained simultaneously. Combining the measured distances with the fiber spacing allows the calculation of the distance, azimuth angle, and spatial coordinates of the target. This lidar has the advantages of high photon detection efficiency, short signal acquisition time, and low cost compared to array detectors.

Multislice B1 Mapping Method Using Magnetic Resonance Composite Spin Echo Sequences and Simultaneous Echo Refocusing

Radiofrequency (RF) transmit field (B1) mapping is a promising method in mitigating the B1 inhomogeneity in various magnetic resonance imaging (MRI) applications. Although several phase- or magnitude-based B1 mapping methods have been proposed, these methods often require complex modeling, long acquisition time, or specialized MRI sequences. A recently introduced simultaneous echo refocusing (SER) technique can be applied in the B1 mapping method to extend the three-dimensional (3D) spatial coverage only without long data acquisition. Therefore, in this study, a multislice B1 mapping method using composite spin echo sequences and SER techniques is proposed to obtain more accurate B1 mapping with short data acquisition time. To evaluate the performance of the proposed B1 mapping method, computational simulations were performed and compared with Morrell’s method, double angle method, and Yarnykh’s method. These results showed that the angle-to-noise ratio of the proposed B1 mapping method has wider B1 range compared to that of other B1 mapping methods. In addition, the proposed B1 mapping methods were compared to the multislice iterative signal intensity mapping method in both phantom and in vivo human experiments, and there was no remarkable difference between the two methods regarding the flip angle distribution in these experiments. Based on these results, this study demonstrated that the proposed B1 mapping method is suitable for accurately measuring B1 propagation under the condition providing reduced scan time and wider 3D coverage of B1 mapping by applying composite RF pulse and SER techniques into the phase-sensitive method.

A radiofrequency coil for infants and toddlers.

Infants and toddlers are a challenging population on which to perform MRI of the brain, both in research and clinical settings. Due to the large range in head size during the early years of development, paediatric neuro-MRI requires a radiofrequency (RF) coil, or set of coils, that is tailored to head size to provide the highest image quality. Mitigating techniques must also be employed to reduce and correct for subject motion. This manuscript describes an RF coil with a tailored mechanical-electrical design that can adapt to the head size of three-month-old infants to three-year-old toddlers. The RF coil was designed with tight-fitting coil elements to improve SNR in comparison to commercially available adult head coils, while simultaneously aiding in immobilization. The coil was designed without visual obstruction to facilitate an unimpeded view of the child's face and the potential application of camera or motion-tracking systems. Despite the lack of elements over the face, the paediatric coil produced higher SNR over most of the brain compared to adult coils, including more than 2-fold in the periphery. Acceleration rates of 4-fold in each Cartesian direction could be achieved. High SNR allowed for short acquisition times through accelerated imaging protocols, reduced the probability of motion during a scan. Modification to the acquisition protocol, with immobilization of the head through the adjustable coil geometry, and subsequently combined with a motion tracking system provides a compelling platform for scanning paediatric populations without sedation and with improved image quality.

Quantitative measurements and morphological evaluation of fetal cardiovascular structures with fetal cardiac MRI

PurposeFetal cardiac magnetic resonance imaging (FCMR) can be used as an imaging modality in fetal cardiovascular evaluation as studied in recent years. We aimed to evaluate cardiovascular morphology using FCMR and to observe the development of cardiovascular structures according to gestational age (GA) in pregnant women. MethodIn our prospective study, 120 pregnant women between 19 and 37 weeks of gestation in whom absence of cardiac anomaly could not be excluded by ultrasonography (US) or, who were referred to us for magnetic resonance imaging (MRI) for suspected non-cardiovascular system pathology, were included. According to the axis of the fetal heart, axial, coronal, and sagittal multiplanar steady-state free precession (SSFP) and 'real time' untriggered SSFP sequence, respectively, were obtained. The morphology of the cardiovascular structures and their relationships with each other were evaluated, and their sizes were measured. ResultsSeven cases (6.3%) contained motion artefacts that did not allow the assessment and measurement of cardiovascular morphology, and three (2.9%) cases with cardiac pathology in the analysed images were excluded from the study. The study included a total of 100 cases. Cardiac chamber diameter, heart diameter, heart length, heart area, thoracic diameter, and thoracic area were measured in all fetuses. The diameters of the aorta ascendens (Aa), aortic isthmus (Ai), aorta descendens (Ad), main pulmonary artery (MPA), ductus arteriosus (DA, superior vena cava (SVC), and inferior vena cava (IVC) were measured in all fetuses. The left pulmonary artery (LPA) was visualised in 89 patients (89%). The right PA (RPA) was visualised in 99 (99%) cases. Four pulmonary veins (PVs) were seen in 49 (49%) cases, three in 33 (33%), and two in 18 (18%). High correlation values were found for all diameter measurements performed with GW. ConclusionIn cases where US cannot achieve adequate image quality, FCMR can contribute to diagnosis. The very short acquisition time and parallel imaging technique with the SSFP sequence allow for adequate image quality without maternal or fetal sedation.

MR Vascular Fingerprinting with Hybrid Gradient–Spin Echo Dynamic Susceptibility Contrast MRI for Characterization of Microvasculature in Gliomas

Characterization of tumor microvasculature is important in tumor assessment and studying treatment response. This is possible by acquiring vascular biomarkers with magnetic resonance imaging (MRI) based on dynamic susceptibility contrast (DSC). We propose magnetic resonance vascular fingerprinting (MRVF) for hybrid echo planar imaging (HEPI) acquired during the first passage of the contrast agent (CA). The proposed approach was evaluated in patients with gliomas, and we simultaneously estimated vessel radius and relative cerebral blood volume. These parameters were also compared to the respective values estimated using the previously introduced vessel size imaging (VSI) technique. The results of both methods were found to be consistent. MRVF was also found to be robust to noise in the estimation of the parameters. DSC-HEPI-based MRVF provides characterization of microvasculature in gliomas with a short acquisition time and can be further improved in several ways to increase our understanding of tumor physiology.

SYNCmoss software package for fitting Mössbauer spectra measured with a synchrotron Mössbauer source.

SYNCmoss is a software package dedicated to fitting Mössbauer spectra measured with a synchrotron Mössbauer source (SMS). Operation conditions of an SMS can be continuously varied from high resolution and low intensity to the opposite extreme. These variations influence the width and shape of the instrumental function. The main purpose of SYNCmoss is to fit data obtained with instrumental functions of various shapes. SYNCmoss allows the instrumental function to be extracted from the spectrum of a standard absorber, and then to utilize it in the fitting procedures for the samples studied. SYNCmoss is standalone software - it does not require installations of any software environment. Setting input parameters and the fitting procedure are controlled within a graphical user interface. High-intensity mode of the SMS leads to a short acquisition time, allowing for fast (for example, operando) measurements resulting in a long sequence of spectra with close or smoothly varying parameters. For such cases, SYNCmoss provides an option to fit a series of spectra in automatic mode. SYNCmoss provides fitting models for various cases of hyperfine interaction including the full Hamiltonian for the combined interaction. Finally, for generality, the software has the ability to also fit conventional Mössbauer spectra and simple cases of nuclear forward scattering spectra.

An Optimized Quantification Method for Marine Radioactivity Measurements: Application in the Southern Caspian Sea Using the KATERINA Underwater γ-Spectrometer

The underwater gamma-ray spectrometer KATERINA was calibrated in a special tank and then demonstrated in the Southern Caspian Sea to determine the radioactivity levels in seawater as well as in the sediment. The simulated marine efficiency of the in situ detection system was validated analyzing the high energetic (1764 keV of 214Bi and 2614 keV of 208Tl) gamma-ray peaks using their known activity concentration as determined from the low energy emissions. The analysis of the in situ gamma-ray spectra in a short acquisition time period provided quantitative data for 226Ra and 232Th progenies as well as for 40K. A satisfactory analysis was performed for quantifying the observed energy peaks in the seawater and sediment measurements acquired at the south coast of the Caspian Sea. The spectrum in the water tank was also analyzed using full spectrum analysis methods, and the reproduced spectrum was in a very good agreement with the experimental spectrum giving as an output the activity concentrations of the observed radionuclides.

Reliability of spinal cord measures based on synthetic T1-weighted MRI derived from multiparametric mapping (MPM)

Short MRI acquisition time, high signal-to-noise ratio, and high reliability are crucial for image quality when scanning healthy volunteers and patients. Cross-sectional cervical cord area (CSA) has been suggested as a marker of neurodegeneration and potential outcome measure in clinical trials and is conventionally measured on T1-weigthed 3D Magnetization Prepared Rapid Acquisition Gradient-Echo (MPRAGE) images. This study aims to reduce the acquisition time for the comprehensive assessment of the spinal cord, which is typically based on MPRAGE for morphometry and multi-parameter mapping (MPM) for microstructure. The MPRAGE is replaced by a synthetic T1-w MRI (synT1-w) estimated from the MPM, in order to measure CSA. SynT1-w images were reconstructed using the MPRAGE signal equation based on quantitative maps of proton density (PD), longitudinal (R1) and effective transverse (R2*) relaxation rates. The reliability of CSA measurements from synT1-w images was determined within a multi-center test-retest study format and validated against acquired MPRAGE scans by assessing the agreement between both methods. The response to pathological changes was tested by longitudinally measuring spinal cord atrophy following spinal cord injury (SCI) for synT1-w and MPRAGE using linear mixed effect models. CSA measurements based on the synT1-w MRI showed high intra-site (Coefficient of variation [CoV]: 1.43% to 2.71%) and inter-site repeatability (CoV: 2.90% to 5.76%), and only a minor deviation of -1.65 mm2 compared to MPRAGE. Crucially, by assessing atrophy rates and by comparing SCI patients with healthy controls longitudinally, differences between synT1-w and MPRAGE were negligible. These results demonstrate that reliable estimates of CSA can be obtained from synT1-w images, thereby reducing scan time significantly.

Magnetic particle based MRI thermometry at 0.2 T and 3 T

This study provides insight into the advantages and disadvantages of using ferrite particles embedded in agar gel phantoms as MRI temperature indicators for low-magnetic field scanners. We compare the temperature-dependent intensity of MR images at low-field (0.2 T) to those at high-field (3.0 T). Due to a shorter T1 relaxation time at low-fields, MRI scanners operating at 0.2 T can use shorter repetition times and achieve a significant T2⁎ weighting, resulting in strong temperature-dependent changes of MR image brightness in short acquisition times. Although the signal-to-noise ratio for MR images at 0.2 T MR is much lower than at 3.0 T, it is sufficient to achieve a temperature measurement uncertainty of about ±1.0 °C at 37 °C for a 90 μg/mL concentration of magnetic particles.

Effects of fitting methods, high b-values and image quality on diffusion and perfusion quantification and reproducibility in the calf

PurposesThe study aimed to optimize diffusion-weighted imaging (DWI) image acquisition and analysis protocols in calf muscles by investigating the effects of different model-fitting methods, image quality, and use of high b-value and constraints on parameters of interest (POIs). The optimized modeling methods were used to select the optimal combinations of b-values, which will allow shorter acquisition time while achieving the same reliability as that obtained using 16 b-values. MethodsTest-retest baseline and high-quality DWI images of ten healthy volunteers were acquired on a 3T MR scanner, using 16 b-values, including a high b-value of 1200 s/mm2, and structural T1-weighted images for calf muscle delineation. Three and six different fitting methods were used to derive ADC from monoexponential (ME) model and Dd, fp, and Dp from intravoxel incoherent motion (IVIM) model, with or without the high b-value. The optimized ME and IVIM models were then used to determine the optimal combinations of b-values, obtainable with the least number of b-values, using the selection criteria of coefficient of variance (CV) ≤10% for all POIs. ResultsThe find minimum multivariate algorithm was more flexible and yielded smaller fitting errors. The 2-steps fitting method, with fixed Dd, performed the best for IVIM model. The inclusion of high b-value reduced outliers, while constraints improved 2-steps fitting only. ConclusionsThe optimal numbers of b-values for ME and IVIM models were nine and six b-values respectively. Test-retest reliability analyses showed that only ADC and Dd were reliable for calf diffusion evaluation, with CVs of 7.22% and 4.09%.

4DCT is long overdue for improvement.

4DCT is long overdue for improvement.

Approaches to standardising the magnetic resonance image analysis of equine tendon lesions.

Low-field magnetic resonance imaging (MRI) has gained increasing importance to monitor equine tendon lesions. Comparing results between studies and cases is hampered, because image analysis approaches vary strongly. This study aimed to improve reliability, comparability and time efficiency of quantitative MRI image analysis. Induced tendon lesions were studied over a 24-week period with 10 follow-up MRI examinations. Signal intensities (SIs) of tendons, tendon lesions, cortical bone and background, as well as lesion cross-sectional areas (CSAs) were measured. Lesion SI standardisation with different formulas was evaluated, using histological findings as reference. Different types of region of interest (ROI) for lesion SI measurement were compared. Lesion CSA measurement at different levels was evaluated, using the calculated total lesion volume as reference. Subjective lesion identification and manual CSA and SI measurements were compared to an automated, algorithm-based approach. Lesion SI standardised using a quotient of lesion and background or cortical bone SI, correlated best with histologically determined lesion severity. Lesion SI in circular ROIs correlated strongly with lesion SI in free-hand whole-lesion ROIs. The level of the maximum lesion CSA shifted over time; the CSA maximum correlated strongly with lesion volume. In sequences with short acquisition time, algorithm-based automated lesion detection showed almost perfect agreement with subjective lesion identification. Automated measurement of CSA and SI was also feasible, with stronger correlation and better agreement with the manually obtained data for the SI than for the CSA. Our study may provide guidance for MRI image analysis of tendon healing. Reliable image analysis can be performed time-efficiently, particularly regarding lesion SI quantification.

Hairpin DNAs conformational changes inducing opposite-polarity photoelectric signals recovery for simultaneous monitoring of dual microRNAs

Building flexible and reliable photoelectrochemical (PEC) sensors capable of measuring multiple miRNAs simultaneously still suffers from a challenge. In this protocol, a unique multiplexed PEC biosensor for miRNA-141 and miRNA-155 was developed by Fe3O4 @SiO2 @CdS-HP1-Ag2S NPs and CdTe QDs-HP2-Au NPs nanobioprobes polarity switching mode. HP1 and HP2 can be simultaneously unfolded by the two targets. The corresponding rigid DNA double-strand structure makes the distance between CdS shells and Ag2S NPs even greater, exposing more photoactive sites of CdS shells and thus the enhanced photoanode current. Similarly, the exciton-plasmon interaction (EPI) between the CdTe QDs and the Au NPs is disrupted, resulting in the photocurrent recovery of the CdTe QDs. Through external magnetic force, the one-step electrode modification of each above nanobioprobe was realized and the photocurrent polarity switching was also achieved. The linearity range of the designed multiplexed PEC biosensor was from 50 fM to 10 nM, and the detection limits reached 40.8 fM and 37.5 fM, respectively, without using any bioamplification technology. In addition, the manufactured PEC biosensor has significant advantages in compactness, short signal acquisition time, cost-effectiveness, as well as stability and replicability. The unique design provides a new perspective for monitoring multiple miRNAs simultaneously.

Optimal clinical protocols for total-body 18F-FDG PET/CT examination under different activity administration plans

BackgroundHighly sensitive digital total-body PET/CT scanners (uEXPLORER) have great potential for clinical applications and fundamental research. Given their increasing sensitivity, low-dose scanning or snapshot imaging is now possible in clinics. However, a standardized total-body 18F-FDG PET/CT protocol is still lacking. Establishing a standard clinical protocol for total-body 18F-FDG PET/CT examination under different activity administration plans can help provide a theoretical reference for nuclear radiologists.MethodsThe NEMA image quality (IQ) phantom was used to evaluate the biases of various total-body 18F-FDG PET/CT protocols related to the administered activity, scan duration, and iterations. Several objective metrics, including contrast recovery (CR), background variability (BV), and contrast-to-noise ratio (CNR), were measured from different protocols. In line with the European Association of Nuclear Medicine Research Ltd. (EARL) guidelines, optimized protocols were suggested and evaluated for total-body 18F-FDG PET/CT imaging for three different injected activities.ResultsOur NEMA IQ phantom evaluation resulted in total-body PET/CT images with excellent contrast and low noise, suggesting great potential for reducing administered activity or shortening the scan duration. Different to the iteration number, prolonging the scan duration was the first choice for achieving higher image quality regardless of the activity administered. In light of image quality, tolerance of oncological patients, and the risk of ionizing radiation damage, the 3-min acquisition and 2-iteration (CNR = 7.54), 10-min acquisition and 3-iteration (CNR = 7.01), and 10-min acquisition and 2-iteration (CNR = 5.49) protocols were recommended for full-dose (3.70 MBq/kg), half-dose (1.95 MBq/kg), and quarter-dose (0.98 MBq/kg) activity injection schemes, respectively. Those protocols were applied in clinical practices, and no significant differences were observed for the SUVmax of large/small lesions or the SUVmean of different healthy organs/tissues.ConclusionThese findings support that digital total-body PET/CT scanners can generate PET images with a high CNR and low-noise background, even with a short acquisition time and low administered activity. The proposed protocols for different administered activities were determined to be valid for clinical examination and can maximize the value of this imaging type.

Performance of a deep learning enhancement method applied to PET images acquired with a reduced acquisition time.

This study aims to evaluate the performance of a deep learning enhancement method in PET images reconstructed with a shorter acquisition time, and different reconstruction algorithms. The impact of the enhancement on clinical decisions was also assessed. Thirty-seven subjects underwent clinical whole-body [18F]FDG PET/CT exams with an acquisition time of 1.5 min per bed position. PET images were reconstructed with the OSEM algorithm using 66% counts (imitating 1 min/bed acquisition time) and 100% counts (1.5 min/bed). Images reconstructed from 66% counts were subsequently enhanced using the SubtlePET™ (SP) deep-learning-based software, (Subtle Medical, USA) - with two different software versions (SP1 and SP2). Additionally, images obtained with 66% counts were reconstructed with QClear™ (GE, USA) algorithm and enhanced with SP2. Volumes of interest (VOI) of the lesions and reference VOIs in the liver, brain, bladder, and mediastinum were drawn on OSEM images and copied on SP images. Quantitative SUVmax values per VOI of OSEM or QClear™ and AI-enhanced 'shortened' acquisitions were compared. Two hundred and fifty-two VOIs were identified (37 for each reference region, and 104 for the lesions) for OSEM, SP1, SP2, and QClear™ images AI-enhanced with SP2. SUVmax values on SP1 images were lower than standard OSEM, but on SP2 differences were smaller (average difference for SP1 11.6%, for SP2 -4.5%). For images reconstructed with QClear™, SUVmax values were higher (average +8.9%, median 6.1%, SD 18.9%). For small lesions with SUVmax values range 2.0 to 4.0 decrease of measured SUVmax was much less significant with SP2 (for liver average -6.5%, median -5.6% for lesions average -5.6%, median - 6.0, SD 5.2%) and showed the best correlation with original OSEM. While no artifacts and good general diagnostic confidence were found in AI-enhanced images, SP1, the images were not equal to the original OSEM - some lesions were hard to spot. SP2 produced images with almost the same quality as the original 1.5 min/bed OSEM reconstruction. The studied deep learning enhancement method can be used to accelerate PET acquisitions without compromising quantitative SUVmax values. AI-based algorithms can enhance the image quality of accelerated PET acquisitions, enabling the dose reduction to the patients and improving the cost-effectiveness of PET/CT imaging.

Image quality using synthetic brain MRI: an age-stratified study.

Synthetic magnetic resonance imaging (MRI) might replace the conventional MR sequences in brain evaluation to shorten scan time and obtain multiple quantitative parameters. To evaluate the image quality of multiple-delay-multiple-echo (MDME) sequence-derived synthetic brain MR images compared to conventional images by considering a multi-age sample. Image sets of conventional and synthetic MRI of 200 participants were included. On the basis of the presence of intracranial lesions, the participants were divided into a normal group and a pathological group. Two neuroradiologists compared the anonymous and unordered images. Image quality, artifacts, and diagnostic performance were analyzed. In the quantitative analysis, comparing with conventional images, MDME sequence-derived synthetic MRI demonstrated an equal/greater signal-to-noise ratio and contrast-to-noise ratio (CNR) in all age groups. Specifically, for participants aged ≤2 years, synthetic T2-fluid-attenuated inversion recovery imaging showed a significantly higher cerebellum gray/white matter CNR (P < 0.05). In the qualitative and artifact analyses, except for the superior sagittal sinus and cranial nerves, synthetic MRI showed good imaging quality (≥3 points) in all brain structures. On synthetic T1-weighted imaging, high signal intensity within the superior sagittal sinus was found in most of our participants (107/118, 90.7%). No difference was observed between synthetic and conventional MRI in diagnosing the lesions. MDME sequence-derived synthetic MRI showed similar image quality and diagnostic performance with a shorter acquisition time than conventional MRI. However, the high signal intensity within the superior sagittal sinus on synthetic T1-weighted images requires consideration.

Rapid identification of breast cancer subtypes using micro-FTIR and machine learning methods.

Breast cancer (BC) molecular subtypes diagnosis involves improving clinical uptake by Fourier transform infrared (FTIR) spectroscopic imaging, which is a non-destructive and powerful technique, enabling label free extraction of biochemical information towards prognostic stratification and evaluation of cell functionality. However, methods of measurements of samples demand a long time to achieve high quality images, making its clinical use impractical because of the data acquisition speed, poor signal to noise ratio, and deficiency of optimized computational framework procedures. To address those challenges, machine learning (ML) tools can facilitate obtaining an accurate classification of BC subtypes with high actionability and accuracy. Here, we propose a ML-algorithm-based method to distinguish computationally BC cell lines. The method is developed by coupling the K-neighbors classifier (KNN) with neighborhood components analysis (NCA), and hence, the NCA-KNN method enables to identify BC subtypes without increasing model size as well as adding additional computational parameters. By incorporating FTIR imaging data, we show that classification accuracy, specificity, and sensitivity improve, respectively, 97.5%, 96.3%, and 98.2%, even at very low co-added scans and short acquisition times. Moreover, a clear distinctive accuracy (up to 9 %) difference of our proposed method (NCA-KNN) was obtained in comparison with the second best supervised support vector machine model. Our results suggest a key diagnostic NCA-KNN method for BC subtypes classification that may translate to advancement of its consolidation in subtype-associated therapeutics.

Could Biparametric MRI Replace Multiparametric MRI in the Management of Prostate Cancer?

Prostate cancer (PCa) is a worldwide epidemiological problem, since it is one of the most prevalent types of neoplasia among men, and the third-leading cause of cancer-related deaths, after lung and colorectal tumors. Unfortunately, the early stages of PCa have a wide range of unspecific symptoms. For these reasons, early diagnosis and accurate evaluation of suspicious lesions are crucial. Multiparametric MRI (mpMRI) is currently the imaging modality of choice for diagnostic screening and local staging of PCa, but also has a leading role in guiding biopsies and in treatment biparametric MRI (bpMRI) could partially replace mpMRI due to its lack of adverse reactions caused by contrast agents, relatively lower costs, and shorter acquisition time. Further, 31 relevant articles regarding the advantages and disadvantages of the aforementioned imaging techniques were scanned. As a result, while bpMRI has comparable accuracy in detecting PCa, its roles in the other steps of PCa management are limited.

Online monitoring of dry powder mixing in a bin mixer

Dry powder mixing is a common process in the food industry. The aim of dry powder mixing is to improve the mixture quality within the optimum critical mixing time. Therefore, critical mixing time and mixture quality need to be monitored and quantified. An optical camera has advantages of high resolution, short image acquisition time and relatively large sampling area. An optical camera was used to online monitor the mixing process of the dairy-based powder and coffee powder of different sizes in a 5-L bin mixer. A new image analysis method including seven mixing indices and three dispersion indicators, has been developed. This method can provide precise results and identify different effects on mixing performance. This study confirms that the best mixing quality can be achieved when mixing particles of similar size. When the rotation speed is increased from 5 to 15 and 30 rpm, the critical mixing time is shortened. • Online monitoring of food powder mixing in a bin mixer by using optical technique. • A new method to quantify critical mixing time and mixture quality. • Both overall and local mixing change are crucial. • Seven mixing indices provide a comprehensive assessment of the mixing process. • Particle size and rotation speed significantly influence the mixing performance.