investigating-cardiac-metabolism-isolated-perfused-mouse-heart-with

Investigating Cardiac Metabolism in the Isolated Perfused Mouse Heart with Hyperpolarized [1-13C]Pyruvate and 13C/31P NMR Spectroscopy

Metabolism is the basis of important processes in cellular life. Characterizing how metabolic networks function in living tissues provides crucial ...

Hebrew University of Jerusalem

Radiological longitudinal follow-up of tumors in CT scans is essential for disease assessment and liver tumor therapy. Currently, most tumor size measurements follow the RECIST guidelines, which can be off by as much as 50%. True volumetric measurements are more accurate but require manual delineation, which is time-consuming and user-dependent. We present a convolutional neural networks (CNN) based method for robust automatic liver tumor delineation in longitudinal CT studies that uses both global and patient specific CNNs trained on a small database of delineated images. The inputs are the baseline scan and the tumor delineation, a follow-up scan, and a liver tumor global CNN voxel classifier built from radiologist-validated liver tumor delineations. The outputs are the tumor delineations in the follow-up CT scan. The baseline scan tumor delineation serves as a high-quality prior for the tumor characterization in the follow-up scans. It is used to evaluate the global CNN performance on the new case and to reliably predict failures of the global CNN on the follow-up scan. High-scoring cases are segmented with a global CNN; low-scoring cases, which are predicted to be failures of the global CNN, are segmented with a patient-specific CNN built from the baseline scan. Our experimental results on 222 tumors from 31 patients yield an average overlap error of 17% (std = 11.2) and surface distance of 2.1 mm (std = 1.8), far better than stand-alone segmentation. Importantly, the robustness of our method improved from 67% for stand-alone global CNN segmentation to 100%. Unlike other medical imaging deep learning approaches, which require large annotated training datasets, our method exploits the follow-up framework to yield accurate tumor tracking and failure detection and correction with a small training dataset. Graphical abstract Flow diagram of the proposed method. In the offline mode (orange), a global CNN is trained as a voxel classifier to segment liver tumor as in [31]. The online mode (blue) is used for each new case. The input is baseline scan with delineation and the follow-up CT scan to be segmented. The main novelty is the ability to predict failures by trying the system on the baseline scan and the ability to correct them using the patient-specific CNN.

Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies.

Precision-cut liver slices (PCLS) are widely used in liver research as they provide a liver model with all liver cell types in their natural architecture. The purpose of this study was to demonstrate the use of PCLS for hyperpolarized metabolic investigation in a mouse model, for potential future application in liver biopsy cores. Fresh normal liver was harvested from six mice. 500 μm PCLS were prepared and placed in a 10 mm NMR tube in an NMR spectrometer and perfused continuously.  P spectra were acquired to evaluate the presence of adenosine triphosphate (ATP) and validate viability in all samples. Hyperpolarized [1- C]pyruvate was flushed into the NMR tube in the spectrometer. Consecutive  C NMR spectra were acquired immediately after the injection using both non-selective (five injections, two livers) and selective RF excitation (six injections, three livers). The  P spectra showed the characteristic signals of ATP, confirming the viability of the PCLS for more than 2.5 h in the spectrometer. After each of the [1- C]pyruvate injections, both [1- C]lactate and [1- C]alanine signals were detected. Selective RF excitation aimed at both [1- C]lactate and [1- C]alanine enabled better visualization and quantification of the metabolic activity. Using this acquisition approach only the newly formed metabolites are observed upon excitation, and their intensities relative to those of hyperpolarized pyruvate enable quantification of metabolite production rates. This rate of lactate and alanine production appeared to be constant throughout the measurement time, with alanine production about 2.3 times higher than lactate. In summary, the viability of PCLS in an NMR spectrometer was demonstrated and hyperpolarized [1- C]pyruvate metabolism was recorded. This study opens up the possibility of evaluating alanine aminotransferase (ALT) and lactate dehydrogenase (LDH) activities in human liver biopsies, while preserving the tissue architecture and viability. In healthy, well-perfused liver slices the ratio of ALT to LDH activity is about 2.3.

Real-time ALT and LDH activities determined in viable precision-cut mouse liver slices using hyperpolarized [1- C]pyruvate-Implications for studies on biopsied liver tissues.

[1-C]pyruvate, the most widely used compound in dissolution-dynamic nuclear polarization (dDNP) magnetic resonance (MR), enables the visualization of lactate dehydrogenase (LDH) activity. This activity had been demonstrated in a wide variety of cancer models, ranging from cultured cells, to xenograft models, to human tumors in situ. Here we quantified the LDH activity in precision cut tumor slices (PCTS) of breast cancer xenografts. The Michigan Cancer Foundation-7 (MCF7) cell-line was chosen as a model for the luminal breast cancer type which is hormone responsive and is highly prevalent. The LDH activity, which was manifested as [1-C]lactate production in the tumor slices, ranged between 3.8 and 6.1 nmole/nmole adenosine tri-phosphate (ATP) in 1 min (average 4.6 ± 1.0) on three different experimental set-ups consisting of arrested vs. continuous perfusion and non-selective and selective RF pulsation schemes and combinations thereof. This rate was converted to an expected LDH activity in a mass ranging between 3.3 and 5.2 µmole/g in 1 min, using the ATP level of these tumors. This indicated the likely utility of this approach in clinical dDNP of the human breast and may be useful as guidance for treatment response assessment in a large number of tumor types and therapies ex vivo.

In-cell determination of Lactate Dehydrogenase Activity in a Luminal Breast Cancer Model ⁻  Investigation of Excised Xenograft Tumor Slices Using dDNP Hyperpolarized [1-C]pyruvate.

Investigation of hyperpolarized substrate metabolism has been showing utility in real-time determination of in-cell and in vivo enzymatic activities. Intracellular reaction rates may vary during the course of a measurement, even on the very short time scales of visibility on hyperpolarized MR, due to many factors such as the availability of the substrate and co-factors in the intracellular space. Despite this potential variation, the kinetic analysis of hyperpolarized signals typically assumes that the same rate constant (and in many cases, the same rate) applies throughout the course of the reaction as observed via the build-up and decay of the hyperpolarized signals. We demonstrate here an acquisition approach that can null the need for such an assumption and enable the detection of instantaneous changes in the rate of the reaction during an ex vivo hyperpolarized investigation, (i.e. in the course of the decay of one hyperpolarized substrate dose administered to a viable tissue sample ex vivo). This approach utilizes hyperpolarized product selective saturating-excitation pulses. Similar pulses have been previously utilized in vivo for spectroscopic imaging. However, we show here favorable consequences to kinetic rate determinations in the preparations used. We implement this acquisition strategy for studies on perfused tissue slices and develop a theory that explains why this particular approach enables the determination of changes in enzymatic rates that are monitored via the chemical conversions of hyperpolarized substrates. Real-time changes in intracellular reaction rates are demonstrated in perfused brain, liver, and xenograft breast cancer tissue slices and provide another potential differentiation parameter for tissue characterization.

Hyperpolarized product selective saturating-excitations for determination of changes in metabolic reaction rates in real-time.

Ischemic stroke is a leading cause for neurologic disability worldwide, for which reperfusion is the only available treatment. Neuroimaging in stroke guides treatment, and therefore determines the clinical outcome. However, there are currently no imaging biomarkers for the status of the ischemic brain tissue. Such biomarkers could potentially be useful for guiding treatment in patients presenting with ischemic stroke. Hyperpolarized C MR of [1-C]pyruvate is a clinically translatable method used to characterize tissue metabolism non-invasively in a relevant timescale. The aim of this study was to utilize hyperpolarized [1-C]pyruvate to investigate the metabolic consequences of an ischemic insult immediately during reperfusion and upon recovery of the brain tissue. The rates of lactate dehydrogenase (LDH) and pyruvate dehydrogenase (PDH) were quantified by monitoring the rates of [1-C]lactate and [C]bicarbonate production from hyperpolarized [1-C]pyruvate. P NMR of the perfused brain slices showed that this system is suitable for studying ischemia and recovery following reperfusion. This was indicated by the levels of the high-energy phosphates (tissue viability) and the chemical shift of the inorganic phosphate signal (tissue pH). Acidification, which was observed during the ischemic insult, has returned to baseline level following reperfusion. The LDH/PDH activity ratio increased following ischemia, from 47.0 ± 12.7 in the control group ( = 6) to 217.4 ± 121.3 in the ischemia-reperfusion group ( = 6). Following the recovery period ( 1.5 h), this value had returned to its pre-ischemia (baseline) level, suggesting the LDH/PDH enzyme activity ratio may be used as a potential indicator for the status of the ischemic and recovering brain.

LDH and PDH Activities in the Ischemic Brain and the Effect of Reperfusion-An Ex Vivo MR Study in Rat Brain Slices Using Hyperpolarized [1-C]Pyruvate.

To assess the potential role of low monoenergetic images in the evaluation of acute appendicitis.

Dual energy CT in acute appendicitis: value of low mono-energy.

To determine whether contrast enhanced DECT low monoenergetic can improve diagnostic conspicuity of inflamed kidney foci in acute pyelonephritis compared to conventional images.

Low monoenergetic DECT detection of pyelonephritis extent.

To determine whether specific ultrasonographic features can predict failure of conservative treatment of acute appendicitis.

Ultrasonographic features can predict outcome of conservative management of acute appendicitis in children.

3-aminopropylphosphonate (3-APP) is known for its use as an exogenous indicator of extracellular volume and pH in phosphorus-31 nuclear magnetic resonance ( P NMR) studies. We used 3-APP for estimating the extracellular volume in NMR studies of several ex vivo preparations including retrograde perfused mouse heart (n = 4), mouse liver slices (n = 2), xenograft breast cancer tumors (n = 7, MCF7), and rat brain slices (n = 4). In the former three preparations, the 3-APP signal was stable in lineshape and intensity for hours and the chemical shift of the signal in the presence of the biological sample was the same as in the perfusion medium without the biological sample. However, in studies of brain slices, the 3-APP signal appeared split into two, with an upfield component (0.7 ± 0.1 ppm to the left) increasing with time and showing a wider linewidth (66.7 ± 12.6 vs. 39.1 ± 7.6 Hz, the latter is of the perfusion medium signal). This finding suggests that 3-APP inadvertently accumulated in brain slices, most likely as a membrane bound form. This observation limits the use of 3-APP as an inert biochemical indicator in brain preparations and should be taken into account when using 3-APP in vivo.

Accumulation of 3-aminopropylphosphonate in the ex vivo brain observed by phosphorus-31 nuclear magnetic resonance.

Biodegradable polymer clips as multidimensional soft tissue biopsy markers were developed with better biocompatibility and imaging features. Unlike the commercially available metallic biopsy markers, the developed polymer clips are temporary implants with similar efficacies as metal markers in imaging and detection and get absorbed within the body with time. Herein, we evaluate the degradation rate of three resorbable polymer-based marker compounds in an in vivo murine model. Three polymers, abbreviated as Polymer A (PLGA poly(lactic--glycolic acid)50:50), Polymer B (PLGA (poly(lactic--glycolic acid)) 75:25), and Polymer C (polycaprolactone (PCL)), mixed with 20% lipiodol and 0.2% iron oxide and a control polymer were implanted into nine mice, followed by CT and MRI imaging. Images were evaluated for conspicuity. Specimens were examined for tissue analysis of iodine and iron contents. Significant differences in polymer resorption and visualization on CT were noted, particularly at 8 weeks ( < 0.027). Polymers A, B, and C were visible by CT at 4, 6, and 8 weeks, respectively. All marker locations were detected on MRI (T1 and SWI) after 24 weeks, with tattooing of the surrounding soft tissue by iron deposits. CT and MR visible polymer markers can be constructed to possess variable resorption, with stability ranging between 4 and 14 weeks post placement, making this approach suitable for distinct clinical scenarios with varying time points.

Characterization and Evaluation of Injectable Biodegradable Polymer Multimodality Radiologic Markers in an In Vivo Murine Model.

The soft texture of the pancreas parenchyma may influence the incidence of pancreatic leakage after pancreaticoduodenectomy (PD). One possible method to assess pancreatic texture and atrophy, is via computed tomography (CT) scan of the abdomen. The purpose of our study was to evaluate the relation between the preoperative CT scan and the incidence of pancreatic fistula after PD.

The effect of atrophied pancreas as shown in the preoperative imaging on the leakage rate after pancreaticoduodenectomy.

Early recognition of bowel ischemia is critical in patients suffering from acute adhesive small bowel obstruction (ASBO). Recent studies attempted to propose a score combining clinical and radiological factors to predict the risk of bowel ischemia in patients with ASBO. This study aimed to compare and validate the existing clinical scores with a cohort of surgical patients.

Existing Scores Fail to Predict Bowel Ischemia in Patients With Adhesive Small Bowel Obstruction.

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://medicaldecathlon.com/. In addition, both data and online evaluation are accessible via https://competitions.codalab.org/competitions/17094.

Article	Year
Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies. Medical & biological engineering & computing\| PubMed ID: 29524116	2018
Real-time ALT and LDH activities determined in viable precision-cut mouse liver slices using hyperpolarized [1- C]pyruvate-Implications for studies on biopsied liver tissues. NMR in biomedicine\| PubMed ID: 30575159	2019
In-cell determination of Lactate Dehydrogenase Activity in a Luminal Breast Cancer Model ⁻ Investigation of Excised Xenograft Tumor Slices Using dDNP Hyperpolarized [1-C]pyruvate. Sensors (Basel, Switzerland)\| PubMed ID: 31060334	2019
Hyperpolarized product selective saturating-excitations for determination of changes in metabolic reaction rates in real-time. NMR in biomedicine\| PubMed ID: 31793111	2020
LDH and PDH Activities in the Ischemic Brain and the Effect of Reperfusion-An Ex Vivo MR Study in Rat Brain Slices Using Hyperpolarized [1-C]Pyruvate. Metabolites\| PubMed ID: 33808434	2021
Dual energy CT in acute appendicitis: value of low mono-energy. Clinical imaging\| PubMed ID: 33992882	2021
Low monoenergetic DECT detection of pyelonephritis extent. European journal of radiology\| PubMed ID: 34339954	2021
Ultrasonographic features can predict outcome of conservative management of acute appendicitis in children. Emergency radiology\| PubMed ID: 34533666	2022
Accumulation of 3-aminopropylphosphonate in the ex vivo brain observed by phosphorus-31 nuclear magnetic resonance. NMR in biomedicine\| PubMed ID: 35229366	2022
Characterization and Evaluation of Injectable Biodegradable Polymer Multimodality Radiologic Markers in an In Vivo Murine Model. Biomacromolecules\| PubMed ID: 35357807	2022
The effect of atrophied pancreas as shown in the preoperative imaging on the leakage rate after pancreaticoduodenectomy. Annals of hepato-biliary-pancreatic surgery\| PubMed ID: 35370142	2022
Existing Scores Fail to Predict Bowel Ischemia in Patients With Adhesive Small Bowel Obstruction. The Journal of surgical research\| PubMed ID: 36434837	2023
The Liver Tumor Segmentation Benchmark (LiTS). Medical image analysis\| PubMed ID: 36481607	2023

Naama Lev-Cohain

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