AI based segmentation of the prostate

Magnetic resonance imaging (MRI) provides increasingly reliable imaging of prostate cancer (PCa) and can improve the detection of lesions and the performance of targeted biopsies. In this regard, segmentation of the prostate in the MRI dataset is critical for several tasks, including the creation of three-dimensional models, e.g., for navigational purposes when planning biopsies or interventional therapies, for planning radiotherapy, for improved volume estimation to assess disease progression, and for automated detection of prostate zones and PCa. However, segmentation by hand is very time-consuming, making an automated machine-based solution desirable. Methods: For this project, a data set of 158 MRI examinations of the prostate was compiled, which meet the technical requirements of the PIRADS V2.1 standard. These included 102 patients with histologically confirmed prostate carcinoma and an image morphological finding of PIRADS 4 or higher. The examinations were then divided into a training data set and a test data set. Both datasets were manually segmented by two subject matter experts with several years of experience in uroradiological imaging, firstly annotating the anatomy and zonal divisions and secondly annotating the tumor regions. Furthermore, a deep learning model was developed and trained on the segmentation of anatomy and tumor region using the training dataset. Subsequently, the agreement of the segmentations of the experts among themselves and the agreement of the segmentations of the model with those of the experts were compared on the test data set. Results: The agreement between the segmentations of the two experts was highest for the central zone, followed by the peripheral zone and lowest for the tumor region. A similar picture was seen for the segmentations of the model. There was no significant difference in the agreement between the model and the respective experts 1 and 2. However, a worse agreement between the model to the experts compared to the interrater agreement between the experts could be observed. Conclusion: Although the deep learning model used for this Thesis for prostate anatomy segmentation and tumor region detection and segmentation could not quite reach the human expert standard, a perspective and great potential for further research and progress in this area of medical image analysis can still be seen. Automated segmentations and tumor detection may facilitate and accelerate clinical workflow and improve future diagnostics and therapies. In the context of further technical advances, a similar quality and safety as long-time trained human experts can be expected.Die Magnetresonanztomographie (MRT) ermöglicht eine zuverlässige Darstellung von Prostatakrebs (PCa) und kann die Erkennung von Läsionen und die Durchführung gezielter Biopsie verbessern. Die Segmentierung der Prostata im MRT Datensatz ist dabei für viele Aufgaben von entscheidender Bedeutung, u. a. für die Erstellung dreidimensionaler Modelle, z. B. zu Navigationszwecken bei der Planung von Biopsien oder interventionellen Therapien, für die Planung einer Strahlentherapie, für eine verbesserte Volumenschätzung zur Beurteilung des Krankheitsverlaufs und für die automatisierte Erkennung der Anatomie und von PCa. Eine Segmentierung von Hand ist jedoch zeitaufwändig, weshalb eine automatisierte maschinelle Lösung erstrebenswert ist. Methoden Es wurde ein Datensatz von insgesamt 158 MRT Untersuchungen der Prostata zusammengestellt, welche den technischen Anforderungen des PI-RADS V2.1 Standards entsprechen. Hierunter befanden sich 102 Patienten mit histologisch gesicherten Prostatakarzinomen und einem bildmoprhologischen Befund von PI-RADS 4 oder höher. Die Untersuchungen wurden daraufhin auf einen Trainingsdatensatz und einen Testdatensatz aufgeteilt. Beide Datensätze wurden händisch durch zwei Experten mit mehrjähriger Erfahrung in uroradiologischer Bildgebung segmentiert, wobei zum einen die zonale Anatomie und zum anderen die Tumorregionen annotiert wurden. Des Weiteren wurde ein Deep Learning Modell entwickelt und mit Hilfe des Trainingsdatensatzes auf die Segmentierung der Anatomie und der Tumorregion trainiert. Anschließend wurde am Testdatensatz die Übereinstimmung der Segmentierungen der Experten untereinander sowie die Übereinstimmung der Segmentierungen des Modells mit denen der Experten verglichen. Ergebnisse Die Übereinstimmung zwischen den Segmentierungen der beiden Experten war am höchsten für die zentrale Drüse, gefolgt von der peripheren Zone und am niedrigsten für die Tumorregion. Ein ähnliches Bild zeigte sich auch für die Segmentierungen desModells. Es bestand kein signifikanter Unterschied in der Übereinstimmung zwischen dem Modell und den jeweiligen Experten 1 und 2. Es konnte jedoch eine schlechtere Übereinstimmung zwischen dem Modell zu den Experten gegenüber der Interrater Übereinstimmung zwischen den Experten festgestellt werden. Schlussfolgerung Obgleich das verwendete Deep Learning Modells für die Segmentierung der Prostataanatomie sowie der Segmentierung der Tumorregion nicht ganz den menschlichen Expertenstandard erreichen konnte, lässt sich dennoch eine Perspektive und großes Potential für weitere Forschung und Fortschritte in diesem Bereich der medizinischen Bildanalyse erkennen. Automatisierte Segmentierungen und Tumordetektionen können den klinischen Arbeitsfluss erleichtern und beschleunigen sowie zukünftige Diagnostik und Therapien verbessern. Im Rahmen weiterer technischer Fortschritte ist eine ähnliche Qualität und Sicherheit wie langjährig antrainierte menschliche Experten erwartbar

Retrieval of the Vacuolar H+-ATPase from Phagosomes Revealed by Live Cell Imaging

The vacuolar H+-ATPase, or V-ATPase, is a highly-conserved multi-subunit enzyme that transports protons across membranes at the expense of ATP. The resulting proton gradient serves many essential functions, among them energizing transport of small molecules such as neurotransmitters, and acidifying organelles such as endosomes. The enzyme is not present in the plasma membrane from which a phagosome is formed, but is rapidly delivered by fusion with endosomes that already bear the V-ATPase in their membranes. Similarly, the enzyme is thought to be retrieved from phagosome membranes prior to exocytosis of indigestible material, although that process has not been directly visualized., we fed the cells yeast, large particles that maintain their shape during trafficking. To track pH changes, we conjugated the yeast with fluorescein isothiocyanate. Cells were labeled with VatM-GFP, a fluorescently-tagged transmembrane subunit of the V-ATPase, in parallel with stage-specific endosomal markers or in combination with mRFP-tagged cytoskeletal proteins.We find that the V-ATPase is commonly retrieved from the phagosome membrane by vesiculation shortly before exocytosis. However, if the cells are kept in confined spaces, a bulky phagosome may be exocytosed prematurely. In this event, a large V-ATPase-rich vacuole coated with actin typically separates from the acidic phagosome shortly before exocytosis. This vacuole is propelled by an actin tail and soon acquires the properties of an early endosome, revealing an unexpected mechanism for rapid recycling of the V-ATPase. Any V-ATPase that reaches the plasma membrane is also promptly retrieved.Thus, live cell microscopy has revealed both a usual route and alternative means of recycling the V-ATPase in the endocytic pathway

Curvature recognition and force generation in phagocytosis

Background: The uptake of particles by actin-powered invagination of the plasma membrane is common to protozoa and to phagocytes involved in the immune response of higher organisms. The question addressed here is how a phagocyte may use geometric cues to optimize force generation for the uptake of a particle. We survey mechanisms that enable a phagocyte to remodel actin organization in response to particles of complex shape. Results: Using particles that consist of two lobes separated by a neck, we found that Dictyostelium cells transmit signals concerning the curvature of a surface to the actin system underlying the plasma membrane. Force applied to a concave region can divide a particle in two, allowing engulfment of the portion first encountered. The phagosome membrane that is bent around the concave region is marked by a protein containing an inverse Bin-Amphiphysin-Rvs (I-BAR) domain in combination with an Src homology (SH3) domain, similar to mammalian insulin receptor tyrosine kinase substrate p53. Regulatory proteins enable the phagocyte to switch activities within seconds in response to particle shape. Ras, an inducer of actin polymerization, is activated along the cup surface. Coronin, which limits the lifetime of actin structures, is reversibly recruited to the cup, reflecting a program of actin depolymerization. The various forms of myosin-I are candidate motor proteins for force generation in particle uptake, whereas myosin-II is engaged only in retracting a phagocytic cup after a switch to particle release. Thus, the constriction of a phagocytic cup differs from the contraction of a cleavage furrow in mitosis. Conclusions: Phagocytes scan a particle surface for convex and concave regions. By modulating the spatiotemporal pattern of actin organization, they are capable of switching between different modes of interaction with a particle, either arresting at a concave region and applying force in an attempt to sever the particle there, or extending the cup along the particle surface to identify the very end of the object to be ingested. Our data illustrate the flexibility of regulatory mechanisms that are at the phagocyte's disposal in exploring an environment of irregular geometr

Feasibility of gadoxetate disodium enhanced 3D T1 MR cholangiography (MRC) with a specific inversion recovery prepulse for the assessment of the hepatobiliary system

Aim: To compare the potential of a gadoxetate disodium enhanced navigator-triggered 3D T1 magnetic-resonance cholangiography (MRC) sequence with a specific inversion recovery prepulse to T2-weighted MRCP for assessment of the hepatobiliary system. Materials and methods: 30 patients (12 male, 18 female) prospectively underwent conventional navigator-triggered 3D turbo spin-echo T2-weighted MRCP and 3D T1 MRC with a specific inversion pulse to minimise signal from the liver 30 minutes after administration of gadoxetate disodium on a 1.5 T MRI system. For qualitative evaluation, biliary duct depiction was assessed segmentally following a 5-point Likert scale. Visualisation of hilar structures as well as image quality was recorded. Additionally, the extrahepatic bile ducts were assessed quantitatively by calculation of signal-to-noise ratios (SNR). Results: The advantages of T1 3D MRC include reduced affection of image quality by bowel movement and robust depiction of the relative position of the extrahepatic bile ducts in relation to the portal vein and the duodenum compared to T2 MRCP. However, overall T1 3D MRC did not significantly (p > 0.05) improve the biliary duct depiction compared to T2 MRCP in all segments: Common bile duct 4.1 vs. 4.4, right hepatic duct 3.6 vs. 4.2, left hepatic duct 3.5 vs. 4.1. Image quality did not differ significantly (p > 0.05) between both sequences (3.6 vs. 3.5). SNR measurements for the hepatobiliary system did not differ significantly (p > 0.05) between navigator-triggered T1 3D MRC and T2 MRCP. Conclusions: This preliminary study demonstrates that T1 3D MRC of a specific inversion recovery pre-pulse has potential to complement T2 MRCP, especially for the evaluation of liver structures close to the hilum in the diagnostic work-up of the biliary system in patients receiving gadoxetate disodium

Highly resolved observations of trace gases in the lowermost stratosphere and upper troposphere from the Spurt project: an overview

During SPURT (Spurenstofftransport in der Tropopausenregion, trace gas transport in the tropopause region) we performed measurements of a wide range of trace gases with different lifetimes and sink/source characteristics in the northern hemispheric upper troposphere (UT) and lowermost stratosphere (LMS). A large number of in-situ instruments were deployed on board a Learjet 35A, flying at altitudes up to 13.7 km, at times reaching to nearly 380 K potential temperature. Eight measurement campaigns (consisting of a total of 36 flights), distributed over all seasons and typically covering latitudes between 35° N and 75° N in the European longitude sector (10° W–20° E), were performed. Here we present an overview of the project, describing the instrumentation, the encountered meteorological situations during the campaigns and the data set available from SPURT. Measurements were obtained for N2O, CH4, CO, CO2, CFC12, H2, SF6, NO, NOy, O3 and H2O. We illustrate the strength of this new data set by showing mean distributions of the mixing ratios of selected trace gases, using a potential temperature – equivalent latitude coordinate system. The observations reveal that the LMS is most stratospheric in character during spring, with the highest mixing ratios of O3 and NOy and the lowest mixing ratios of N2O and SF6. The lowest mixing ratios of NOy and O3 are observed during autumn, together with the highest mixing ratios of N2O and SF6 indicating a strong tropospheric influence. For H2O, however, the maximum concentrations in the LMS are found during summer, suggesting unique (temperature- and convection-controlled) conditions for this molecule during transport across the tropopause. The SPURT data set is presently the most accurate and complete data set for many trace species in the LMS, and its main value is the simultaneous measurement of a suite of trace gases having different lifetimes and physical-chemical histories. It is thus very well suited for studies of atmospheric transport, for model validation, and for investigations of seasonal changes in the UT/LMS, as demonstrated in accompanying and elsewhere published studies

Highly resolved observations of trace gases in the lowermost stratosphere and upper troposphere from the Spurt project: an overview

During SPURT (Spurenstofftransport in der Tropopausenregion, trace gas transport in the tropopause region) we performed measurements of a wide range of trace gases with different lifetimes and sink/source characteristics in the northern hemispheric upper troposphere (UT) and lowermost stratosphere (LMS). A large number of in-situ instruments were deployed on board a Learjet 35A, flying at altitudes up to 13.7 km, at times reaching to nearly 380 K potential temperature. Eight measurement campaigns (consisting of a total of 36 flights), distributed over all seasons and typically covering latitudes between 35° N and 75° N in the European longitude sector (10° W–20° E), were performed. Here we present an overview of the project, describing the instrumentation, the encountered meteorological situations during the campaigns and the data set available from SPURT. Measurements were obtained for N2O, CH4, CO, CO2, CFC12, H2, SF6, NO, NOy, O3 and H2O. We illustrate the strength of this new data set by showing mean distributions of the mixing ratios of selected trace gases, using a potential temperature – equivalent latitude coordinate system. The observations reveal that the LMS is most stratospheric in character during spring, with the highest mixing ratios of O3 and NOy and the lowest mixing ratios of N2O and SF6. The lowest mixing ratios of NOy and O3 are observed during autumn, together with the highest mixing ratios of N2O and SF6 indicating a strong tropospheric influence. For H2O, however, the maximum concentrations in the LMS are found during summer, suggesting unique (temperature- and convection-controlled) conditions for this molecule during transport across the tropopause. The SPURT data set is presently the most accurate and complete data set for many trace species in the LMS, and its main value is the simultaneous measurement of a suite of trace gases having different lifetimes and physical-chemical histories. It is thus very well suited for studies of atmospheric transport, for model validation, and for investigations of seasonal changes in the UT/LMS, as demonstrated in accompanying and elsewhere published studies

A large Hilbert space QRPA and RQRPA calculation of neutrinoless double beta decay

A large Hilbert space is used for the calculation of the nuclear matrix elements governing the light neutrino mass mediated mode of neutrinoless double beta decay of Ge76, Mo100, Cd116, Te128 and Xe136 within the proton-neutron quasiparticle random phase approximation (pn-QRPA) and the renormalized QRPA with proton-neutron pairing (full-RQRPA) methods. We have found that the nuclear matrix elements obtained with the standard pn-QRPA for several nuclear transitions are extremely sensitive to the renormalization of the particle-particle component of the residual interaction of the nuclear hamiltonian. Therefore the standard pn-QRPA does not guarantee the necessary accuracy to allow us to extract a reliable limit on the effective neutrino mass. This behaviour, already known from the calculation of the two-neutrino double beta decay matrix elements, manifests itself in the neutrinoless double-beta decay but only if a large model space is used. The full-RQRPA, which takes into account proton-neutron pairing and considers the Pauli principle in an approximate way, offers a stable solution in the physically acceptable region of the particle-particle strength. In this way more accurate values on the effective neutrino mass have been deduced from the experimental lower limits of the half-lifes of neutrinoless double beta decay.Comment: 19 pages, RevTex, 1 Postscript figur

Effect of volcanic dykes on coastal groundwater flow and saltwater intrusion : a field-scale multiphysics approach and parameter evaluation

Acknowledgments This research was primarily based on research grant‐aided by the Irish Department of Communications, Energy and Natural Resources under the National Geoscience Programme 2007–2013. It also benefited from complementary funding from the Scottish Alliance for Geoscience, Environment and Society (SAGES). We acknowledge the contribution in data acquisition of the MSc students in Environmental Engineering at Queen's University Belfast, the landowner for access to the inland fields and the Department of Geography, Archaeology and Paleoecology at QUB for provision of the tidal model of Belfast Lough. The data used are listed in the references, tables, and figures and are available from the corresponding author upon demand. We acknowledge the constructive comments by the Associate Editor and three reviewers, which helped in improving the final manuscript.Peer reviewedPublisher PD

MEMACU PEMBENTUKAN UMBI MIKRO TANAMAN KENTANG YANG DITANAM SECARA IN VITRO PADA SUHU TINGGI DENGAN APLIKASI ANCYMIDOL, PACLOBUTRAZOL, CCC, DAN COUMARIN

The overall goal of this experiment was to establish a technology for growing potato at the low elevation. Producing potato tubers at high temperatures is the first step to reach the goal, as potato crops are well-known to be temperate crops. At high temperature, potato crops produce more gibberrelic acid (GA), which inhibits potato tuber formation. Several retardants have been reported to inhibit GA biosynthesis or halt GA activity. The specific goal of this experiment was to find the effective concentration of four retardan in promoting tuber formation at 30/25 oC. Four retardants (Ancymidol, Paclobutrazol, CCC, and Coumarin) were individually applied to potato 6-week old explants grown in vitro on modified MS medium at different regimes: Ancymidol (0, 1, 2, 3, and 4 ppm), Paclobutrazol (0, 1000, 2000, 3000, and 4000 ppm), CCC (0, 300, 600, 900, 1200 ppm), and Coumarin (0, 25, 50, 100, 200 ppm). The explants were incubated under 16 days/8 night cycle for 6 weeks. Retardants were applied when the explants were 6 weeks old, followed by total dark incubation for the next 6 weeks. The results showed that three important things. First, the application of retardant promoted tuber formation in potato crops grown in vitro at high temperature (30//25 oC). In contrast, no tuber was produced without the application of any retardant. Secondly, each retardant had different effective concentration (4 ppm for Ancymidol, 4000 ppm for Paclobutrazol, 1200 ppm for CCC, and 50 ppm for Coumarin. Thirdly, the number of tuber steadily increased with increasing retardant concentration, except for Coumarin which reached its peak at 50 ppm. Other tuber characteristics were discussed in more detail the text. Since the application of retardant may cause inhibition of crop growth, it is recommended to carry out further researches to elucidate when and how those retardants should be applied to the crop when the crops are grown in the field

Dataset of prostate MRI annotated for anatomical zones and cancer

In the present work, we present a publicly available, expert-segmented representative dataset of 158 3.0 Tesla biparametric MRIs [1]. There is an increasing number of studies investigating prostate and prostate carcinoma segmentation using deep learning (DL) with 3D architectures [2], [3], [4], [5], [6], [7]. The development of robust and data-driven DL models for prostate segmentation and assessment is currently limited by the availability of openly available expert-annotated datasets [8], [9], [10]. The dataset contains 3.0 Tesla MRI images of the prostate of patients with suspected prostate cancer. Patients over 50 years of age who had a 3.0 Tesla MRI scan of the prostate that met PI-RADS version 2.1 technical standards were included. All patients received a subsequent biopsy or surgery so that the MRI diagnosis could be verified/matched with the histopathologic diagnosis. For patients who had undergone multiple MRIs, the last MRI, which was less than six months before biopsy/surgery, was included. All patients were examined at a German university hospital (Charité Universitätsmedizin Berlin) between 02/2016 and 01/2020. All MRI were acquired with two 3.0 Tesla MRI scanners (Siemens VIDA and Skyra, Siemens Healthineers, Erlangen, Germany). Axial T2W sequences and axial diffusion-weighted sequences (DWI) with apparent diffusion coefficient maps (ADC) were included in the data set. T2W sequences and ADC maps were annotated by two board-certified radiologists with 6 and 8 years of experience, respectively. For T2W sequences, the central gland (central zone and transitional zone) and peripheral zone were segmented. If areas of suspected prostate cancer (PIRADS score of ≥ 4) were identified on examination, they were segmented in both the T2W sequences and ADC maps. Because restricted diffusion is best seen in DWI images with high b-values, only these images were selected and all images with low b-values were discarded. Data were then anonymized and converted to NIfTI (Neuroimaging Informatics Technology Initiative) format