Quantitative and qualitative evaluation of sequential PET/MRI using a newly developed mobile PET system for brain imaging

[Purpose]To evaluate the clinical feasibility of a newly developed mobile PET system with MR-compatibility (flexible PET; fxPET), compared with conventional PET (cPET)/CT for brain imaging.[Methods]Twenty-one patients underwent cPET/CT with subsequent fxPET/MRI using 18F-FDG. As qualitative evaluation, we visually rated image quality of MR and PET images using a four-point scoring system. We evaluated overall image quality for MR, while we evaluated overall image quality, sharpness and lesion contrast. As quantitative evaluation, we compared registration accuracy between two modalities [(fxPET and MRI) and (cPET and CT)] measuring spatial coordinates. We also examined the accuracy of regional 18F-FDG uptake.[Results]All acquired images were of diagnostic quality and the number of detected lesions did not differ significantly between fxPET/MR and cPET/CT. Mean misregistration was significantly larger with fxPET/MRI than with cPET/CT. SUVmax and SUVmean for fxPET and cPET showed high correlations in the lesions (R = 0.84, 0.79; P < 0.001, P = 0.002, respectively). In normal structures, we also showed high correlations of SUVmax (R = 0.85, 0.87; P < 0.001, P < 0.001, respectively) and SUVmean (R = 0.83, 0.87; P < 0.001, P < 0.001, respectively) in bilateral caudate nuclei and a moderate correlation of SUVmax (R = 0.65) and SUVmean (R = 0.63) in vermis.[Conclusions]The fxPET/MRI system showed image quality within the diagnostic range, registration accuracy below 3 mm and regional 18F-FDG uptake highly correlated with that of cPET/CT

Evaluation of three methods for delineation and attenuation estimation of the sinus region in MR-based attenuation correction for brain PET-MR imaging

Background Attenuation correction is crucial in quantitative positron emission tomography-magnetic resonance (PET-MRI) imaging. We evaluated three methods to improve the segmentation and modelling of the attenuation coefficients in the nasal sinus region. Two methods (cuboid and template method) included a MRI-CT conversion model for assigning the attenuation coefficients in the nasal sinus region, whereas one used fixed attenuation coefficient assignment (bulk method). Methods The study population consisted of data of 10 subjects which had undergone PET-CT and PET-MRI. PET images were reconstructed with and without time-of-flight (TOF) using CT-based attenuation correction (CTAC) as reference. Comparison was done visually, using DICE coefficients, correlation, analyzing attenuation coefficients, and quantitative analysis of PET and bias atlas images. Results The median DICE coefficients were 0.824, 0.853, 0.849 for the bulk, cuboid and template method, respectively. The median attenuation coefficients were 0.0841 cm-1, 0.0876 cm-1, 0.0861 cm-1 and 0.0852 cm-1, for CTAC, bulk, cuboid and template method, respectively. The cuboid and template methods showed error of less than 2.5% in attenuation coefficients. An increased correlation to CTAC was shown with the cuboid and template methods. In the regional analysis, improvement in at least 49% and 80% of VOI was seen with non-TOF and TOF imaging. All methods showed errors less than 2.5% in non-TOF and less than 2% in TOF reconstructions. Conclusions We evaluated two proof-of-concept methods for improving quantitative accuracy in PET/MRI imaging and showed that bias can be further reduced by inclusion of TOF. Largest improvements were seen in the regions of olfactory bulb, Heschl's gyri, lingual gyrus and cerebellar vermis. However, the overall effect of inclusion of the sinus region as separate class in MRAC to PET quantification in the brain was considered modest.</p

Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network

Objective: We demonstrate the feasibility of direct generation of attenuation and scatter-corrected images from uncorrected images (PET-nonASC) using deep residual networks in whole-body 18F-FDG PET imaging. Methods: Two- and three-dimensional deep residual networks using 2D successive slices (DL-2DS), 3D slices (DL-3DS) and 3D patches (DL-3DP) as input were constructed to perform joint attenuation and scatter correction on uncorrected whole-body images in an end-to-end fashion. We included 1150 clinical whole-body 18F-FDG PET/CT studies, among which 900, 100 and 150 patients were randomly partitioned into training, validation and independent validation sets, respectively. The images generated by the proposed approach were assessed using various evaluation metrics, including the root-mean-squared-error (RMSE) and absolute relative error (ARE ) using CT-based attenuation and scatter-corrected (CTAC) PET images as reference. PET image quantification variability was also assessed through voxel-wise standardized uptake value (SUV) bias calculation in different regions of the body (head, neck, chest, liver-lung, abdomen and pelvis). Results: Our proposed attenuation and scatter correction (Deep-JASC) algorithm provided good image quality, comparable with those produced by CTAC. Across the 150 patients of the independent external validation set, the voxel-wise REs () were � 1.72 ± 4.22, 3.75 ± 6.91 and � 3.08 ± 5.64 for DL-2DS, DL-3DS and DL-3DP, respectively. Overall, the DL-2DS approach led to superior performance compared with the other two 3D approaches. The brain and neck regions had the highest and lowest RMSE values between Deep-JASC and CTAC images, respectively. However, the largest ARE was observed in the chest (15.16 ± 3.96) and liver/lung (11.18 ± 3.23) regions for DL-2DS. DL-3DS and DL-3DP performed slightly better in the chest region, leading to AREs of 11.16 ± 3.42 and 11.69 ± 2.71, respectively (p value &lt; 0.05). The joint histogram analysis resulted in correlation coefficients of 0.985, 0.980 and 0.981 for DL-2DS, DL-3DS and DL-3DP approaches, respectively. Conclusion: This work demonstrated the feasibility of direct attenuation and scatter correction of whole-body 18F-FDG PET images using emission-only data via a deep residual network. The proposed approach achieved accurate attenuation and scatter correction without the need for anatomical images, such as CT and MRI. The technique is applicable in a clinical setting on standalone PET or PET/MRI systems. Nevertheless, Deep-JASC showing promising quantitative accuracy, vulnerability to noise was observed, leading to pseudo hot/cold spots and/or poor organ boundary definition in the resulting PET images. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature

A review on methods to estimate a CT from MRI data in the context of MRI-alone RT

Background: In recent years, Radiation Therapy (RT) has undergone many developments and provided progress in the field of cancer treatment. However, dose optimisation each treatment session puts the patient at risk of successive X-Ray exposure from Computed Tomography CT scans since this imaging modality is the reference for dose planning. Add to this difficulties related to contour propagation. Thus, approaches are focusing on the use of MRI as the only modality in RT. In this paper, we review methods for creating pseudo-CT images from MRI data for MRI-alone RT. Each class of methods is explained and underlying works are presented in detail with performance results. We discuss the advantages and limitations of each class. Methods: We classified recent works in deriving a pseudo-CT from MR images into four classes: segmentation-based, intensity-based, atlas-based and hybrid methods and the classification was based on considering the general technique applied. Results: Most research focused on the brain and the pelvic regions. The mean absolute error ranged from 80 to 137 HU and from 36.4 to 74 HU for the brain and pelvis, respectively. In addition, an interest in the Dixon MR sequence is increasing since it has the advantage of producing multiple contrast images with a single acquisition. Conclusion: Radiation therapy is emerging towards the generalisation of MRI-only RT thanks to the advances in techniques for generation of pseudo-CT images and the development of specialised MR sequences favouring bone visualisation. However, a benchmark needs to be established to set in common performance metrics to assess the quality of the generated pseudo-CT and judge on the efficiency of a certain method

Quantitative analysis of MRI-guided attenuation correction techniques in time-of-flight brain PET/MRI.

In quantitative PET/MR imaging, attenuation correction (AC) of PET data is markedly challenged by the need of deriving accurate attenuation maps from MR images. A number of strategies have been developed for MRI-guided attenuation correction with different degrees of success. In this work, we compare the quantitative performance of three generic AC methods, including standard 3-class MR segmentation-based, advanced atlas-registration-based and emission-based approaches in the context of brain time-of-flight (TOF) PET/MRI

Exploring novel ways to improve the MRI-based image segmentation in the head region

Accurate electron density information is extremely important in positron emission tomography (PET) attenuation correction (AC) and radiotherapy (RT) treatment planning (RTP), especially in the head region, as many interesting brain regions are located near the skull. Achieving good electron density information for bone is not trivial when magnetic resonance imaging (MRI) is used as a source for the anatomical structures of the head, since many MRI sequences show bone in a similar fashion as air. Various atlas-based, emission-based, and segmentation-based methods have been explored to address this problem. In this PhD project, a pipeline for MRI-based substitute CT (sCT) creation is developed and novel ways are developed to further improve the quality of bone delineation in the head region. First, a robust sCT pipeline is developed and validated. This allows modular improvements of the various aspects of head sCT in later publications. The MRI image is segmented into different tissue classes and the final sCT image is constructed from these. The sCT images had good image quality with small non-systematic error. The time-of-flight (TOF) information improves the accuracy of PET reconstruction. The effect of TOF with different AC maps is evaluated to substantiate the need for accurate AC maps for a TOF capable system. The evaluation is performed on both subject and brain region level. While TOF information is helpful, it cannot negate the effect of the AC map quality. The sinus region is problematic in MRI-based sCT creation, as it is easily segmented as bone. Two new methods for addressing AC in the sinus region are presented. One method tries to find the cuboid that covers the largest area of air tissue incorrectly assigned as bone and then correct the incorrect attenuation coefficient. Another method uses the sinus covering cuboid in the normalized space, from which it is converted back to each subject’s individual space, after which the attenuation coefficients are calculated. Both methods improve the alignment of sCT and CT images. Finally, the possibilities of improving the quality of the bone segmentation by utilizing a random forest (RF) machine learning process is explored. The RF model is used to estimate the bone likelihood. The likelihood is then used to enhance the bone segmentation and to model the attenuation coefficient. The machine learning model improves the bone segmentation and reduces the error between sCT and CT images.Tutkimus uusien pään alueen MRI-kuvantamiseen pohjautuvien kuvasegmentaatiomenetelmien kehittämisestä. Tarkka elektronitiheystieto on hyvin tärkeää PET-kuvantamisen vaimenemiskorjauksessa sekä sädehoidon suunnittelussa erityisesti pään alueella, sillä useat kiinnostavat aivoalueet ovat kallon lähellä. Hyvän elektronitiheystiedon laskeminen luulle ei ole yksinkertaista MRI-kuvantamisen pohjalta, sillä useat MRI-sekvenssit näyttävät luut samoin kuin ilman. Useita atlas-, emissio- ja segmentointipohjaisia metodeja on tutkittu tämän ongelman ratkaisemiseksi. Tässä työssä MRI-pohjainen luotiin menetelmä MRI-pohjaisten vaihtoehto-TT-kuvien (sCT) laskemiseksi, sekä kehitetään uusia tapoja parantaa luun MRI-pohjaista erottelukykyä pään alueella. Ensin kehitettiin ja validoitiin sCT-menetelmä. Tämä mahdollisti modulaaristen parannusten lisäämiseen sCT-menetelmään tutkimuksen myöhemmissä vaiheissa. MRI-kuva segmentoidaan eri kudosluokkiin, ja sCT-kuva lasketaan niiden pohjalta. Näin saaduissa sCT-kuvissa oli hyvä kuvanlaatu pienin epäsystemaattisin virhein. PET-kuvantamisessa fotonin lentoaikatieto (TOF) parantaa PET-rekonstruktion tark-kuutta. Tämän parantumisen määrää tutkittiin eri vaimenemiskartoilla fotonin lento-aikaa mittaavien PET-kameroiden vaimenemiskartan laatuvaatimuksien arvioimiseksi. TOF-tieto ei kokonaan pysty poistamaan vaimenemiskartan laadun vaikutusta. Sinusten alue on ongelmallinen MRI-pohjaisessa sCT-kuvan luomisessa, sillä segmentointimenetelmät määrittävät sen usein luuksi. Kaksi uutta menetelmää esiteltiin sinusten alueen PET-kuvantamisen vaimenemiskarttojen laskentaan. Ensimmäinen menetelmä yrittää löytää sellaisen suorakulmaisen särmiön, joka kattaisi suurimman mahdollisen alueen ilmaa, joka on väärin segmentoitu luuksi, ja sitten korjata tämän alueen vaimenemiskertoimen. Toinen menetelmä asettaa suorakulmaisen särmiön normalisoituun kuva-avaruuteen, josta se käännetään takaisin kunkin henkilön omaan yksilölliseen kuva-avaruuteen, minkä jälkeen vaimenemiskertoimet määritetään. Molemmat menetelmät parantavat TT-kuvien ja sCT-kuvien vastaavuutta. Lopuksi tarkasteltiin mahdollisuuksia käyttää koneoppimista ja satunnaismetsäalgoritmeja luun segmentoinnin parantamiseen. Satunnaismetsäalgoritmia käytetään laskemaan ennusteita kunkin kuvapisteen luutodennäköisyydelle. Luutodennäköisyyksiä käytetään luun segmentaation parantamiseen sekä luun tiheyden arviointiin. Kone-oppimispohjainen malli parantaa luun segmentoinnin laatua, sekä vähentää virheitä TT-kuvien ja sCT-kuvien välillä

Regulation of intestinal metabolism in obesity and diabetes : studies using positron emission tomography

The global epidemic of obesity is a challenge to healthcare systems due to the increase in the incidence of type 2 diabetes (T2D) and its associated morbidities. Although the small intestine is the first absorptive organ to encounter the ingested and digesting nutrients, it has gained little attention in the research of T2D and obesity. In the present study, multimodality imaging by Positron emission tomography (PET) combined with magnetic resonance imaging (MRI) or computed tomography (CT) modalities were utilized to study intestinal blood flow and metabolic substrate uptake in healthy normal-weight controls and obese patients with T2D before and after surgical or medical treatments. In the PET imaging, we focused on intestinal blood flow and volume, fatty acid, glucose uptake using 15O-water, 15O-labeled carbon monoxide, palmitate analogue 14(RS)-[18F]fluoro-6-thia-heptadecanoic acid, ([18F]FTHA) and 2-[18F]fluoro- 2-deoxy-D-glucose ([18F]FDG), respectively. Morbidly obese subjects (mean BMI 41±4.5kg/m2) with T2D had similar blood flow in the intestine even after bariatric surgery when compared to healthy controls. The bariatric surgery was either Roux-en Y gastric bypass (n=13) or Sleeve gastrectomy (n=20). Postprandially, nutrient contact with the small intestine and infusion of glucose dependent insulinotrophic polypeptide (GIP) stimulated blood flow in the small intestine of all groups. These findings suggest that despite the adaptation changes after bariatric surgery of the intestine, postprandial blood flow regulation in the small intestine remains intact in T2D and obese individuals. Intestinal fatty acid (FA) uptake was higher in obese subjects compared to healthy counterparts and unexpectedly this increased after bariatric surgery. The FA extraction rate in the small intestine also increased after bariatric surgery and this phenomenon suggests that intestinal energy expenditure relies on high FFA-to-glucose ratio in obese patients, which persists even after weight loss. Glucose uptake in the small intestines of metformin treated study subjects with T2D was increased compared to baseline and reached the level observed in healthy study subjects in previous studies. Taken together, the data of the present study provide novel insight on the role of the small intestine in the multiorgan metabolic derangements associated with T2D. It is not known whether these changes are part of the adaptation mechanism, due to improved glycaemic control and insulin resistance breakdown or due to the fundamental pathophysiology behind T2D. The actual mechanism behind these changes should be addressed in future research.Suoliston aineenvaihdunnan säätely lihavuudessa ja diabeteksessa : positroniemissiotomografiaa käyttäen tehtyjä tutkimuksia Lihavuus on huomattavasti yleistynyt viime vuosikymmeninä ja kuormittaa terveydenhuoltoamme lisäten tyypin 2 diabeteksen ilmaantuvuutta ja yleistä sairastavuutta.Lihavuuden ja tyypin 2 diabeteksen tutkimuksessa on aiemmin keskitytty suoliston aineenvaihduntaan varsin vähän, vaikka suolisto ensimmäisenä elimenä käsittelee elimistöön tulevan ravinnon ja ruoansulatuskanavasta erittyvillä hormoneilla säätelee sokeriaineenvaihduntaa. Tutkimuksessa verrattiin suoliston verenvirtauksen ja ravintoaineiden soluunottokyvyn muutoksia ylipainoisilla tyypin 2 diabeetikoilla ja terveillä normaalipainoisilla verrokeilla käyttäen positroniemissiotomografiaa (PET) yhdistettynä rakenteelliseen magneetti- ja tietokonetomografia kuvantamiseen. Tutkittavat osallistuivat kliinisen hoitokäytännön mukaan lihavuusleikkaukseen tai käyttivät tutkimuslääkettä protokollan mukaan. PET-kuvantamisella tutkittiin suoliston verenvirtauksen ja verimäärän muutoksia sekä rasvahappojen ja sokerin soluunottokykyä käyttäen 15O-vettä, 15Oleimattua hiilimonoksidia, palmitaattianalogi 14(RS)-[18F]fluoro-6-thia-heptadekanoidi happoa ([18F]FTHA) ja 2-[18F]fluoro-2-deoxy-D-glukoosia ([18F]FDG). Sairaalloisen ylipainoisilla diabeetikoilla suoliston verenvirtaus ei poikennut terveistä kontrolleista edes lihavuusleikkauksen jälkeen. Ryhmien välisiä eroja veren virtauksessa ei todettu syömisen ja glukoosista riippuvaisen insuliinin eritystä lisäävän hormonin (GIP) annostelun jälkeen. Havainnot viittaavat siihen, että aterian jälkeinen verenvirtauksen säätely ei ole muuttunut lihavilla diabeetikoilla edes lihavuuskirurgian jälkeen, vaikka suolisto muuten sopeutuu kirurgian aiheuttamiin anatomisiin muutoksiin. Ylipainoisilla tyypin 2 diabetesta sairastavilla tutkittavilla suoliston rasvahappojen soluunottokyky todettiin lisääntyneeksi verrattuna terveisiin kontrollihenkilöihin ja odottamatta lihavuuskirurgia lisäsi kyseistä muutosta. Rasvahappojen soluunottokyvyn lisääntyminen verenkierrosta vielä lihavuuskirurgian jälkeen, osoittaa suoliston energiankäytön riippuvan korkeasta rasvahappo-sokerin käyttösuhteesta vielä laihtumisen jälkeenkin. Metformiini-lääkitys lisäsi suoliston sokerin käyttöä ja vähensi suoliston insuliiniresistenssiä, jopa normaalistaen sen terveiden tasolle. Tämä väitöskirjatutkimus osoittaa, että suolistossa tapahtuu merkittäviä aineenvaihdunnallisia muutoksia tyypin 2 diabeteksessa, ylipainossa ja lihavuusleikkauksen jälkeen. Avoimeksi jää säätelevätkö lihavuuskirurgian ja lääkehoitojen myötä lisääntyneet suoliston rasvahappojen ja sokerin käyttö koko elimistö aineenvaihduntaa vai ovatko ne seurausta suoliston sopeutumisesta muuttuneeseen energia-aineenvaihduntaan. Koska lihavuuskirurgia johtaa usein merkittävään painonlaskuun ja tyypin 2 diabeteksen paranemiseen tulisi suoliston energia-aineenvaihdunnan tutkimusta jatkaa kyseisten tautien syntymekanismin ymmärtämiseksi