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OBJECTIVES: Holistic segmentation of CT structural alterations with 3D deep learning has recently been described in cystic fibrosis (CF), allowing the measurement of normalized volumes of airway abnormalities (NOVAA-CT) as an automated quantitative outcome. Clinical validations are needed, including longitudinal and multicenter evaluations. MATERIALS AND METHODS: The validation study was retrospective between 2010 and 2023. CF patients undergoing Elexacaftor/Tezacaftor/Ivacaftor (ETI) or corticosteroids for allergic broncho-pulmonary aspergillosis (ABPA) composed the monocenter ETI and ABPA groups, respectively. Patients from six geographically distinct institutions composed a multicenter external group. All patients had completed CT and pulmonary function test (PFT), with a second assessment at 1 year in case of ETI or ABPA treatment. NOVAA-CT quantified bronchiectasis, peribronchial thickening, bronchial mucus, bronchiolar mucus, collapse/consolidation, and their overall total abnormal volume (TAV). Two observers evaluated the visual Bhalla score. RESULTS: A total of 139 CF patients (median age, 15 years [interquartile range: 13-25]) were evaluated. All correlations between NOVAA-CT to both PFT and Bhalla score were significant in the ETI (n = 60), ABPA (n = 20), and External groups (n = 59), such as the normalized TAV (ρ ≥ 0.76; p < 0.001). In both ETI and ABPA groups, there were significant longitudinal improvements in peribronchial thickening, bronchial mucus, bronchiolar mucus and collapse/consolidation (p ≤ 0.001). An additional reversibility in bronchiectasis volume was quantified with ETI (p < 0.001). Intraclass correlation coefficient of reproducibility was > 0.99. CONCLUSION: NOVAA-CT automated scoring demonstrates validity, reliability and responsiveness for monitoring CF severity over an entire lung and quantifies therapeutic effects on lung structure at CT, such as the volumetric reversibility of airway abnormalities with ETI. CLINICAL RELEVANCE STATEMENT: Normalized volume of airway abnormalities at CT automated 3D outcome enables objective, reproducible, and holistic monitoring of cystic fibrosis severity over an entire lung for management and endpoints during therapeutic trials. KEY POINTS: Visual scoring methods lack sensitivity and reproducibility to assess longitudinal bronchial changes in cystic fibrosis (CF). AI-driven volumetric CT scoring correlates longitudinally to disease severity and reliably improves with Elexacaftor/Tezacaftor/Ivacaftor or corticosteroid treatments. AI-driven volumetric CT scoring enables reproducible monitoring of lung disease severity in CF and quantifies longitudinal structural therapeutic effects.
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Background Lung MRI with ultrashort echo times (UTEs) enables high-resolution and radiation-free morphologic imaging; however, its image quality is still lower than that of CT. Purpose To assess the image quality and clinical applicability of synthetic CT images generated from UTE MRI by a generative adversarial network (GAN). Materials and Methods This retrospective study included patients with cystic fibrosis (CF) who underwent both UTE MRI and CT on the same day at one of six institutions between January 2018 and December 2022. The two-dimensional GAN algorithm was trained using paired MRI and CT sections and tested, along with an external data set. Image quality was assessed quantitatively by measuring apparent contrast-to-noise ratio, apparent signal-to-noise ratio, and overall noise and qualitatively by using visual scores for features including artifacts. Two readers evaluated CF-related structural abnormalities and used them to determine clinical Bhalla scores. Results The training, test, and external data sets comprised 82 patients with CF (mean age, 21 years ± 11 [SD]; 42 male), 28 patients (mean age, 18 years ± 11; 16 male), and 46 patients (mean age, 20 years ± 11; 24 male), respectively. In the test data set, the contrast-to-noise ratio of synthetic CT images (median, 303 [IQR, 221-382]) was higher than that of UTE MRI scans (median, 9.3 [IQR, 6.6-35]; P < .001). The median signal-to-noise ratio was similar between synthetic and real CT (88 [IQR, 84-92] vs 88 [IQR, 86-91]; P = .96). Synthetic CT had a lower noise level than real CT (median score, 26 [IQR, 22-30] vs 42 [IQR, 32-50]; P < .001) and the lowest level of artifacts (median score, 0 [IQR, 0-0]; P < .001). The concordance between Bhalla scores for synthetic and real CT images was almost perfect (intraclass correlation coefficient, ≥0.92). Conclusion Synthetic CT images showed almost perfect concordance with real CT images for the depiction of CF-related pulmonary alterations and had better image quality than UTE MRI. Clinical trial registration no. NCT03357562 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Schiebler and Glide-Hurst in this issue.
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Fibrose Cística , Adolescente , Adulto , Humanos , Masculino , Adulto Jovem , Fibrose Cística/diagnóstico por imagem , Pulmão/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos , Estudos Retrospectivos , Tomografia Computadorizada por Raios X/métodos , Feminino , CriançaRESUMO
PURPOSE: In presence of respiratory motion, temperature mapping is altered by in-plane and through-plane displacements between successive acquisitions together with periodic phase variations. Fast 2D Echo Planar Imaging (EPI) sequence can accommodate intra-scan motion, but limited volume coverage and inter-scan motion remain a challenge during free-breathing acquisition since position offsets can arise between the different slices. METHOD: To address this limitation, we evaluated a 2D simultaneous multi-slice EPI sequence with multiband (MB) acceleration during radiofrequency ablation on a mobile gel and in the liver of a volunteer (no heating). The sequence was evaluated in terms of resulting inter-scan motion, temperature uncertainty and elevation, potential false-positive heating and repeatability. Lastly, to account for potential through-plane motion, a 3D motion compensation pipeline was implemented and evaluated. RESULTS: In-plane motion was compensated whatever the MB factor and temperature distribution was found in agreement during both the heating and cooling periods. No obvious false-positive temperature was observed under the conditions being investigated. Repeatability of measurements results in a 95% uncertainty below 2 °C for MB1 and MB2. Uncertainty up to 4.5 °C was reported with MB3 together with the presence of aliasing artifacts. Lastly, fast simultaneous multi-slice EPI combined with 3D motion compensation reduce residual out-of-plane motion. CONCLUSION: Volumetric temperature imaging (12 slices/700 ms) could be performed with 2 °C accuracy or less, and offer tradeoffs in acquisition time or volume coverage. Such a strategy is expected to increase procedure safety by monitoring large volumes more rapidly for MR-guided thermotherapy on mobile organs.
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Imagem Ecoplanar , Termometria , Humanos , Imagem Ecoplanar/métodos , Termometria/métodos , Termografia/métodos , Temperatura , Temperatura Corporal , Encéfalo , Imageamento por Ressonância Magnética/métodos , Processamento de Imagem Assistida por ComputadorRESUMO
BACKGROUND: Chest computed tomography (CT) remains the imaging standard for demonstrating cystic fibrosis (CF) airway structural disease in vivo. However, visual scoring systems as an outcome measure are time consuming, require training and lack high reproducibility. Our objective was to validate a fully automated artificial intelligence (AI)-driven scoring system of CF lung disease severity. METHODS: Data were retrospectively collected in three CF reference centres, between 2008 and 2020, in 184 patients aged 4-54â years. An algorithm using three 2D convolutional neural networks was trained with 78 patients' CT scans (23â530 CT slices) for the semantic labelling of bronchiectasis, peribronchial thickening, bronchial mucus, bronchiolar mucus and collapse/consolidation. 36 patients' CT scans (11â435 CT slices) were used for testing versus ground-truth labels. The method's clinical validity was assessed in an independent group of 70 patients with or without lumacaftor/ivacaftor treatment (n=10 and n=60, respectively) with repeat examinations. Similarity and reproducibility were assessed using the Dice coefficient, correlations using the Spearman test, and paired comparisons using the Wilcoxon rank test. RESULTS: The overall pixelwise similarity of AI-driven versus ground-truth labels was good (Dice 0.71). All AI-driven volumetric quantifications had moderate to very good correlations to a visual imaging scoring (p<0.001) and fair to good correlations to forced expiratory volume in 1â s % predicted at pulmonary function tests (p<0.001). Significant decreases in peribronchial thickening (p=0.005), bronchial mucus (p=0.005) and bronchiolar mucus (p=0.007) volumes were measured in patients with lumacaftor/ivacaftor. Conversely, bronchiectasis (p=0.002) and peribronchial thickening (p=0.008) volumes increased in patients without lumacaftor/ivacaftor. The reproducibility was almost perfect (Dice >0.99). CONCLUSION: AI allows fully automated volumetric quantification of CF-related modifications over an entire lung. The novel scoring system could provide a robust disease outcome in the era of effective CF transmembrane conductance regulator modulator therapy.
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Inteligência Artificial , Regulador de Condutância Transmembrana em Fibrose Cística , Adolescente , Adulto , Aminopiridinas/uso terapêutico , Criança , Pré-Escolar , Humanos , Pulmão/diagnóstico por imagem , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Estudos Retrospectivos , Tomografia Computadorizada por Raios X , Adulto JovemRESUMO
OBJECTIVE: To assess automatic computer-aided in situ recognition of the morphological features of pure and mixed urinary stones using intra-operative digital endoscopic images acquired in a clinical setting. MATERIALS AND METHODS: In this single-centre study, a urologist with 20 years' experience intra-operatively and prospectively examined the surface and section of all kidney stones encountered. Calcium oxalate monohydrate (COM) or Ia, calcium oxalate dihydrate (COD) or IIb, and uric acid (UA) or IIIb morphological criteria were collected and classified to generate annotated datasets. A deep convolutional neural network (CNN) was trained to predict the composition of both pure and mixed stones. To explain the predictions of the deep neural network model, coarse localization heat-maps were plotted to pinpoint key areas identified by the network. RESULTS: This study included 347 and 236 observations of stone surface and stone section, respectively; approximately 80% of all stones exhibited only one morphological type and approximately 20% displayed two. A highest sensitivity of 98% was obtained for the type 'pure IIIb/UA' using surface images. The most frequently encountered morphology was that of the type 'pure Ia/COM'; it was correctly predicted in 91% and 94% of cases using surface and section images, respectively. Of the mixed type 'Ia/COM + IIb/COD', Ia/COM was predicted in 84% of cases using surface images, IIb/COD in 70% of cases, and both in 65% of cases. With regard to mixed Ia/COM + IIIb/UA stones, Ia/COM was predicted in 91% of cases using section images, IIIb/UA in 69% of cases, and both in 74% of cases. CONCLUSIONS: This preliminary study demonstrates that deep CNNs are a promising method by which to identify kidney stone composition from endoscopic images acquired intra-operatively. Both pure and mixed stone composition could be discriminated. Collected in a clinical setting, surface and section images analysed by a deep CNN provide valuable information about stone morphology for computer-aided diagnosis.
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Cálculos Renais , Cálculos Urinários , Oxalato de Cálcio , Endoscopia , Humanos , Cálculos Renais/diagnóstico por imagem , Cálculos Renais/cirurgia , Ácido Úrico , Cálculos Urinários/diagnóstico por imagem , Cálculos Urinários/cirurgiaRESUMO
OBJECTIVE: To improve endoscopic recognition of the most frequently encountered urinary stone morphologies for a better aetiological approach in lithiasis by urologists. MATERIALS AND METHODS: An expert urologist intraoperatively and prospectively (between June 2015 and June 2018) examined the surface, the section, and the nucleus of all encountered kidney stones. Fragmented stones were subsequently analysed by a biologist based on both microscopic morphological (i.e. binocular magnifying glass) and infrared (i.e. Fourier transform-infrared spectroscopy) examinations (microscopists were blinded to the endoscopic data). Morphological criteria were collected and classified for the endoscopic and microscopic studies. The Wilcoxon-Mann-Whitney test was used to detect differences between the endoscopic and microscopic diagnoses. A diagnosis for a given urinary stone was considered 'confirmed' for a non-statistically significant difference. RESULTS: A total of 399 urinary stones were included in this study: 51.4% of the stones had only one morphological type, while 48.6% were mixed stones (41% had at least two morphologies and 7.6% had three morphologies). The overall matching rate was 81.6%. Diagnostics were confirmed for the following morphologies: whewellite (Ia or Ib), weddellite (IIa or IIb), uric acid (IIIa or IIIb), carbapatite-struvite association (IVb), and brushite (IVd). CONCLUSIONS: Our preliminary study demonstrates the feasibility of using endoscopic morphology for the most frequently encountered urinary stones and didactic boards of confirmed endoscopic images are provided. The present study constitutes the first step toward endoscopic stone recognition, which is essential in lithiasis. We provide didactic boards of confirmed endoscopic images that pave the way for automatic computer-aided in situ recognition.
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Cálculos Renais/química , Cálculos Renais/patologia , Ureteroscopia , Humanos , Microscopia , Estudos Retrospectivos , Espectroscopia de Infravermelho com Transformada de FourierRESUMO
Whole brain segmentation of fine-grained structures using deep learning (DL) is a very challenging task since the number of anatomical labels is very high compared to the number of available training images. To address this problem, previous DL methods proposed to use a single convolution neural network (CNN) or few independent CNNs. In this paper, we present a novel ensemble method based on a large number of CNNs processing different overlapping brain areas. Inspired by parliamentary decision-making systems, we propose a framework called AssemblyNet, made of two "assemblies" of U-Nets. Such a parliamentary system is capable of dealing with complex decisions, unseen problem and reaching a relevant consensus. AssemblyNet introduces sharing of knowledge among neighboring U-Nets, an "amendment" procedure made by the second assembly at higher-resolution to refine the decision taken by the first one, and a final decision obtained by majority voting. During our validation, AssemblyNet showed competitive performance compared to state-of-the-art methods such as U-Net, Joint label fusion and SLANT. Moreover, we investigated the scan-rescan consistency and the robustness to disease effects of our method. These experiences demonstrated the reliability of AssemblyNet. Finally, we showed the interest of using semi-supervised learning to improve the performance of our method.
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Encéfalo/diagnóstico por imagem , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Aprendizado Profundo , Humanos , SoftwareRESUMO
OBJECTIVE: A new computer tool is proposed to distinguish between focal nodular hyperplasia (FNH) and an inflammatory hepatocellular adenoma (I-HCA) using contrast-enhanced ultrasound (CEUS). The new method was compared with the usual qualitative analysis. METHODS: The proposed tool embeds an "optical flow" algorithm, designed to mimic the human visual perception of object transport in image series, to quantitatively analyse apparent microbubble transport parameters visible on CEUS. Qualitative (visual) and quantitative (computer-assisted) CEUS data were compared in a cohort of adult patients with either FNH or I-HCA based on pathological and radiological results. For quantitative analysis, several computer-assisted classification models were tested and subjected to cross-validation. The accuracies, area under the receiver-operating characteristic curve (AUROC), sensitivity and specificity, positive predictive values (PPVs), negative predictive values (NPVs), false predictive rate (FPRs) and false negative rate (FNRs) were recorded. RESULTS: Forty-six patients with FNH (n = 29) or I-HCA (n = 17) with 47 tumours (one patient with 2 I-HCA) were analysed. The qualitative diagnostic parameters were accuracy = 93.6%, AUROC = 0.94, sensitivity = 94.4%, specificity = 93.1%, PPV = 89.5%, NPV = 96.4%, FPR = 6.9% and FNR = 5.6%. The quantitative diagnostic parameters were accuracy = 95.9%, AUROC = 0.97, sensitivity = 93.4%, specificity = 97.6%, PPV = 95.3%, NPV = 96.7%, FPR = 2.4% and FNR = 6.6%. CONCLUSIONS: Microbubble transport patterns evident on CEUS are valuable diagnostic indicators. Machine-learning algorithms analysing such data facilitate the diagnosis of FNH and I-HCA tumours. KEY POINTS: ⢠Distinguishing between focal nodular hyperplasia and an inflammatory hepatocellular adenoma using dynamic contrast-enhanced ultrasound is sometimes difficult. ⢠Microbubble transport patterns evident on contrast-enhanced sonography are valuable diagnostic indicators. ⢠Machine-learning algorithms analysing microbubble transport patterns facilitate the diagnosis of FNH and I-HCA.
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Adenoma de Células Hepáticas/diagnóstico por imagem , Carcinoma Hepatocelular/diagnóstico por imagem , Meios de Contraste , Diagnóstico por Computador/métodos , Hiperplasia Nodular Focal do Fígado/diagnóstico por imagem , Aumento da Imagem/métodos , Neoplasias Hepáticas/diagnóstico por imagem , Microbolhas , Ultrassonografia/métodos , Adulto , Idoso , Confiabilidade dos Dados , Diagnóstico Diferencial , Feminino , Seguimentos , Humanos , Aprendizado de Máquina , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Sensibilidade e Especificidade , Adulto JovemRESUMO
Arterial spin labeling (ASL)-MRI can noninvasively map cerebral blood flow (CBF) and cerebrovascular reactivity (CVR), potential biomarkers of cognitive impairment and dementia. Mouse models of disease are frequently used in translational MRI studies, which are commonly performed under anesthesia. Understanding the influence of the specific anesthesia protocol used on the measured parameters is important for accurate interpretation of hemodynamic studies with mice. Isoflurane is a frequently used anesthetic with vasodilative properties. Here, the influence of three distinct isoflurane protocols was studied with pseudo-continuous ASL in two different mouse strains. The first protocol was a free-breathing set-up with medium concentrations, the second a free-breathing set-up with low induction and maintenance concentrations, and the third a set-up with medium concentrations and mechanical ventilation. A protocol with the vasoconstrictive anesthetic medetomidine was used as a comparison. As expected, medium isoflurane anesthesia resulted in significantly higher CBF and lower CVR values than medetomidine (median whole-brain CBF of 157.7 vs 84.4 mL/100 g/min and CVR of 0.54 vs 51.7% in C57BL/6 J mice). The other two isoflurane protocols lowered the CBF and increased the CVR values compared with medium isoflurane anesthesia, without obvious differences between them (median whole-brain CBF of 138.9 vs 131.7 mL/100 g/min and CVR of 10.0 vs 9.6%, in C57BL/6 J mice). Furthermore, CVR was shown to be dependent on baseline CBF, regardless of the anesthesia protocol used.
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Anestesia , Encéfalo/fisiologia , Artérias Cerebrais/fisiologia , Hemodinâmica/efeitos dos fármacos , Isoflurano/farmacologia , Marcadores de Spin , Animais , Encéfalo/efeitos dos fármacos , Artérias Cerebrais/efeitos dos fármacos , Circulação Cerebrovascular/efeitos dos fármacos , Feminino , Masculino , Camundongos Endogâmicos C57BLRESUMO
PURPOSE: To demonstrate that fluid filling of the digestive tract improves the performance of respiratory motion-compensated proton resonance frequency shift (PRFS)-based magnetic resonance (MR) thermometry in the pancreas. MATERIALS AND METHODS: In seven volunteers (without heating), we evaluated PRFS thermometry in the pancreas with and without filling of the surrounding digestive tract. All data acquisition was performed at 1.5T, then all datasets were analyzed and compared with three different PRFS respiratory motion-compensated thermometry methods: gating, multibaseline, and referenceless. The temperature precision of the different methods was evaluated by assessing temperature standard deviation over time, while a simulation experiment was used to study the accuracy of the methods. RESULTS: Without fluid intake, errors in temperature precision in the pancreas up to 10°C were observed for all evaluated methods. After liquid intake, temperature precision improved to median values between 1.8 and 2.9°C. The simulations showed that gating had the lowest accuracy, with errors up to 7°C. Multibaseline and referenceless thermometry performed better, with a median error in the pancreas between -3 and +3°C after fluid intake, for all volunteers. CONCLUSION: Preparation of the digestive tract near the pancreas by filling it with fluid improved MR thermometry precision and accuracy for all common respiratory motion-compensated methods evaluated. These improvements are attributed to reducing field inhomogeneity in the pancreas. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:692-701.
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Sucos de Frutas e Vegetais , Trato Gastrointestinal , Imageamento por Ressonância Magnética/métodos , Pâncreas/diagnóstico por imagem , Termometria/métodos , Adulto , Humanos , Masculino , Valores de ReferênciaRESUMO
AIM: To assess regular MRI findings and tumour texture features on pre-CRT imaging as potential predictive factors of event-free survival (disease progression or death) after chemoradiotherapy (CRT) for anal squamous cell carcinoma (ASCC) without metastasis. MATERIALS AND METHODS: We retrospectively included 28 patients treated by CRT for pathologically proven ASCC with a pre-CRT MRI. Texture analysis was carried out with axial T2W images by delineating a 3D region of interest around the entire tumour volume. First-order analysis by quantification of the histogram was carried out. Second-order statistical texture features were derived from the calculation of the grey-level co-occurrence matrix using a distance of 1 (d1), 2 (d2) and 5 (d5) pixels. Prognostic factors were assessed by Cox regression and performance of the model by the Harrell C-index. RESULTS: Eight tumour progressions led to six tumour-specific deaths. After adjusting for age, gender and tumour grade, skewness (HR = 0.131, 95% CI = 0-0.447, p = 0.005) and cluster shade_d1 (HR = 0.601, 95% CI = 0-0.861, p = 0.027) were associated with event occurrence. The corresponding Harrell C-indices were 0.846, 95% CI = 0.697-0.993, and 0.851, 95% CI = 0.708-0.994. CONCLUSION: ASCC MR texture analysis provides prognostic factors of event occurrence and requires additional studies to assess its potential in an "individual dose" strategy for ASCC chemoradiation therapy. KEY POINTS: ⢠MR texture features help to identify tumours with high progression risk. ⢠Texture feature maps help to identify intra-tumoral heterogeneity. ⢠Texture features are a better prognostic factor than regular MR findings.
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Neoplasias do Ânus/terapia , Carcinoma de Células Escamosas/terapia , Quimiorradioterapia/métodos , Idoso , Neoplasias do Ânus/mortalidade , Neoplasias do Ânus/patologia , Carcinoma de Células Escamosas/mortalidade , Carcinoma de Células Escamosas/patologia , Quimiorradioterapia/mortalidade , Intervalo Livre de Doença , Feminino , Humanos , Imageamento por Ressonância Magnética/métodos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Resultado do Tratamento , Carga TumoralRESUMO
INTRODUCTION: Magnetic resonance-guided high-intensity focused ultrasound (MRgHIFU) treatments of mobile organs require locking the HIFU beam on the targeted tissue to maximise heating efficiency. We propose to use a standalone 3 D ultrasound (US)-based motion correction technique using the HIFU transducer in pulse-echo mode. Validation of the method was performed in vitro and in vivo in the liver of pig under MR-thermometry. METHODS: 3 D-motion estimation was implemented using ultrasonic speckle-tracking between consecutive acquisitions. Displacement was estimated along four sub-apertures of the HIFU transducer by computing the normalised cross-correlation of backscattered signals followed by a triangulation algorithm. The HIFU beam was steered accordingly and energy was delivered under real-time MR-thermometry (using the proton resonance frequency shift method with online motion compensation and correction of associated susceptibility artefacts). An MR-navigator echo was used to assess the quality of the US-based motion correction. RESULTS: Displacement estimations from US measurements were in good agreement with 1 D MR-navigator echo readings. In vitro, the maximum temperature increase was improved by 37% as compared to experiments performed without motion correction and temperature distribution remained much more focussed. Similar results were reported in vivo, with an increase of 35% on the maximum temperature using this US-based HIFU target locking. CONCLUSION: This standalone 3D US-based motion correction technique is robust and allows maintaining the HIFU focal spot in the presence of motion without adding any burden or complexity to MR thermal imaging. In vitro and in vivo results showed about 35% improvement in heating efficiency when focus position was locked on the target using the proposed technique.
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Fígado/diagnóstico por imagem , Fígado/cirurgia , Animais , Ablação por Ultrassom Focalizado de Alta Intensidade , Imageamento por Ressonância Magnética , Suínos , Ultrassonografia/métodosRESUMO
BACKGROUND: Clinical treatment of cardiac arrhythmia by radiofrequency ablation (RFA) currently lacks quantitative and precise visualization of lesion formation in the myocardium during the procedure. This study aims at evaluating thermal dose (TD) imaging obtained from real-time magnetic resonance (MR) thermometry on the heart as a relevant indicator of the thermal lesion extent. METHODS: MR temperature mapping based on the Proton Resonance Frequency Shift (PRFS) method was performed at 1.5 T on the heart, with 4 to 5 slices acquired per heartbeat. Respiratory motion was compensated using navigator-based slice tracking. Residual in-plane motion and related magnetic susceptibility artifacts were corrected online. The standard deviation of temperature was measured on healthy volunteers (N = 5) in both ventricles. On animals, the MR-compatible catheter was positioned and visualized in the left ventricle (LV) using a bSSFP pulse sequence with active catheter tracking. Twelve MR-guided RFA were performed on three sheep in vivo at various locations in left ventricle (LV). The dimensions of the thermal lesions measured on thermal dose images, on 3D T1-weighted (T1-w) images acquired immediately after the ablation and at gross pathology were correlated. RESULTS: MR thermometry uncertainty was 1.5 °C on average over more than 96% of the pixels covering the left and right ventricles, on each volunteer. On animals, catheter repositioning in the LV with active slice tracking was successfully performed and each ablation could be monitored in real-time by MR thermometry and thermal dosimetry. Thermal lesion dimensions on TD maps were found to be highly correlated with those observed on post-ablation T1-w images (R = 0.87) that also correlated (R = 0.89) with measurements at gross pathology. CONCLUSIONS: Quantitative TD mapping from real-time rapid CMR thermometry during catheter-based RFA is feasible. It provides a direct assessment of the lesion extent in the myocardium with precision in the range of one millimeter. Real-time MR thermometry and thermal dosimetry may improve safety and efficacy of the RFA procedure by offering a reliable indicator of therapy outcome during the procedure.
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Ablação por Cateter , Imagem Cinética por Ressonância Magnética , Miocárdio/patologia , Termometria/métodos , Animais , Artefatos , Temperatura Corporal , Cateteres Cardíacos , Ablação por Cateter/instrumentação , Estudos de Viabilidade , Frequência Cardíaca , Humanos , Modelos Animais , Valor Preditivo dos Testes , Reprodutibilidade dos Testes , Mecânica Respiratória , Carneiro Doméstico , Termometria/instrumentação , Fatores de TempoRESUMO
OBJECTIVES: The objective of this study is to assess the association between texture parameter analysis derived from T2-weighted images and efficiency of magnetic resonance-guided focussed ultrasound (MRgFUS) ablation for the treatment of uterine fibroids. MATERIALS AND METHODS: Fifty-five women treated by MRgFUS were included in this retrospective analysis. Texture parameters were calculated using three 2D regions of interest placed on three consecutive slices on the same sagittal 3D T2-weighted images obtained at the beginning of MRgFUS ablation. Using uni- and multi-variate linear regression, texture parameters, fibroids/muscular T2W ratio (T2Wr), Funaki type, and fibroid depth were correlated with ablation efficiency, defined as the ratio of non-perfused volume (NPV) on post-treatment contrast-enhanced MRI by total volume of treatment-cell sizes used. Inter-rater reproducibility for texture analysis was assessed using variation coefficients. RESULTS: The mean total treatment cell volume was 49.5 (±30) ml, corresponding to a mean NPV of 57.2 (±57) ml (28%). The mean ablation efficiency was 1.14 (±0.7), with a range of 0.03-3.6. In addition to fibroid/muscular T2Wr, seven of the 14 texture parameters were significantly correlated with ablation efficiency: mean signal intensity (p = .047); Skewness (p = .03); Kurtosis (p = .015); mean uniformity (p = .052); mean sum of square (p = .045); mean sum entropy (p = .021) and mean entropy (p = .051). In multivariate linear regression, fibroid/muscular T2Wr and sum of entropy were associated with ablation efficiency. The inter-rater coefficient of variation for sum entropy was 2.6%. CONCLUSIONS: Uterine fibroid texture parameters provide complementary information to T2Wr, and are associated with MRgFUS efficiency. Key points Mean sum entropy is negatively correlated with MRgFUS efficiency (ρ = -0.307, p = .021). Fibroids/muscular T2-weighted ratio and entropy are associated with MRgFUS efficiency. Texture parameters are better predictors of MRgFUS efficiency than Funaki type. Fibroid MR texture analysis can improve patient selection for MRgFUS.
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PURPOSE: To propose a postprocessing technique that measures tumor surface with insufficient ablative margins (≤ 5 mm) on magnetic resonance (MR) imaging to predict local tumor progression (LTP) following radiofrequency (RF) ablation. MATERIALS AND METHODS: A diagnostic method is proposed based on measurement of tumor surface with a margin ≤ 5 mm on MR imaging. The postprocessing technique includes fully automatic registration of pre- and post-RF ablation MR imaging, a semiautomatic segmentation of pre-RF ablation tumor and post-RF ablation volume, and a subsequent calculation of the three-dimensional exposed tumor surface area. The ability to use this surface margin ≤ 5 mm to predict local recurrence at 2 years was then tested on 16 patients with cirrhosis who were treated by RF ablation with a margin ≤ 5 mm in 2012: eight with LTP matched according to tumor size and number and α-fetoprotein level versus eight without local recurrence. RESULTS: The error of estimated tumor surface with a margin ≤ 5 mm was less than 12%. Results of a log-rank test showed that patients with a tumor surface area > 425 mm(2) had a 2-year LTP rate of 77.5%, compared with 25% for patients with a tumor surface area ≤ 425 mm(2) (P = .018). CONCLUSIONS: This proof-of-concept study proposes an accurate and reliable postprocessing technique to estimate tumor surface with insufficient ablative margins, and underscores the potential usefulness of tumor surface with a margin ≤ 5 mm to stratify patients with HCC treated by RF ablation according to their risk of LTP.
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Carcinoma Hepatocelular/diagnóstico por imagem , Carcinoma Hepatocelular/cirurgia , Ablação por Cateter/efeitos adversos , Interpretação de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Neoplasias Hepáticas/diagnóstico por imagem , Neoplasias Hepáticas/cirurgia , Imageamento por Ressonância Magnética/métodos , Recidiva Local de Neoplasia , Idoso , Carcinoma Hepatocelular/sangue , Carcinoma Hepatocelular/patologia , Progressão da Doença , Feminino , Humanos , Neoplasias Hepáticas/sangue , Neoplasias Hepáticas/patologia , Masculino , Margens de Excisão , Pessoa de Meia-Idade , Neoplasia Residual , Valor Preditivo dos Testes , Reprodutibilidade dos Testes , Estudos Retrospectivos , Medição de Risco , Fatores de Risco , Fatores de Tempo , Resultado do Tratamento , Carga Tumoral , alfa-Fetoproteínas/metabolismoRESUMO
Local drug delivery by hyperthermia-induced drug release from thermosensitive liposomes (TSLs) may reduce the systemic toxicity of chemotherapy, whilst maintaining or increasing its efficacy. Relaxivity contrast agents can be co-encapsulated with the drug to allow the visualization of the presence of liposomes, by means of R2 *, as well as the co-release of the contrast agent and the drug, by means of R1, on heating. Here, the mathematical method used to extract both R2 * and R1 from a fast dynamic multi-echo spoiled gradient echo (ME-SPGR) is presented and analyzed. Finally, this method is used to monitor such release events. R2 * was obtained from a fit to the ME-SPGR data. Absolute R1 was calculated from the signal magnitude changes corrected for the apparent proton density changes and a baseline Look-Locker R1 map. The method was used to monitor nearly homogeneous water bath heating and local focused ultrasound heating of muscle tissue, and to visualize the release of a gadolinium chelate from TSLs in vitro. R2 *, R1 and temperature maps were measured with a 5-s temporal resolution. Both R2 *and R1 measured were found to change with temperature. The dynamic R1 measurements after heating agreed with the Look-Locker R1 values if changes in equilibrium magnetization with temperature were considered. Release of gadolinium from TSLs was detected by an R1 increase near the phase transition temperature, as well as a shallow R2 * increase. Simultaneous temperature, R2 * and R1 mapping is feasible in real time and has the potential for use in image-guided drug delivery studies.
Assuntos
Sistemas de Liberação de Medicamentos/métodos , Monitoramento de Medicamentos/métodos , Imageamento por Ressonância Magnética/métodos , Termometria/métodos , Animais , Antineoplásicos/farmacocinética , Meios de Contraste , Portadores de Fármacos/farmacocinética , Espectroscopia de Ressonância de Spin Eletrônica , Gadolínio/administração & dosagem , Gadolínio/análise , Gadolínio/farmacocinética , Calefação/instrumentação , Compostos Heterocíclicos/administração & dosagem , Compostos Heterocíclicos/análise , Lipossomos/administração & dosagem , Músculo Esquelético/anatomia & histologia , Compostos Organometálicos/administração & dosagem , Compostos Organometálicos/análise , Tamanho da Partícula , Sus scrofa , Suínos , Temperatura , Distribuição Tecidual , UltrassomRESUMO
Objective.In medical imaging, it is often crucial to accurately assess and correct movement during image-guided therapy. Deformable image registration (DIR) consists in estimating the required spatial transformation to align a moving image with a fixed one. However, it is acknowledged that for DIR methods, boundary conditions applied to the solution are critical in preventing mis-registration. This poses an issue particularly when areas of interest are located near the image border. Despite the extensive research on registration techniques, relatively few have addressed the issue of boundary conditions in the context of medical DIR. Our aim is a step towards customizing boundary conditions to suit the diverse registration tasks at hand.Approach.We analyze the behavior of two typical global boundary conditions: homogeneous Dirichlet and homogeneous Neumann. We propose a generic, locally adaptive, Robin-type condition enabling to balance between Dirichlet and Neumann boundary conditions, depending on incoming/outgoing flow fields on the image boundaries. The proposed framework is entirely automatized through the determination of a reduced set of hyperparameters optimized via energy minimization.Main results.The proposed approach was tested on a mono-modal computed tomography (CT) thorax registration task and an abdominal CT-to-MRI registration task. For the first task, we observed a relative improvement in terms of target registration error of up to 12% (mean 4%), compared to homogeneous Dirichlet and homogeneous Neumann. For the second task, the automatic framework provides results close to the best achievable.Significance.This study underscores the importance of tailoring the registration problem at the image boundaries. In this research, we introduce a novel method to adapt the boundary conditions on a voxel-by-voxel basis, yielding optimized results in two distinct tasks: mono-modal CT thorax registration and abdominal CT-to-MRI registration. The proposed framework enables optimized boundary conditions in image registration without prior assumptions regarding the images or the motion.
Assuntos
Processamento de Imagem Assistida por Computador , Imageamento por Ressonância Magnética , Tomografia Computadorizada por Raios X , Processamento de Imagem Assistida por Computador/métodos , Humanos , Radiografia Torácica , AlgoritmosRESUMO
Objectives: Non-invasive subtyping of hepatocellular adenomas (HCA) remains challenging for several subtypes, thus carrying different levels of risks and management. The goal of this study is to devise a multivariable diagnostic model based on basic clinical features (age and sex) combined with MRI-radiomics and to evaluate its diagnostic performance. Methods: This single-center retrospective case-control study included all consecutive patients with HCA identified within the pathological database from our institution from January 2003 to April 2018 with MRI examination (T2, T1-no injection/injection-arterial-portal); volumes of interest were manually delineated in adenomas and 38 textural features were extracted (LIFEx, v5.10). Qualitative (i.e., visual on MRI) and automatic (computer-assisted) analysis were compared. The prognostic scores of a multivariable diagnostic model based on basic clinical features (age and sex) combined with MRI-radiomics (tumor volume and texture features) were assessed using a cross-validated Random Forest algorithm. Results: Via visual MR-analysis, HCA subgroups could be classified with balanced accuracies of 80.8 % (I-HCA or ß-I-HCA, the two being indistinguishable), 81.8 % (H-HCA) and 74.4 % (sh-HCA or ß-HCA also indistinguishable). Using a model including age, sex, volume and texture variables, HCA subgroups were predicted (multivariate classification) with an averaged balanced accuracy of 58.6 %, best=73.8 % (sh-HCA) and 71.9 % (ß-HCA). I-HCA and ß-I-HCA could be also distinguished (binary classification) with a balanced accuracy of 73 %. Conclusion: Multiple HCA subtyping could be improved using machine-learning algorithms including two clinical features, i.e., age and sex, combined with MRI-radiomics. Future HCA studies enrolling more patients will further test the validity of the model.
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Background: Cerebral amyloid angiopathy (CAA) is a cerebral small vessel disease in which amyloid-ß accumulates in vessel walls. CAA is a leading cause of symptomatic lobar intracerebral hemorrhage and an important contributor to age-related cognitive decline. Recent work has suggested that vascular dysfunction may precede symptomatic stages of CAA, and that spontaneous slow oscillations in arteriolar diameter (termed vasomotion), important for amyloid-ß clearance, may be impaired in CAA. Methods: To systematically study the progression of vascular dysfunction in CAA, we used the APP23 mouse model of amyloidosis, which is known to develop spontaneous cerebral microbleeds mimicking human CAA. Using in vivo 2-photon microscopy, we longitudinally imaged unanesthetized APP23 transgenic mice and wildtype littermates from 7 to 14 months of age, tracking amyloid-ß accumulation and vasomotion in individual pial arterioles over time. MRI was used in separate groups of 12-, 18-, and 24-month-old APP23 transgenic mice and wildtype littermates to detect microbleeds and to assess cerebral blood flow and cerebrovascular reactivity with pseudo-continuous arterial spin labeling. Results: We observed a significant decline in vasomotion with age in APP23 mice, while vasomotion remained unchanged in wildtype mice with age. This decline corresponded in timing to initial vascular amyloid-ß deposition (â¼8-10 months of age), although was more strongly correlated with age than with vascular amyloid-ß burden in individual arterioles. Declines in vasomotion preceded the development of MRI-visible microbleeds and the loss of smooth muscle actin in arterioles, both of which were observed in APP23 mice by 18 months of age. Additionally, evoked cerebrovascular reactivity was intact in APP23 mice at 12 months of age, but significantly lower in APP23 mice by 24 months of age. Conclusions: Our findings suggest that a decline in spontaneous vasomotion is an early, potentially pre-symptomatic, manifestation of CAA and vascular dysfunction, and a possible future treatment target.
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BACKGROUND: Deformable image registration is increasingly used in radiotherapy to adapt the treatment plan and accumulate the delivered dose. Consequently, clinical workflows using deformable image registration require quick and reliable quality assurance to accept registrations. Additionally, for online adaptive radiotherapy, quality assurance without the need for an operator to delineate contours while the patient is on the treatment table is needed. Established quality assurance criteria such as the Dice similarity coefficient or Hausdorff distance lack these qualities and also display a limited sensitivity to registration errors beyond soft tissue boundaries. PURPOSE: The purpose of this study is to investigate the existing intensity-based quality assurance criteria structural similarity and normalized mutual information for their ability to quickly and reliably identify registration errors for (online) adaptive radiotherapy and compare them to contour-based quality assurance criteria. METHODS: All criteria were tested using synthetic and simulated biomechanical deformations of 3D MR images as well as manually annotated 4D CT data. The quality assurance criteria were scored for classification performance, for their ability to predict the registration error, and for their spatial information. RESULTS: We found that besides being fast and operator-independent, the intensity-based criteria have the highest area under the receiver operating characteristic curve and provide the best input for models to predict the registration error on all data sets. Structural similarity furthermore provides spatial information with a higher gamma pass rate of the predicted registration error than commonly used spatial quality assurance criteria. CONCLUSIONS: Intensity-based quality assurance criteria can provide the required confidence in decisions about using mono-modal registrations in clinical workflows. They thereby enable automated quality assurance for deformable image registration in adaptive radiotherapy treatments.