Mindy X. Wang, Jeffrey R. Guccione, B. R. Korivi, M. Abdelsalam, S. Klimkowski, Moataz Soliman, A. Shalaby, K. Elsayes
Gastrointestinal bleeding (GIB) among cancer patients is a major source of morbidity and mortality. Although a wide variety of etiologies contribute to GIB, special considerations should be made for cancer-related factors such as the type of malignancy, location and extent of disease, hemostatic parameters, and treatment effects. Key imaging modalities used to evaluate GIB include computed tomography angiography (CTA), radionuclide imaging, and catheter-based angiography. Understanding the cancer and treatment history and recognizing the associated imaging manifestations are important for identifying the source and potential causes of GIB in cancer patients. This article will review the common clinical presentations, causes, imaging manifestations, and angiographic management of GIB in cancer patients.
{"title":"Gastrointestinal bleeding: Imaging and interventions in cancer patients.","authors":"Mindy X. Wang, Jeffrey R. Guccione, B. R. Korivi, M. Abdelsalam, S. Klimkowski, Moataz Soliman, A. Shalaby, K. Elsayes","doi":"10.1259/bjr.20211158","DOIUrl":"https://doi.org/10.1259/bjr.20211158","url":null,"abstract":"Gastrointestinal bleeding (GIB) among cancer patients is a major source of morbidity and mortality. Although a wide variety of etiologies contribute to GIB, special considerations should be made for cancer-related factors such as the type of malignancy, location and extent of disease, hemostatic parameters, and treatment effects. Key imaging modalities used to evaluate GIB include computed tomography angiography (CTA), radionuclide imaging, and catheter-based angiography. Understanding the cancer and treatment history and recognizing the associated imaging manifestations are important for identifying the source and potential causes of GIB in cancer patients. This article will review the common clinical presentations, causes, imaging manifestations, and angiographic management of GIB in cancer patients.","PeriodicalId":226783,"journal":{"name":"The British journal of radiology","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129524439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. van Assen, Mohammadreza Zandehshahvar, H. Maleki, Y. Kiarashi, T. Arleo, A. Stillman, Peter D Filev, A. Davarpanah, E. Berkowitz, S. Tigges, Scott J. Lee, B. Vey, A. Adibi, C. D. De Cecco
OBJECTIVE The purpose was to evaluate reader variability between experienced and in-training radiologists of COVID-19 pneumonia severity on CXR, and to create a multi reader database suitable for AI development. METHODS In this study, CXRs from PCR positive COVID-19 patients were reviewed. Six experienced cardiothoracic radiologists and two residents classified each CXR according to severity. One radiologist performed the classification twice to assess intra observer variability. Severity classification was assessed using a four-class system: normal(0), mild, moderate, and severe. A median severity score (Rad Med) for each CXR was determined for the six radiologists for development of a multi reader database (XCOMS). Kendal Tau correlation and percentage of disagreement were calculated to assess variability. RESULTS A total of 397 patients (1208 CXRs) were included (mean age, 60 years SD ±1), 189 men). Inter observer variability between the radiologists ranges between 0.67-0.78. Compared to the Rad Med score, the radiologists show good correlation between 0.79-0.88. Residents show slightly lower inter observer agreement of 0.66 with each other and between 0.69-0.71 with experienced radiologists. Intra observer agreement was high with a correlation coefficient of 0.77. In 220 (18%), 707 (59%), 259 (21%) and 22 (2%) CXRs there was a 0, 1, two or three class-difference. In 594 (50%) CXRs the median scores of the residents and the radiologists were similar, in 578 (48%) and 36 (3%) CXRs there was a 1 and 2 class-difference. CONCLUSION Experienced and in-training radiologists demonstrate good inter and intra observer agreement in COVID-19 pneumonia severity classification. A higher percentage of disagreement was observed in moderate cases, which may affect training of AI algorithms. ADVANCES IN KNOWLEDGE Most AI algorithms are trained on data labeled by a single expert. This study shows that for COVID-19 X-ray severity classification there is significant variability and disagreement between radiologist and between residents.
{"title":"COVID-19 pneumonia chest radiographic severity score: Variability assessment among experienced and In-training radiologists and creation of a Multi-reader composite score database for artificial intelligence algorithm development.","authors":"M. van Assen, Mohammadreza Zandehshahvar, H. Maleki, Y. Kiarashi, T. Arleo, A. Stillman, Peter D Filev, A. Davarpanah, E. Berkowitz, S. Tigges, Scott J. Lee, B. Vey, A. Adibi, C. D. De Cecco","doi":"10.1259/bjr.20211028","DOIUrl":"https://doi.org/10.1259/bjr.20211028","url":null,"abstract":"OBJECTIVE\u0000The purpose was to evaluate reader variability between experienced and in-training radiologists of COVID-19 pneumonia severity on CXR, and to create a multi reader database suitable for AI development.\u0000\u0000\u0000METHODS\u0000In this study, CXRs from PCR positive COVID-19 patients were reviewed. Six experienced cardiothoracic radiologists and two residents classified each CXR according to severity. One radiologist performed the classification twice to assess intra observer variability. Severity classification was assessed using a four-class system: normal(0), mild, moderate, and severe. A median severity score (Rad Med) for each CXR was determined for the six radiologists for development of a multi reader database (XCOMS). Kendal Tau correlation and percentage of disagreement were calculated to assess variability.\u0000\u0000\u0000RESULTS\u0000A total of 397 patients (1208 CXRs) were included (mean age, 60 years SD ±1), 189 men). Inter observer variability between the radiologists ranges between 0.67-0.78. Compared to the Rad Med score, the radiologists show good correlation between 0.79-0.88. Residents show slightly lower inter observer agreement of 0.66 with each other and between 0.69-0.71 with experienced radiologists. Intra observer agreement was high with a correlation coefficient of 0.77. In 220 (18%), 707 (59%), 259 (21%) and 22 (2%) CXRs there was a 0, 1, two or three class-difference. In 594 (50%) CXRs the median scores of the residents and the radiologists were similar, in 578 (48%) and 36 (3%) CXRs there was a 1 and 2 class-difference.\u0000\u0000\u0000CONCLUSION\u0000Experienced and in-training radiologists demonstrate good inter and intra observer agreement in COVID-19 pneumonia severity classification. A higher percentage of disagreement was observed in moderate cases, which may affect training of AI algorithms.\u0000\u0000\u0000ADVANCES IN KNOWLEDGE\u0000Most AI algorithms are trained on data labeled by a single expert. This study shows that for COVID-19 X-ray severity classification there is significant variability and disagreement between radiologist and between residents.","PeriodicalId":226783,"journal":{"name":"The British journal of radiology","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124645505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wan-liang Guo, Ansng Geng, C. Geng, Jian Wang, Y. Dai
OBJECTIVES The aim of this study was to establish an automatic classification model for chronic inflammation of the choledoch wall using deep learning with CT images in patients with pancreaticobiliary maljunction (PBM). METHODS CT images were obtained from 76 PBM patients, including 61 cases assigned to the training set and 15 cases assigned to the testing set. The region of interest (ROI) containing the choledochal lesion was extracted and segmented using the UNet ++network. The degree of severity of inflammation in the choledochal wall was initially classified using the ResNeSt network. The final classification result was determined per decision rules. Grad-CAM was used to explain the association between the classification basis of the network and clinical diagnosis. RESULTS Segmentation of the lesion on the common bile duct wall was roughly obtained with the UNet ++ segmentation model and the average value of Dice coefficient of the segmentation model in the testing set was 0.839 ± 0.150, which was verified through 5-fold cross-validation. Inflammation was initially classified with ResNeSt18, which resulted in accuracy = 0.756, sensitivity = 0.611, specificity = 0.852, precision = 0.733, and area under curve (AUC) = 0.711. The final classification sensitivity was 0.8. Grad-CAM revealed similar distribution of inflammation of the choledochal wall and verified the inflammation classification. CONCLUSIONS By combining the UNet ++network and the ResNeSt network, we achieved automatic classification of chronic inflammation of the choledoch in PBM patients and verified the robustness through cross-validation performed five times. This study provided an important basis for classification of inflammation severity of the choledoch in PBM patients. ADVANCES IN KNOWLEDGE We combined the UNet ++ network and the ResNeSt network to achieve automatic classification of chronic inflammation of the choledoch in PBM. These results provided an important basis for classification of choledochal inflammation in PBM and for surgical therapy.
{"title":"Combination of UNet++ and ResNeSt to classify chronic inflammation of the choledochal cystic wall in patients with pancreaticobiliary maljunction.","authors":"Wan-liang Guo, Ansng Geng, C. Geng, Jian Wang, Y. Dai","doi":"10.1259/bjr.20201189","DOIUrl":"https://doi.org/10.1259/bjr.20201189","url":null,"abstract":"OBJECTIVES\u0000The aim of this study was to establish an automatic classification model for chronic inflammation of the choledoch wall using deep learning with CT images in patients with pancreaticobiliary maljunction (PBM).\u0000\u0000\u0000METHODS\u0000CT images were obtained from 76 PBM patients, including 61 cases assigned to the training set and 15 cases assigned to the testing set. The region of interest (ROI) containing the choledochal lesion was extracted and segmented using the UNet ++network. The degree of severity of inflammation in the choledochal wall was initially classified using the ResNeSt network. The final classification result was determined per decision rules. Grad-CAM was used to explain the association between the classification basis of the network and clinical diagnosis.\u0000\u0000\u0000RESULTS\u0000Segmentation of the lesion on the common bile duct wall was roughly obtained with the UNet ++ segmentation model and the average value of Dice coefficient of the segmentation model in the testing set was 0.839 ± 0.150, which was verified through 5-fold cross-validation. Inflammation was initially classified with ResNeSt18, which resulted in accuracy = 0.756, sensitivity = 0.611, specificity = 0.852, precision = 0.733, and area under curve (AUC) = 0.711. The final classification sensitivity was 0.8. Grad-CAM revealed similar distribution of inflammation of the choledochal wall and verified the inflammation classification.\u0000\u0000\u0000CONCLUSIONS\u0000By combining the UNet ++network and the ResNeSt network, we achieved automatic classification of chronic inflammation of the choledoch in PBM patients and verified the robustness through cross-validation performed five times. This study provided an important basis for classification of inflammation severity of the choledoch in PBM patients.\u0000\u0000\u0000ADVANCES IN KNOWLEDGE\u0000We combined the UNet ++ network and the ResNeSt network to achieve automatic classification of chronic inflammation of the choledoch in PBM. These results provided an important basis for classification of choledochal inflammation in PBM and for surgical therapy.","PeriodicalId":226783,"journal":{"name":"The British journal of radiology","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117124200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daisuke Kawahara, Y. Murakami, Shigeyuki Tani, Y. Nagata
OBJECTIVES To propose deep learning (DL)-based predictive model for pathological complete response rate for resectable locally advanced esophageal squamous cell carcinoma (SCC) after neoadjuvant chemoradiotherapy (NCRT) with endoscopic images. METHODS AND MATERIAL This retrospective study analyzed 98 patients with locally advanced esophagus cancer treated by preoperative chemoradiotherapy followed by surgery from 2004 to 2016. The patient data were split into two sets: 72 patients for the training of models and 26 patients for testing of the model. Patients was classified into two groups with the LC (Group I: responder and Group II: non-responder). The scanned images were converted into joint photographic experts group (JPEG) format and resized to 150 × 150 pixels. The input image without imaging filter (w/o filter) and with Laplacian, Sobel, and wavelet imaging filters deep learning model to predict the pathological CR with a convolution neural network (CNN). The accuracy, sensitivity, and specificity, the area under the curve (AUC) of the receiver operating characteristic were evaluated. RESULTS The average of accuracy for the cross-validation was 0.64 for w/o filter, 0.69 for Laplacian filter, 0.71 for Sobel filter, and 0.81 for wavelet filter, respectively. The average of sensitivity for the cross-validation was 0.80 for w/o filter, 0.81 for Laplacian filter, 0.67 for Sobel filter, and 0.80 for wavelet filter, respectively. The average of specificity for the cross-validation was 0.37 for w/o filter, 0.55 for Laplacian filter, 0.68 for Sobel filter, and 0.81 for wavelet filter, respectively. From the ROC curve, the average AUC for the cross-validation was 0.58 for w/o filter, 0.67 for Laplacian filter, 0.73 for Sobel filter, and 0.83 for wavelet filter, respectively. CONCLUSIONS The current study proposed the improvement the accuracy of the DL-based prediction model with the imaging filters. With the imaging filters, the accuracy was significantly improved. The model can be supported to assist clinical oncologists to have a more accurate expectations of the treatment outcome. ADVANCES IN KNOWLEDGE The accuracy of the prediction for the local control after radiotherapy can improve with the input image with the imaging filter for deep learning.
{"title":"A prediction model for pathological findings after neoadjuvant chemoradiotherapy for resectable locally advanced esophageal squamous cell carcinoma based on endoscopic images using deep learning.","authors":"Daisuke Kawahara, Y. Murakami, Shigeyuki Tani, Y. Nagata","doi":"10.1259/bjr.20210934","DOIUrl":"https://doi.org/10.1259/bjr.20210934","url":null,"abstract":"OBJECTIVES\u0000To propose deep learning (DL)-based predictive model for pathological complete response rate for resectable locally advanced esophageal squamous cell carcinoma (SCC) after neoadjuvant chemoradiotherapy (NCRT) with endoscopic images.\u0000\u0000\u0000METHODS AND MATERIAL\u0000This retrospective study analyzed 98 patients with locally advanced esophagus cancer treated by preoperative chemoradiotherapy followed by surgery from 2004 to 2016. The patient data were split into two sets: 72 patients for the training of models and 26 patients for testing of the model. Patients was classified into two groups with the LC (Group I: responder and Group II: non-responder). The scanned images were converted into joint photographic experts group (JPEG) format and resized to 150 × 150 pixels. The input image without imaging filter (w/o filter) and with Laplacian, Sobel, and wavelet imaging filters deep learning model to predict the pathological CR with a convolution neural network (CNN). The accuracy, sensitivity, and specificity, the area under the curve (AUC) of the receiver operating characteristic were evaluated.\u0000\u0000\u0000RESULTS\u0000The average of accuracy for the cross-validation was 0.64 for w/o filter, 0.69 for Laplacian filter, 0.71 for Sobel filter, and 0.81 for wavelet filter, respectively. The average of sensitivity for the cross-validation was 0.80 for w/o filter, 0.81 for Laplacian filter, 0.67 for Sobel filter, and 0.80 for wavelet filter, respectively. The average of specificity for the cross-validation was 0.37 for w/o filter, 0.55 for Laplacian filter, 0.68 for Sobel filter, and 0.81 for wavelet filter, respectively. From the ROC curve, the average AUC for the cross-validation was 0.58 for w/o filter, 0.67 for Laplacian filter, 0.73 for Sobel filter, and 0.83 for wavelet filter, respectively.\u0000\u0000\u0000CONCLUSIONS\u0000The current study proposed the improvement the accuracy of the DL-based prediction model with the imaging filters. With the imaging filters, the accuracy was significantly improved. The model can be supported to assist clinical oncologists to have a more accurate expectations of the treatment outcome.\u0000\u0000\u0000ADVANCES IN KNOWLEDGE\u0000The accuracy of the prediction for the local control after radiotherapy can improve with the input image with the imaging filter for deep learning.","PeriodicalId":226783,"journal":{"name":"The British journal of radiology","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115627685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Ferro, F. Deodato, M. Ferro, G. Panza, M. Buwenge, D. Pezzulla, S. Cilla, M. Boccardi, C. Romano, A. Arcelli, S. Cammelli, A. Zamagni, A. Morganti, G. Macchia
OBJECTIVES To assess feasibility and safety of a SHort-course Accelerated RadiatiON therapy (SHARON) regimen, in the treatment of non-melanoma skin cancers in older patients. METHODS Old patients (age ≥80 years) with histological confirmed non-melanoma skin cancers were enrolled. The primary endpoint was to determine the maximum tolerated dose (MTD). Radiotherapy regimen was based on the delivery of four radiotherapy fractions (5 Gy per fraction) with a bd fractionation in two consecutive days. Three different level of dose were administered: 20 Gy (one cycle), 40 Gy (two cycles) and 60 Gy (three cycles). RESULTS Thirty patients (median age: 91.0 years; range: 80-96) were included in this analysis. Among fourteen patients who completed the one cycle, only one (7%) experimented acute G4 skin toxicity. Twelve patients reported an improvement or resolution of baseline symptoms (overall palliative response rate: 85.8%). Nine and seven patients underwent to two and three RT cycles, respectively: of these, no G3 toxicities were recorded. The overall response rate was 100% when three cycles were delivered. The overall six-month symptom-free survival was 78.7 and 77.8% in patients treated with one course and more courses, respectively. CONCLUSIONS Short-course accelerated radiotherapy in older patients with non-melanoma skin cancers is well tolerated. High doses seem to be more effective in terms of response rate. ADVANCES IN KNOWLEDGE This approach could represent an option for older adults with nMSC, being both palliative (one course) or potentially curative (more courses) in the aim, accordingly to the patient's condition.
{"title":"A SHort course accelerated radiotherapy (SHARON) dose-escalation trial in older adults head and neck non-melanoma skin cancer.","authors":"M. Ferro, F. Deodato, M. Ferro, G. Panza, M. Buwenge, D. Pezzulla, S. Cilla, M. Boccardi, C. Romano, A. Arcelli, S. Cammelli, A. Zamagni, A. Morganti, G. Macchia","doi":"10.1259/bjr.20211347","DOIUrl":"https://doi.org/10.1259/bjr.20211347","url":null,"abstract":"OBJECTIVES\u0000To assess feasibility and safety of a SHort-course Accelerated RadiatiON therapy (SHARON) regimen, in the treatment of non-melanoma skin cancers in older patients.\u0000\u0000\u0000METHODS\u0000Old patients (age ≥80 years) with histological confirmed non-melanoma skin cancers were enrolled. The primary endpoint was to determine the maximum tolerated dose (MTD). Radiotherapy regimen was based on the delivery of four radiotherapy fractions (5 Gy per fraction) with a bd fractionation in two consecutive days. Three different level of dose were administered: 20 Gy (one cycle), 40 Gy (two cycles) and 60 Gy (three cycles).\u0000\u0000\u0000RESULTS\u0000Thirty patients (median age: 91.0 years; range: 80-96) were included in this analysis. Among fourteen patients who completed the one cycle, only one (7%) experimented acute G4 skin toxicity. Twelve patients reported an improvement or resolution of baseline symptoms (overall palliative response rate: 85.8%). Nine and seven patients underwent to two and three RT cycles, respectively: of these, no G3 toxicities were recorded. The overall response rate was 100% when three cycles were delivered. The overall six-month symptom-free survival was 78.7 and 77.8% in patients treated with one course and more courses, respectively.\u0000\u0000\u0000CONCLUSIONS\u0000Short-course accelerated radiotherapy in older patients with non-melanoma skin cancers is well tolerated. High doses seem to be more effective in terms of response rate.\u0000\u0000\u0000ADVANCES IN KNOWLEDGE\u0000This approach could represent an option for older adults with nMSC, being both palliative (one course) or potentially curative (more courses) in the aim, accordingly to the patient's condition.","PeriodicalId":226783,"journal":{"name":"The British journal of radiology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125266239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nuclear Medicine therapy has reached a critical juncture with an unprecedented number of patients being treated and an extensive list of new radiopharmaceuticals under development. Since the early applications of these treatments dosimetry has played a vital role in their development, in both aiding optimisation and enhancing safety and efficacy. To inform the future direction of this field it is useful to reflect on the scientific and technological advances that have occurred since those early uses. In this review we explore how dosimetry has evolved over the years and discuss why such initiatives were conceived and the importance of maintaining standards within our practise. Specific milestones and landmark publications are highlighted and a thematic review and significant outcomes during each decade are presented.
{"title":"Milestones in dosimetry for nuclear medicine therapy.","authors":"J. Gear","doi":"10.1259/bjr.20220056","DOIUrl":"https://doi.org/10.1259/bjr.20220056","url":null,"abstract":"Nuclear Medicine therapy has reached a critical juncture with an unprecedented number of patients being treated and an extensive list of new radiopharmaceuticals under development. Since the early applications of these treatments dosimetry has played a vital role in their development, in both aiding optimisation and enhancing safety and efficacy. To inform the future direction of this field it is useful to reflect on the scientific and technological advances that have occurred since those early uses. In this review we explore how dosimetry has evolved over the years and discuss why such initiatives were conceived and the importance of maintaining standards within our practise. Specific milestones and landmark publications are highlighted and a thematic review and significant outcomes during each decade are presented.","PeriodicalId":226783,"journal":{"name":"The British journal of radiology","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128287076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arterial spin labeling (ASL) is a powerful noncontrast MRI technique for evaluation of cerebral blood flow (CBF). A key parameter in single-delay ASL is the choice of postlabel delay (PLD), which refers to the timing between the labeling of arterial free water and measurement of flow into the brain. Multidelay ASL (MDASL) utilizes several PLDs to improve the accuracy of CBF calculations using arterial transit time (ATT) correction. This approach is particularly helpful in situations where ATT is unknown, including young subjects and slow-flow conditions. In this article, we discuss the technical considerations for MDASL, including labeling techniques, quantitative metrics, and technical artifacts. We then provide a practical summary of key clinical applications with real-life imaging examples in the pediatric brain, including stroke, vasculopathy, hypoxic-ischemic injury, epilepsy, migraine, tumor, infection, and metabolic disease.
{"title":"Multidelay ASL of the pediatric brain.","authors":"X. Golay, Mai‐Lan Ho","doi":"10.1259/bjr.20220034","DOIUrl":"https://doi.org/10.1259/bjr.20220034","url":null,"abstract":"Arterial spin labeling (ASL) is a powerful noncontrast MRI technique for evaluation of cerebral blood flow (CBF). A key parameter in single-delay ASL is the choice of postlabel delay (PLD), which refers to the timing between the labeling of arterial free water and measurement of flow into the brain. Multidelay ASL (MDASL) utilizes several PLDs to improve the accuracy of CBF calculations using arterial transit time (ATT) correction. This approach is particularly helpful in situations where ATT is unknown, including young subjects and slow-flow conditions. In this article, we discuss the technical considerations for MDASL, including labeling techniques, quantitative metrics, and technical artifacts. We then provide a practical summary of key clinical applications with real-life imaging examples in the pediatric brain, including stroke, vasculopathy, hypoxic-ischemic injury, epilepsy, migraine, tumor, infection, and metabolic disease.","PeriodicalId":226783,"journal":{"name":"The British journal of radiology","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127213067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Bellini, G. Bicchierai, F. Amato, Elena Savi, D. De Benedetto, F. Di Naro, C. Boeri, E. Vanzi, V. Miele, J. Nori
OBJECTIVES To compare second-look US with second-look DBT in the detection of additional lesions (ALs) with presurgical CESM. METHODS We retrospectively included 121 women with 128 ALs from patients who underwent CESM for presurgical staging at our centre from September 2016 to December 2018. These ALs underwent SL-US and a retrospective review of DBT (SL-DBT) performed 1-3 weeks prior to CESM to evaluate the performance of each technique individually and in combination. ALs in CESM images were evaluated according to enhancement type (focus, mass, or non-mass), size (<10 mm or >10 mm) and level of suspicion (BI-RADS 2, 3, four or 5). Our gold standard was post-biopsy histology, post-surgical specimen or >24 month negative follow-up. McNemar's test was used for the statistical analysis. RESULTS Out of the 128 Als, an imaging correlate was found for 71 (55.5 %,) with US, 79 (61.7%) with DBT, 53 (41.4 %) with DBT and US, and 97 (75.8%) with US and/or DBT. SL-DBT demonstrated a higher detection rate vs SL-US in non-mass enhancement (NME) pattern (p:0.0325) and DCIS histological type (p:0.0081). Adding SL-DBT improved the performance vs SL-US alone in the overall sample (p:<0.0001) and in every subcategory identified; adding SL-US to SL-DBT improved the detectability of ALs in the overall sample and in every category except for NME (p:0.0833), foci (p:0.0833) and B3 lesions (p:0.3173). CONCLUSIONS Combined second-look imaging (SL-DBT +SL US) for CESM ALs is superior to SL-DBT alone and SL-US alone. In B3 lesions, NME, and foci, the analysis of a larger sample could determine whether adding SL-US to SL-DBT is necessary or not. ADVANCES IN KNOWLEDGE Thanks to its high sensitivity, CESM is a useful tool in presurgical staging to detect the extent of the disease burden and identify ALs not detected with conventional imaging. Since CESM-guided biopsy systems are still scarcely available in clinical practice, it is necessary to look for other approaches to histologically characterize ALs detected with CESM. In our study, combined second-look imaging (SL-DBT +SL US) showed better performance in terms of detectability of ALs, than either SL-DBT or SL-US alone, and allowed us to identify 91.2% of ALs that turned out to be malignant at final histology; for the remaining 8.8% it was still necessary to perform MRI or MRI-guided biopsy. However, this issue could be solved once CESM-guided biopsies spread in clinical practice. SL-DBT demonstrated a higher detection rate than SL-US in NME and DCIS histology.
{"title":"Comparison between second-look ultrasound and second-look digital breast tomosynthesis in the detection of additional lesions with presurgical CESM.","authors":"C. Bellini, G. Bicchierai, F. Amato, Elena Savi, D. De Benedetto, F. Di Naro, C. Boeri, E. Vanzi, V. Miele, J. Nori","doi":"10.1259/bjr.20210927","DOIUrl":"https://doi.org/10.1259/bjr.20210927","url":null,"abstract":"OBJECTIVES\u0000To compare second-look US with second-look DBT in the detection of additional lesions (ALs) with presurgical CESM.\u0000\u0000\u0000METHODS\u0000We retrospectively included 121 women with 128 ALs from patients who underwent CESM for presurgical staging at our centre from September 2016 to December 2018. These ALs underwent SL-US and a retrospective review of DBT (SL-DBT) performed 1-3 weeks prior to CESM to evaluate the performance of each technique individually and in combination. ALs in CESM images were evaluated according to enhancement type (focus, mass, or non-mass), size (<10 mm or >10 mm) and level of suspicion (BI-RADS 2, 3, four or 5). Our gold standard was post-biopsy histology, post-surgical specimen or >24 month negative follow-up. McNemar's test was used for the statistical analysis.\u0000\u0000\u0000RESULTS\u0000Out of the 128 Als, an imaging correlate was found for 71 (55.5 %,) with US, 79 (61.7%) with DBT, 53 (41.4 %) with DBT and US, and 97 (75.8%) with US and/or DBT. SL-DBT demonstrated a higher detection rate vs SL-US in non-mass enhancement (NME) pattern (p:0.0325) and DCIS histological type (p:0.0081). Adding SL-DBT improved the performance vs SL-US alone in the overall sample (p:<0.0001) and in every subcategory identified; adding SL-US to SL-DBT improved the detectability of ALs in the overall sample and in every category except for NME (p:0.0833), foci (p:0.0833) and B3 lesions (p:0.3173).\u0000\u0000\u0000CONCLUSIONS\u0000Combined second-look imaging (SL-DBT +SL US) for CESM ALs is superior to SL-DBT alone and SL-US alone. In B3 lesions, NME, and foci, the analysis of a larger sample could determine whether adding SL-US to SL-DBT is necessary or not.\u0000\u0000\u0000ADVANCES IN KNOWLEDGE\u0000Thanks to its high sensitivity, CESM is a useful tool in presurgical staging to detect the extent of the disease burden and identify ALs not detected with conventional imaging. Since CESM-guided biopsy systems are still scarcely available in clinical practice, it is necessary to look for other approaches to histologically characterize ALs detected with CESM. In our study, combined second-look imaging (SL-DBT +SL US) showed better performance in terms of detectability of ALs, than either SL-DBT or SL-US alone, and allowed us to identify 91.2% of ALs that turned out to be malignant at final histology; for the remaining 8.8% it was still necessary to perform MRI or MRI-guided biopsy. However, this issue could be solved once CESM-guided biopsies spread in clinical practice. SL-DBT demonstrated a higher detection rate than SL-US in NME and DCIS histology.","PeriodicalId":226783,"journal":{"name":"The British journal of radiology","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123038900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yasuhiro Fujiwara, Shota Ishida, Yuki Matta, M. Kanamoto, H. Kimura
OBJECTIVES Parkinson's disease is a neurodegenerative disorder caused by neuronal cell loss in the substantia nigra pars compacta (SNpc). We aimed to perform atlas-based relaxometry using an anatomical SNpc atlas and obtain baseline values of SNpc regions in healthy volunteers. METHODS Neuromelanin (NM)-sensitive imaging of the midbrain and whole-brain 3D T1-weighted images of 27 healthy volunteers (20 males; aged 36.3 ± 11.5 years) were obtained. An anatomical SNpc atlas was created using NM-sensitive images in standard space, and divided into medial (MG), dorsal (DG), and ventrolateral (VG) groups. Proton density (PD), T1, and T2 values in these regions were obtained using quantitative magnetic resonance imaging (MRI). The relationships between PD, T1, and T2 values in each SNpc region and age were evaluated. RESULTS The VG PD value was significantly higher than the MG and DG values. MG, DG, and VG T1 values were significantly different, whereas the T2 value of the MG was significantly lower than the DG and VG values. Moreover, a significant negative correlation between PD and T1 values of the MG and age was observed. CONCLUSION The PD, T1, and T2 values of the SNpc regions measured in standard space using an anatomical atlas can be used as baseline values. PD and T1 values of the SNpc regions may be associated with NM concentrations. ADVANCES IN KNOWLEDGE An anatomical SNpc atlas was created using NM-sensitive MRI and can be used for the quantitative evaluation of sub segments of the SNpc in standard space.
{"title":"Atlas-based relaxometry and subsegment analysis of the substantia nigra pars compacta using quantitative MRI: A healthy volunteer study.","authors":"Yasuhiro Fujiwara, Shota Ishida, Yuki Matta, M. Kanamoto, H. Kimura","doi":"10.1259/bjr.20210572","DOIUrl":"https://doi.org/10.1259/bjr.20210572","url":null,"abstract":"OBJECTIVES\u0000Parkinson's disease is a neurodegenerative disorder caused by neuronal cell loss in the substantia nigra pars compacta (SNpc). We aimed to perform atlas-based relaxometry using an anatomical SNpc atlas and obtain baseline values of SNpc regions in healthy volunteers.\u0000\u0000\u0000METHODS\u0000Neuromelanin (NM)-sensitive imaging of the midbrain and whole-brain 3D T1-weighted images of 27 healthy volunteers (20 males; aged 36.3 ± 11.5 years) were obtained. An anatomical SNpc atlas was created using NM-sensitive images in standard space, and divided into medial (MG), dorsal (DG), and ventrolateral (VG) groups. Proton density (PD), T1, and T2 values in these regions were obtained using quantitative magnetic resonance imaging (MRI). The relationships between PD, T1, and T2 values in each SNpc region and age were evaluated.\u0000\u0000\u0000RESULTS\u0000The VG PD value was significantly higher than the MG and DG values. MG, DG, and VG T1 values were significantly different, whereas the T2 value of the MG was significantly lower than the DG and VG values. Moreover, a significant negative correlation between PD and T1 values of the MG and age was observed.\u0000\u0000\u0000CONCLUSION\u0000The PD, T1, and T2 values of the SNpc regions measured in standard space using an anatomical atlas can be used as baseline values. PD and T1 values of the SNpc regions may be associated with NM concentrations.\u0000\u0000\u0000ADVANCES IN KNOWLEDGE\u0000An anatomical SNpc atlas was created using NM-sensitive MRI and can be used for the quantitative evaluation of sub segments of the SNpc in standard space.","PeriodicalId":226783,"journal":{"name":"The British journal of radiology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132491059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
OBJECTIVES Several preoperative parameters have been studied to estimate stone-free rate (SFR) following RIRS procedures. The objective of this study was to evaluate the effects of stone density on surgical outcomes of RIRS. METHODS This retrospective study included 30 stone-free patients (Group SF) and 30 patients with residual fragments (Group RF). Patients' age and gender, laterality, non-contrast computed tomography findings, including size and density of the kidney stones, infundibular pelvic angle (IPA), operational time, and postoperative pain were recorded and compared between the two groups. The stone density was measured by free hand region of interest (ROI) determination coincident with the stone borders and expressed as Hounsfield Units (HU). RESULTS The rate of single stones was significantly higher in Group SF compared to Group RF (p < 0.001). The mean stone size was found as 11.93 ± 7.81 mm in Group SF and 16.27 ± 7.29 mm in Group RF with the difference being statistically significant (p < 0.001). The mean infundibular pelvic angle (IPA) was 53.87 degrees in Group SF and 50.33 degrees in Group RF. The mean density was measured as 748.17 ± 318.14 HU in Group SF and 945.90 ± 345.30 HU in Group RF. The mean stone density was statistically significantly higher in patients with residual fragments compared to the stone-free patients (p < 0.001). CONCLUSIONS This study revealed that stone density as measured as Hounsfield Units (HU) affects the treatment outcomes with retrograde intrarenal surgery (RIRS) procedure and the mean density is significantly higher in patients with residual stone fragments. ADVANCES IN KNOWLEDGE Studies about the effects of Hounsfield units on stone-free rate are limited in the literature. Stone density affects the treatment outcomes with retrograde intrarenal surgery (RIRS) procedure and the mean density is significantly higher in patients with residual stone fragments.
{"title":"The effects of stone density on surgical outcomes of retrograde intrarenal stone surgery.","authors":"S. Aksoy, B. Çakıroğlu, Tuncay Taş, I. Yurdaışık","doi":"10.1259/bjr.20220229","DOIUrl":"https://doi.org/10.1259/bjr.20220229","url":null,"abstract":"OBJECTIVES\u0000Several preoperative parameters have been studied to estimate stone-free rate (SFR) following RIRS procedures. The objective of this study was to evaluate the effects of stone density on surgical outcomes of RIRS.\u0000\u0000\u0000METHODS\u0000This retrospective study included 30 stone-free patients (Group SF) and 30 patients with residual fragments (Group RF). Patients' age and gender, laterality, non-contrast computed tomography findings, including size and density of the kidney stones, infundibular pelvic angle (IPA), operational time, and postoperative pain were recorded and compared between the two groups. The stone density was measured by free hand region of interest (ROI) determination coincident with the stone borders and expressed as Hounsfield Units (HU).\u0000\u0000\u0000RESULTS\u0000The rate of single stones was significantly higher in Group SF compared to Group RF (p < 0.001). The mean stone size was found as 11.93 ± 7.81 mm in Group SF and 16.27 ± 7.29 mm in Group RF with the difference being statistically significant (p < 0.001). The mean infundibular pelvic angle (IPA) was 53.87 degrees in Group SF and 50.33 degrees in Group RF. The mean density was measured as 748.17 ± 318.14 HU in Group SF and 945.90 ± 345.30 HU in Group RF. The mean stone density was statistically significantly higher in patients with residual fragments compared to the stone-free patients (p < 0.001).\u0000\u0000\u0000CONCLUSIONS\u0000This study revealed that stone density as measured as Hounsfield Units (HU) affects the treatment outcomes with retrograde intrarenal surgery (RIRS) procedure and the mean density is significantly higher in patients with residual stone fragments.\u0000\u0000\u0000ADVANCES IN KNOWLEDGE\u0000Studies about the effects of Hounsfield units on stone-free rate are limited in the literature. Stone density affects the treatment outcomes with retrograde intrarenal surgery (RIRS) procedure and the mean density is significantly higher in patients with residual stone fragments.","PeriodicalId":226783,"journal":{"name":"The British journal of radiology","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114421480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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