{"title":"Effect of deep learning reconstruction on the assessment of pancreatic cystic lesions using computed tomography.","authors":"Jun Kanzawa, Koichiro Yasaka, Yuji Ohizumi, Yuichi Morita, Mariko Kurokawa, Osamu Abe","doi":"10.1007/s12194-024-00834-6","DOIUrl":"10.1007/s12194-024-00834-6","url":null,"abstract":"<p><p>This study aimed to compare the image quality and detection performance of pancreatic cystic lesions between computed tomography (CT) images reconstructed by deep learning reconstruction (DLR) and filtered back projection (FBP). This retrospective study included 54 patients (mean age: 67.7 ± 13.1) who underwent contrast-enhanced CT from May 2023 to August 2023. Among eligible patients, 30 and 24 were positive and negative for pancreatic cystic lesions, respectively. DLR and FBP were used to reconstruct portal venous phase images. Objective image quality analyses calculated quantitative image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) using regions of interest on the abdominal aorta, pancreatic lesion, and pancreatic parenchyma. Three blinded radiologists performed subjective image quality assessment and lesion detection tests. Lesion depiction, normal structure illustration, subjective image noise, and overall image quality were utilized as subjective image quality indicators. DLR significantly reduced quantitative image noise compared with FBP (p < 0.001). SNR and CNR were significantly improved in DLR compared with FBP (p < 0.001). Three radiologists rated significantly higher scores for DLR in all subjective image quality indicators (p ≤ 0.029). Performance of DLR and FBP were comparable in lesion detection, with no statistically significant differences in the area under the receiver operating characteristic curve, sensitivity, specificity and accuracy. DLR reduced image noise and improved image quality with a clearer depiction of pancreatic structures. These improvements may have a positive effect on evaluating pancreatic cystic lesions, which can contribute to appropriate management of these lesions.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"827-833"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11579065/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141989183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Puspen Chakraborty, Hidetoshi Saitoh, Yuta Miyake, Tenyoh Suzuki, Weishan Chang
{"title":"Estimation of the lateral variation of photon beam energy spectra using the percentage depth dose reconstruction method.","authors":"Puspen Chakraborty, Hidetoshi Saitoh, Yuta Miyake, Tenyoh Suzuki, Weishan Chang","doi":"10.1007/s12194-024-00835-5","DOIUrl":"10.1007/s12194-024-00835-5","url":null,"abstract":"<p><p>In photon-collapsed cone convolution (pCCC) algorithm of the Monaco treatment planning system (TPS), the central-axis energy spectrum is assumed constant throughout the entire irradiation area. To consider lateral variations, an off-axis softening factor is applied to attenuation coefficients during the total energy released per unit mass calculation. We evaluated this method through comparison studies of percentage depth doses (PDDs) and off-axis ratios (OARs) calculated by Monaco and measured for a 6 MV photon beam at various off-axis angles and depths. Significant differences were observed, with relative differences exceeding ± 1%. Therefore, this method may not accurately represent lateral variations of energy spectra. We propose directly implementing energy spectra on both central-axis and off-axis to improve dose calculation accuracy for large field. To this end, we introduce reconstruction of PDDs from monoenergetic depth doses (MDDs) along off-axis angles, thereby estimating energy spectra as functions of radial distance. This method derives energy spectra quickly without significantly increasing the beam modeling time. MDDs were computed through Monte Carlo simulations (DOSRZnrc). The variances between reconstructed and measured PDDs were minimized using the generalized-reduced-gradient method to optimize energy spectra. Reconstructed PDDs along off-axis angles of 0°, 1.15°, 2.29°, 3.43°, 4.57°, 5.71°, 6.84°, 7.97°, 9.09°, 10.2° to estimate energy spectra at radial distances of 0-18 cm in 2 cm increments and OARs calculated using estimated energy spectra at 5, 10, and 20 cm depths, well agreed with measurement (relative differences within ± 0.5%). In conclusion, our proposed method accurately estimates lateral energy spectrum variation, thereby improving dose calculation accuracy of pCCC algorithm.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"834-842"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11579137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142141310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimum delineation of skin structure for dose calculation with the linear Boltzmann transport equation algorithm in radiotherapy treatment planning.","authors":"Keisuke Hamada, Toshioh Fujibuchi, Hiroyuki Arakawa","doi":"10.1007/s12194-024-00840-8","DOIUrl":"10.1007/s12194-024-00840-8","url":null,"abstract":"<p><p>This study investigated the effectiveness of placing skin-ring structures to enhance the precision of skin dose calculations in patients who had undergone head and neck volumetric modulated arc therapy using the Acuros XB algorithm. The skin-ring structures in question were positioned 2 mm below the skin surface (skin A) and 1 mm above and below the skin surface (skin B) within the treatment-planning system. These structures were then tested on both acrylic cylindrical and anthropomorphic phantoms and compared with the Gafchromic EBT3 film (EBT3). The results revealed that the maximum dose differences between skins A and B for the cylindrical and anthropomorphic phantoms were approximately 12% and 2%, respectively. In patients 1 and 2, the dose differences between skins A and B were 9.2% and 8.2%, respectively. Ultimately, demonstrated that the skin-dose calculation accuracy of skin B was within 2% and did not impact the deep organs.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"938-946"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142156303","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}
{"title":"Single-point macromolecular proton fraction mapping using a 0.3 T permanent magnet MRI system: phantom and healthy volunteer study.","authors":"Yasuhiro Fujiwara, Shoma Eitoku, Nobutaka Sakae, Takahisa Izumi, Hiroyuki Kumazoe, Mika Kitajima","doi":"10.1007/s12194-024-00843-5","DOIUrl":"10.1007/s12194-024-00843-5","url":null,"abstract":"<p><p>In a 0.3 T permanent-magnet magnetic resonance imaging (MRI) system, quantifying myelin content is challenging owing to long imaging times and low signal-to-noise ratio. macromolecular proton fraction (MPF) offers a quantitative assessment of myelin in the nervous system. We aimed to demonstrate the practical feasibility of MPF mapping in the brain using a 0.3 T MRI. Both 0.3 T and 3.0 T MRI systems were used. The MPF-mapping protocol used a standard 3D fast spoiled gradient-echo sequence based on the single-point reference method. Proton density, T<sub>1</sub>, and magnetization transfer-weighted images were obtained from a protein phantom at 0.3 T and 3.0 T to calculate MPF maps. MPF was measured in all phantom sections to assess its relationship to protein concentration. We acquired MPF maps for 16 and 8 healthy individuals at 0.3 T and 3.0 T, respectively, measuring MPF in nine brain tissues. Differences in MPF between 0.3 T and 3.0 T, and between 0.3 T and previously reported MPF at 0.5 T, were investigated. Pearson's correlation coefficient between protein concentration and MPF at 0.3 T and 3.0 T was 0.92 and 0.90, respectively. The 0.3 T MPF of brain tissue strongly correlated with 3.0 T MPF and literature values measured at 0.5 T. The absolute mean differences in MPF between 0.3 T and 0.5 T were 0.42% and 1.70% in white and gray matter, respectively. Single-point MPF mapping using 0.3 T permanent-magnet MRI can effectively assess myelin content in neural tissue.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"869-877"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142298280","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}
{"title":"An updated overview of radiomics-based artificial intelligence (AI) methods in breast cancer screening and diagnosis.","authors":"Reza Elahi, Mahdis Nazari","doi":"10.1007/s12194-024-00842-6","DOIUrl":"10.1007/s12194-024-00842-6","url":null,"abstract":"<p><p>Current imaging methods for diagnosing breast cancer (BC) are associated with limited sensitivity and specificity and modest positive predictive power. The recent progress in image analysis using artificial intelligence (AI) has created great promise to improve BC diagnosis and subtype differentiation. In this case, novel quantitative computational methods, such as radiomics, have been developed to enhance the sensitivity and specificity of early BC diagnosis and classification. The potential of radiomics in improving the diagnostic efficacy of imaging studies has been shown in several studies. In this review article, we discuss the radiomics workflow and current handcrafted radiomics methods in the diagnosis and classification of BC based on the most recent studies on different imaging modalities, e.g., MRI, mammography, contrast-enhanced spectral mammography (CESM), ultrasound imaging, and digital breast tumosynthesis (DBT). We also discuss current challenges and potential strategies to improve the specificity and sensitivity of radiomics in breast cancer to help achieve a higher level of BC classification and diagnosis in the clinical setting. The growing field of AI incorporation with imaging information has opened a great opportunity to provide a higher level of care for BC patients.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"795-818"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142298276","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}
{"title":"Effect of frame rate on image quality in cardiology evaluated using an indirect conversion dynamic flat-panel detector.","authors":"Akira Hasegawa, Yohan Kondo","doi":"10.1007/s12194-024-00845-3","DOIUrl":"10.1007/s12194-024-00845-3","url":null,"abstract":"<p><p>To verify the effect of the frame rate on image quality in cardiology, we used an indirect conversion dynamic flat-panel detector (FPD). We quantified the input-output characteristics, and determined the modulation transfer function (MTF) and normalized noise power spectrum (NNPS) of the equipment used in cardiology at 7.5, 10, 15, and 30 frames per second (fps). We also calculated the noise power spectrum for still images and videos at all frame rates and obtained the image lag correction factor r. The input-output characteristics and the MTF agreed even when the frame rate was varied. The NNPS tended to decrease uniformly as a function of frequency at increasing frame rates. The factor r decreased as a function of the frame rate, and its minimum value was 30 fps. Our results suggest that high-frame-rate imaging in cardiology using indirect conversion dynamic FPDs is affected by image lag.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"947-954"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142298278","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}
Mageshraja Kannan, Sathiyan Saminathan, Varatharaj Chandraraj, B Shwetha, D Gowtham Raj, K M Ganesh
{"title":"Evaluation of patient-specific quality assurance for fractionated stereotactic treatment plans with 6 and 10MV photon beams in beam-matched linacs.","authors":"Mageshraja Kannan, Sathiyan Saminathan, Varatharaj Chandraraj, B Shwetha, D Gowtham Raj, K M Ganesh","doi":"10.1007/s12194-024-00848-0","DOIUrl":"10.1007/s12194-024-00848-0","url":null,"abstract":"<p><p>Beam-matched linear accelerators (LA's) require accurate and precise dosimetry for fractionated stereotactic treatment. In this study, the beam data were validated by comparing the three-beam-matched LA's measured data and the vendor reference data. Upon its validation, the accuracy of the volumetric dose delivery for eighty patient-specific fractionated stereotactic treatment plans was evaluated. Measurements of the percentage depth dose (PDD), beam profiles, output factors (OFs), absolute output, and dynamic multi-leaf collimator (MLC) transmission factors for 6 MV and 10 MV flattening filter (FF) and flattening filter-free (FFF) photon beams were obtained from three-beam-matched LA's. The patient-specific quality assurance evaluation for all eighty plans was performed using PTW Octavius 1000 SRS™ array detectors for two-dimensional (2D) fluence measurement. The following 2D gamma passing criteria were used: 1%/1 mm, 2%/1 mm, 1%/2 mm, 2%/2 mm and 3%/2 mm. In all three LA's, gamma analysis for PDD and profile were above 97% with gamma criteria of 1%/1 mm. The differences OFs, absolute output, and dynamic MLC transmission factors were less than ± 1% of base value. For all eighty cases, the median passing rates on the three LA's were above 76%, 88%, 92%, 96%, and 98% for the above-mentioned gamma criteria of the three LA's. The beam-matched LA's showed good agreement between the measured and treatment planning system (TPS) calculated values for fractionated stereotactic VMAT plans with 6 MV and 10 MV (FF and FFF) photon beams. Patients can be shifted and treated on any beam-matched linac without the need of re-planning.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"896-906"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373206","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}
{"title":"Parameter optimisation for image acquisition and stacking in carbon dioxide digital subtraction angiography.","authors":"Kazuya Kakuta, Koichi Chida","doi":"10.1007/s12194-024-00841-7","DOIUrl":"10.1007/s12194-024-00841-7","url":null,"abstract":"<p><p>The aim of this study was to optimise the vessel angle as well as the stack number from the profiles of carbon dioxide digital subtraction angiography (CO<sub>2</sub>-DSA) images of a water phantom containing an artificial vessel tilted at different angles which imitate arteries in the body. The artificial vessel was tilted at 0°, 15°, and 30° relative to the horizontal axis with its centre as the pivot point, and CO<sub>2</sub>-DSA images were acquired at each vessel tilt angle. The maximum opacity method was used to stack up to four images of the next frame one by one. The signal-to-noise ratio (SNR) was determined from the profile curves. The Wilcoxon rank sum test was used to evaluate whether the profile curve and SNR differed depending on the vessel tilt angle or stack number, and a p-value of less than 0.05 was considered statistically significant. Images acquired at 0° had a significantly lower SNR than images acquired at 15° (p = 0.10). When the vessel angle was 30°, the profile curves were significantly improved (p < 0.05) when two or more images were stacked over the original image. Images with a good SNR were acquired at the vessel tilt angle of 15°, and the shape of the profile curve was improved when two or more images were stacked on the original image. This study demonstrates that the quality of images acquired using CO<sub>2</sub>-DSA can be significantly improved through parameter optimisation for image acquisition and post-processing.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"862-868"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142156304","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}
{"title":"A novel internal target volume definition based on velocity and time of respiratory target motion for external beam radiotherapy.","authors":"Masashi Yamanaka, Teiji Nishio, Kohei Iwabuchi, Hironori Nagata","doi":"10.1007/s12194-024-00837-3","DOIUrl":"10.1007/s12194-024-00837-3","url":null,"abstract":"<p><p>This study aimed to develop a novel internal target volume (ITV) definition for respiratory motion targets, considering target motion velocity and time. The proposed ITV was evaluated in respiratory-gated radiotherapy. An ITV modified with target motion velocity and time (ITVvt) was defined as an ITV that includes a target motion based on target motion velocity and time. The target motion velocity was calculated using four-dimensional computed tomography (4DCT) images. The ITVvts were created from phantom and clinical 4DCT images. The phantom 4DCT images were acquired using a solid phantom that moved with a sinusoidal waveform (peak-to-peak amplitudes of 10 and 20 mm and cycles of 2-6 s). The clinical 4DCT images were obtained from eight lung cancer cases. In respiratory-gated radiotherapy, the ITVvt was compared with conventional ITVs for beam times of 0.5-2 s within the gating window. The conventional ITV was created by adding a uniform margin as the maximum motion within the gating window. In the phantom images, the maximum volume difference between the ITVvt and conventional ITV was -81.9%. In the clinical images, the maximum volume difference was -53.6%. Shorter respiratory cycles and longer BTs resulted in smaller ITVvt compared with the conventional ITV. Therefore, the proposed ITVvt plan could be used to reduce treatment volumes and doses to normal tissues.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"843-853"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142298275","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}
Hisamichi Takagi, Ken Takeda, Noriyuki Kadoya, Koki Inoue, Shiki Endo, Noriyoshi Takahashi, Takaya Yamamoto, Rei Umezawa, Keiichi Jingu
{"title":"Development of deep learning-based novel auto-segmentation for the prostatic urethra on planning CT images for prostate cancer radiotherapy.","authors":"Hisamichi Takagi, Ken Takeda, Noriyuki Kadoya, Koki Inoue, Shiki Endo, Noriyoshi Takahashi, Takaya Yamamoto, Rei Umezawa, Keiichi Jingu","doi":"10.1007/s12194-024-00832-8","DOIUrl":"10.1007/s12194-024-00832-8","url":null,"abstract":"<p><p>Urinary toxicities are one of the serious complications of radiotherapy for prostate cancer, and dose-volume histogram of prostatic urethra has been associated with such toxicities in previous reports. Previous research has focused on estimating the prostatic urethra, which is difficult to delineate in CT images; however, these studies, which are limited in number, mainly focused on cases undergoing brachytherapy uses low-dose-rate sources and do not involve external beam radiation therapy (EBRT). In this study, we aimed to develop a deep learning-based method of determining the position of the prostatic urethra in patients eligible for EBRT. We used contour data from 430 patients with localized prostate cancer. In all cases, a urethral catheter was placed when planning CT to identify the prostatic urethra. We used 2D and 3D U-Net segmentation models. The input images included the bladder and prostate, while the output images focused on the prostatic urethra. The 2D model determined the prostate's position based on results from both coronal and sagittal directions. Evaluation metrics included the average distance between centerlines. The average centerline distances for the 2D and 3D models were 2.07 ± 0.87 mm and 2.05 ± 0.92 mm, respectively. Increasing the number of cases while maintaining equivalent accuracy as we did in this study suggests the potential for high generalization performance and the feasibility of using deep learning technology for estimating the position of the prostatic urethra.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"819-826"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11579160/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141983522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}