Medical physics最新文献

{"title":"Development of a proton CT imaging system using scintillator-based range detection","authors":"Meiqi Liu, Yuxiang Wang, Yue Gu, Haonian Gong, Hsiao-Ming Lu, Zebo Tang, Yidong Yang","doi":"10.1002/mp.17393","DOIUrl":"10.1002/mp.17393","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The accuracy of proton therapy and preclinical proton irradiation experiments is susceptible to proton range uncertainties, which partly stem from the inaccurate conversion between CT numbers and relative stopping power (RSP). Proton computed tomography (PCT) can reduce these uncertainties by directly acquiring RSP maps.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aims to develop a novel PCT imaging system based on scintillator-based proton range detection for accurate RSP reconstruction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The proposed PCT system consists of a pencil-beam brass collimator with a 1 mm aperture, an object stage capable of translation and 360° rotation, a plastic scintillator for dose-to-light conversion, and a complementary metal oxide semiconductor (CMOS) camera for light distribution acquisition. A calibration procedure based on Monte Carlo (MC) simulation was implemented to convert the obtained light ranges into water equivalent ranges. The water equivalent path lengths (WEPLs) of the imaged object were determined by calculating the differences in proton ranges obtained with and without the object in the beam path. To validate the WEPL calculation, measurements of WEPLs for eight tissue-equivalent inserts were conducted. PCT imaging was performed on a custom-designed phantom and a mouse, utilizing both 60 and 360 projections. The filtered back projection (FBP) algorithm was employed to reconstruct the RSP from WEPLs. Image quality was assessed based on the reconstructed RSP maps and compared to reference and simulation-based reconstructions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The differences between the calibrated and reference ranges of 110–150 MeV proton beams were within 0.18 mm. The WEPLs of eight tissue-equivalent inserts were measured with accuracies better than 1%. Phantom experiments exhibited good agreement with reference and simulation-based reconstructions, demonstrating average RSP errors of 1.26%, 1.38%, and 0.38% for images reconstructed with 60 projections, 60 projections after penalized weighted least-squares algorithm denoising, and 360 projections, respectively. Mouse experiments provided clear observations of mouse contours and major tissue types. MC simulation estimated an imaging dose of 3.44 cGy for decent RSP reconstruction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The proposed PCT imaging system enables RSP map acquisition with high accuracy and has the potential to improve dose calculation accuracy in proton therapy and precli","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8047-8059"},"PeriodicalIF":3.2,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Precise ablation zone segmentation on CT images after liver cancer ablation using semi‐automatic CNN‐based segmentation","authors":"Quoc Anh Le, Xuan Loc Pham, Theo van Walsum, Viet Hang Dao, Tuan Linh Le, Daniel Franklin, Adriaan Moelker, Vu Ha Le, Nguyen Linh Trung, Manh Ha Luu","doi":"10.1002/mp.17373","DOIUrl":"https://doi.org/10.1002/mp.17373","url":null,"abstract":"BackgroundAblation zone segmentation in contrast‐enhanced computed tomography (CECT) images enables the quantitative assessment of treatment success in the ablation of liver lesions. However, fully automatic liver ablation zone segmentation in CT images still remains challenging, such as low accuracy and time‐consuming manual refinement of the incorrect regions.PurposeTherefore, in this study, we developed a semi‐automatic technique to address the remaining drawbacks and improve the accuracy of the liver ablation zone segmentation in the CT images.MethodsOur approach uses a combination of a CNN‐based automatic segmentation method and an interactive CNN‐based segmentation method. First, automatic segmentation is applied for coarse ablation zone segmentation in the whole CT image. Human experts then visually validate the segmentation results. If there are errors in the coarse segmentation, local corrections can be performed on each slice via an interactive CNN‐based segmentation method. The models were trained and the proposed method was evaluated using two internal datasets of post‐interventional CECT images ( = 22, = 145; 62 patients in total) and then further tested using an external benchmark dataset ( = 12; 10 patients).ResultsTo evaluate the accuracy of the proposed approach, we used Dice similarity coefficient (<jats:italic>DSC</jats:italic>), average symmetric surface distance (<jats:italic>ASSD</jats:italic>), Hausdorff distance (<jats:italic>HD</jats:italic>), and volume difference (<jats:italic>VD</jats:italic>). The quantitative evaluation results show that the proposed approach obtained mean <jats:italic>DSC</jats:italic>, <jats:italic>ASSD</jats:italic>, <jats:italic>HD</jats:italic>, and <jats:italic>VD</jats:italic> scores of 94.0%, 0.4 mm, 8.4 mm, 0.02, respectively, on the internal dataset, and 87.8%, 0.9 mm, 9.5 mm, and −0.03, respectively, on the benchmark dataset. We also compared the performance of the proposed approach to that of five well‐known segmentation methods; the proposed semi‐automatic method achieved state‐of‐the‐art performance on ablation segmentation accuracy, and on average, 2 min are required to correct the segmentation. Furthermore, we found that the accuracy of the proposed method on the benchmark dataset is comparable to that of manual segmentation by human experts ( = 0.55, ‐test).ConclusionsThe proposed semi‐automatic CNN‐based segmentation method can be used to effectively segment the ablation zones, increasing the value of CECT for an assessment of treatment success. For reproducibility, the trained models, source code, and demonstration tool are publicly available at <jats:ext-link xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"https://github.com/lqanh11/Interactive_AblationZone_Segmentation\">https://github.com/lqanh11/Interactive_AblationZone_Segmentation</jats:ext-link>.","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"5 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying dose perturbations in high-risk prostate radiotherapy due to translational and rotational motion of prostate and pelvic lymph nodes","authors":"Karolina A. Klucznik,&nbsp;Thomas Ravkilde,&nbsp;Simon Skouboe,&nbsp;Ditte S. Møller,&nbsp;Steffen B. Hokland,&nbsp;Paul Keall,&nbsp;Simon Buus,&nbsp;Lise Bentzen,&nbsp;Per R. Poulsen","doi":"10.1002/mp.17366","DOIUrl":"10.1002/mp.17366","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Radiotherapy of the prostate and the pelvic lymph nodes (LN) is a part of the standard of care treatment for high-risk prostate cancer. The independent translational and rotational (i.e., six-degrees-of-freedom, [6DoF]) motion of the prostate and LN target during and between fractions can perturb the dose distribution. However, no standard dose reconstruction method accounting for differential 6DoF target motion is available.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We present a framework for monitoring motion-induced dose perturbations for two independently moving target volumes in 6DoF. The framework was used to determine the dose perturbation for the prostate and the LN target caused by differential 6DoF motion for a cohort of high-risk prostate cancer patients. As a potential first step toward real-time dose-guided high-risk prostate radiotherapy, we furthermore investigated if the dose reconstruction was fast enough for real-time application for both targets.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Twenty high-risk prostate cancer patients were treated with 3-arc volumetric modulated arc therapy (VMAT). Kilovoltage intrafraction monitoring (KIM) with triggered kilovoltage (kV) images acquired every 3 throughout 7–10 fractions per patient was used for retrospective 6DoF intrafraction prostate motion estimation. The 6DoF interfraction LN motion was determined from a pelvic bone match between the planning CT and a post-treatment cone beam CT (CBCT). Using the retrospectively extracted motion, real-time 6DoF motion-including dose reconstruction was simulated using the in-house developed software DoseTracker. A data stream with the 6DoF target positions and linac parameters was broadcasted at a 3-Hz frequency to DoseTracker. In a continuous loop, DoseTracker calculated the target dose increments including the specified motion and, for comparison, without motion. The motion-induced change in D&lt;sub&gt;99.5%&lt;/sub&gt; for the prostate CTV (ΔD&lt;sub&gt;99.5%&lt;/sub&gt;) and in D&lt;sub&gt;98%&lt;/sub&gt; for the LN CTV (ΔD&lt;sub&gt;98%&lt;/sub&gt;) was calculated using the final cumulative dose of each fraction and averaged over all imaged fractions. The real-time reconstructed dose distribution of DoseTracker was benchmarked against a clinical treatment planning system (TPS) and it was investigated whether the calculation speed was fast enough to keep up with the incoming data stream.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Translational motion was largest in cranio-caudal (CC) direction (prostate: [-5.9, +8.4] mm; LN: [-9.9; +11.0] m","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8423-8433"},"PeriodicalIF":3.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17366","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142143511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrasound attenuation imaging as a strategy for evaluation of early and late ambulatory functions in Duchenne muscular dystrophy","authors":"Dong Yan,&nbsp;Qiang Li,&nbsp;Ya-Wen Chuang,&nbsp;Chun-Hao Lu,&nbsp;Ai-Ping Yang,&nbsp;Chia-Wei Lin,&nbsp;Jeng-Yi Shieh,&nbsp;Wen-Chin Weng,&nbsp;Po-Hsiang Tsui","doi":"10.1002/mp.17389","DOIUrl":"10.1002/mp.17389","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Duchenne muscular dystrophy (DMD) is a genetic neuromuscular disorder that leads to mobility loss and life-threatening cardiac or respiratory complications. Quantitative ultrasound (QUS) envelope statistics imaging, which characterizes fat infiltration and fibrosis in muscles, has been extensively used for DMD evaluations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Notably, changes in muscle microstructures also result in acoustic attenuation, potentially serving as another crucial imaging biomarker for DMD. Expanding upon the reference frequency method (RFM), this study contributes to the field by introducing the robust RFM (RRFM) as a novel approach for ultrasound attenuation imaging in DMD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The RRFM algorithm was developed using an iterative reweighted least squares technique. We conducted standard phantom measurements with a clinical ultrasound system equipped with a linear array transducer to assess the improvement in attenuation estimation bias by RRFM. Additionally, 161 DMD patients, included in both a validation dataset (<i>n</i> = 130) and a testing dataset (<i>n</i> = 31), underwent ultrasound scanning of the gastrocnemius for RRFM-based attenuation imaging. The diagnostic performances for ambulatory functions and discrimination between early and late ambulatory stages were evaluated and compared with those of QUS envelope statistics imaging (involving Nakagami distribution, homodyned K distribution, and entropy values) using the area under the receiver operating characteristic curve (AUROC).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The results indicated that the RRFM method more closely matched the actual attenuation properties of the phantom, reducing measurement bias by 50% compared to conventional RFM. The AUROCs for RRFM-based attenuation imaging, used to discriminate between early and late ambulatory stages, were 0.88 and 0.92 for the validation and testing datasets, respectively. These performances significantly surpassed those of QUS envelope statistics imaging (<i>p</i> &lt; 0.05).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Ultrasound attenuation imaging employing RRFM may serve as a sensitive tool for evaluating the progression of ambulatory function deterioration, offering substantial potential for the health management and follow-up care of DMD patients.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8074-8086"},"PeriodicalIF":3.2,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142142247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance evaluation of single- and dual-contrast spectral imaging on a photon-counting-detector CT","authors":"Liqiang Ren,&nbsp;Zhongxing Zhou,&nbsp;Zaki Ahmed,&nbsp;Kishore Rajendran,&nbsp;Joel G. Fletcher,&nbsp;Cynthia H. McCollough,&nbsp;Lifeng Yu","doi":"10.1002/mp.17367","DOIUrl":"10.1002/mp.17367","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The first commercially available photon-counting-detector CT (PCD-CT) has been introduced for clinical use. However, its spectral performance on single- and dual-contrast imaging tasks has not been comprehensively assessed.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To evaluate the spectral imaging performance of a clinical PCD-CT system for single-contrast material [iodine (I) or gadolinium (Gd)] and dual-contrast materials (I and Gd) in comparison with a dual-source dual-energy CT (DS-DECT).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Iodine (5, 10, and 15 mg/mL) and gadolinium (3.3, 6.6, and 9.9 mg/mL) samples, and their mixtures (I/Gd: 5/3.3 and 10/6.6 mg/mL) were prepared and placed in two torso-shaped water phantoms (lateral dimensions: 30 and 40 cm). These phantoms were scanned on a PCD-CT (NAEOTOM Alpha, Siemens) at 90, 120, and 140 kV. The same phantoms were scanned on a DS-DECT (SOMATOM Force, Siemens) with 70/Sn150, 80/Sn150, 90/Sn150, and 100/Sn150 kV. The radiation dose levels were matched [volume CT dose index (CTDIvol): 10 mGy for the 30 cm phantom and 20 mGy for the 40 cm phantom] across all tube voltage settings and between scanners. Two-material decomposition (I/water or Gd/water) was performed on iodine or gadolinium samples, and three-material decomposition (I/Gd/water) on both individual samples and mixtures. On each decomposed image, mean mass concentration (± standard deviation) was measured in circular region-of-interests placed on the contrast samples. Root-mean-square-error (RMSE) values of iodine and gadolinium concentrations were reported based on the measurements across all contrast samples and repeated on 10 consecutive slices.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;For all material decomposition tasks on the DS-DECT, the kV pairs with greater spectral separation (70/Sn150 kV and 80/Sn150 kV) yielded lower RMSE values than other DS-DECT and PCD-CT alternatives. Specifically, for the optimal 70/Sn150 kV, RMSE values were 1.2 ± 0.1 mg/mL (I) for I/water material decomposition, 1.0 ± 0.1 mg/mL (Gd) for Gd/water material decomposition, and 4.5 ± 0.2 mg/mL (I) and 3.7 ± 0.2 mg/mL (Gd), respectively, for I/Gd/water material decomposition. On the PCD-CT, the optimal tube voltages were 120 or 140 kV for I/water decomposition with RMSE values of 2.0 ± 0.1 mg/mL (I). For Gd/water decomposition on PCD-CT, the optimal tube voltage was 140 kV with gadolinium RMSE values of 1.5 ± 0.1 mg/mL (Gd), with the 90 kV setting on PCD-CT generating higher RMSE values for gadolinium concentration compared to all DS-DECT and PCD-CT alternatives. For three material decompositi","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8034-8046"},"PeriodicalIF":3.2,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142134948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning method for predicting weekly anatomical changes in patients with nasopharyngeal carcinoma during radiotherapy","authors":"Bining Yang,&nbsp;Yuxiang Liu,&nbsp;Ran Wei,&nbsp;Kuo Men,&nbsp;Jianrong Dai","doi":"10.1002/mp.17381","DOIUrl":"10.1002/mp.17381","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Patients may undergo anatomical changes during radiotherapy, leading to an underdosing of the target or overdosing of the organs at risk (OARs).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study developed a deep-learning method to predict the tumor response of patients with nasopharyngeal carcinoma (NPC) during treatment. This method can predict the anatomical changes of a patient.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The participants included 230 patients with NPC. The data included planning computed tomography (pCT) and routine cone-beam CT (CBCT) images. The CBCT image quality was improved to the CT level using an advanced method. A long short-term memory network-generative adversarial network (LSTM-GAN) is proposed, which can harness the forecasting ability of LSTM and the generation ability of GAN. Four models were trained to predict the anatomical changes that occurred in weeks 3–6 and named LSTM-GAN-week 3 to LSTM-GAN-week 6. The pCT and CBCT were used as input, and the tumor target volumes (TVs) and OARs were delineated on the predicted and real images (ground truth). Finally, the models were evaluated using contours and dosimetry parameters.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The proposed method predicted the anatomical changes, with a dice similarity coefficient above 0.94 and 0.90 for the TVs and surrounding OARs, respectively. The dosimetry parameters were close between the prediction and ground truth. The deviations in the prescription, minimum, and maximum doses of the tumor targets were below 0.5 Gy. For serial organs (brain stem and spinal cord), the deviations in the maximum dose were below 0.6 Gy. For parallel organs (bilateral parotid glands), the deviations in the mean dose were below 0.8 Gy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The proposed method can predict the tumor response to radiotherapy in the future such that adaptation can be scheduled on time. This study provides a proactive mechanism for planning adaptation, which can enable personalized treatment and save clinical time by anticipating and preparing for treatment strategy adjustments.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"7998-8009"},"PeriodicalIF":3.2,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142121457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating the viscoelastic anisotropy of human skin through high-frequency ultrasound elastography","authors":"Yu-Chen Wu,&nbsp;Guo-Xuan Xu,&nbsp;Chien Chen,&nbsp;Yi-Hsiang Chuang,&nbsp;Chih-Chung Huang","doi":"10.1002/mp.17372","DOIUrl":"10.1002/mp.17372","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The skin is the largest organ of the human body and serves distinct functions in protecting the body. The viscoelastic properties of the skin play a key role in supporting the skin-healing process, also it may be changed due to some skin diseases.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Propose</h3>\u0000 \u0000 <p>In this study, high-frequency ultrasound (HFUS) elastography based on a Lamb wave model was used to noninvasively assess the viscoelastic anisotropy of human skin.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>Elastic waves were generated through an external vibrator, and the wave propagation velocity was measured through 40 MHz ultrafast HFUS imaging. Through the use of a thin-layer gelatin phantom, HFUS elastography was verified to produce highly accurate estimates of elasticity and viscosity. In a human study involving five volunteers, viscoelastic anisotropy was assessed by rotating an ultrasound transducer 360°.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>An oval-shaped pattern in the elasticity of human forearm skin was identified, indicating the high elastic anisotropy of skin; the average elastic moduli were 24.90 ± 6.63 and 13.64 ± 2.67 kPa along and across the collagen fiber orientation, respectively. The average viscosity of all the recruited volunteers was 3.23 ± 0.93 Pa·s.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Although the examined skin exhibited elastic anisotropy, no evident viscosity anisotropy was observed.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8060-8073"},"PeriodicalIF":3.2,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17372","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142121458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of early recurrence of adult-type diffuse gliomas following radiotherapy using multi-modal magnetic resonance images","authors":"Elahheh Salari,&nbsp;Xuxin Chen,&nbsp;Jacob Frank Wynne,&nbsp;Richard L. J. Qiu,&nbsp;Justin Roper,&nbsp;Hui-Kuo Shu,&nbsp;Xiaofeng Yang","doi":"10.1002/mp.17382","DOIUrl":"10.1002/mp.17382","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Adult-type diffuse gliomas are among the central nervous system's most aggressive malignant primary neoplasms. Despite advancements in systemic therapies and technological improvements in radiation oncology treatment delivery, the survival outcome for these patients remains poor. Fast and accurate assessment of tumor response to oncologic treatments is crucial, as it can enable the early detection of recurrent or refractory gliomas, thereby allowing timely intervention with life-prolonging salvage therapies.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Radiomics is a developing field with great potential to improve medical image interpretation. This study aims to apply a radiomics-based predictive model for classifying response to radiotherapy within the first 3 months post-treatment.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Ninety-five patients were selected from the Burdenko Glioblastoma Progression Dataset. Tumor regions were delineated in the axial plane on contrast-enhanced T1(CE T1W) and T2 fluid-attenuated inversion recovery (T2_FLAIR) magnetic resonance imaging (MRI). Hand-crafted radiomic (HCR) features, including first- and second-order features, were extracted using PyRadiomics (3.7.6) in Python (3.10). Then, recursive feature elimination with a random forest (RF) classifier was applied for feature dimensionality reduction. RF and support vector machine (SVM) classifiers were built to predict treatment outcomes using the selected features. Leave-one-out cross-validation was employed to tune hyperparameters and evaluate the models.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;For each segmented target, 186 HCR features were extracted from the MRI sequence. Using the top-ranked radiomic features from a combination of CE T1W and T2_FLAIR, an optimized classifier achieved the highest averaged area under the curve (AUC) of 0.829 ± 0.075 using the RF classifier. The HCR features of CE T1W produced the worst outcomes among all models (0.603 ± 0.024 and 0.615 ± 0.075 for RF and SVM classifiers, respectively).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We developed and evaluated a radiomics-based predictive model for early tumor response to radiotherapy, demonstrating excellent performance supported by high AUC values. This model, harnessing radiomic features from multi-modal MRI, showed superior predictive performance compared to single-modal MRI approaches. These results underscore the potential of radiomics in clinical decision support for this disease process.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8638-8648"},"PeriodicalIF":3.2,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142116529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of singular value decomposition on removing injection variability in 2D quantitative angiography: An in silico and in vitro phantoms study","authors":"Parmita Mondal,&nbsp;Swetadri Vasan Setlur Nagesh,&nbsp;Sam Sommers-Thaler,&nbsp;Allison Shields,&nbsp;Mohammad Mahdi Shiraz Bhurwani,&nbsp;Kyle A. Williams,&nbsp;Ammad Baig,&nbsp;Kenneth Snyder,&nbsp;Adnan H. Siddiqui,&nbsp;Elad Levy,&nbsp;Ciprian N. Ionita","doi":"10.1002/mp.17357","DOIUrl":"10.1002/mp.17357","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Intraoperative 2D quantitative angiography (QA) for intracranial aneurysms (IAs) has accuracy challenges due to the variability of hand injections. Despite the success of singular value decomposition (SVD) algorithms in reducing biases in computed tomography perfusion (CTP), their application in 2D QA has not been extensively explored. This study seeks to bridge this gap by investigating the potential of SVD-based deconvolution methods in 2D QA, particularly in addressing the variability of injection durations.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Building on the identified limitations in QA, the study aims to adapt SVD-based deconvolution techniques from CTP to QA for IAs. This adaptation seeks to capitalize on the high temporal resolution of QA, despite its two-dimensional nature, to enhance the consistency and accuracy of hemodynamic parameter assessment. The goal is to develop a method that can reliably assess hemodynamic conditions in IAs, independent of injection variables, for improved neurovascular diagnostics.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Materials and methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The study included three internal carotid aneurysm (ICA) cases. Virtual angiograms were generated using computational fluid dynamics (CFD) for three physiologically relevant inlet velocities to simulate contrast media injection durations. Time-density curves (TDCs) were produced for both the inlet and aneurysm dome. Various SVD variants, including standard SVD (sSVD) with and without classical Tikhonov regularization, block-circulant SVD (bSVD), and oscillation index SVD (oSVD), were applied to virtual angiograms. The method was applied on virtual angiograms to recover the aneurysmal dome impulse response function (IRF) and extract flow related parameters such as Peak Height PH&lt;sub&gt;IRF&lt;/sub&gt;, Area Under the Curve AUC&lt;sub&gt;IRF&lt;/sub&gt;, and Mean transit time MTT. Next, correlations between QA parameters, injection duration, and inlet velocity were assessed for unconvolved and deconvolved data for all SVD methods. Additionally, we performed an in vitro study, to complement our in silico investigation. We generated a 2D DSA using a flow circuit design for a patient-specific internal carotid artery phantom. The DSA showcases factors like x-ray artifacts, noise, and patient motion. We evaluated QA parameters for the in vitro phantoms using different SVD variants and established correlations between QA parameters, injection duration, and velocity for unconvolved and deconvolved data.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The different SVD algorithm variants showed strong correlations between flow and deconvolut","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8192-8212"},"PeriodicalIF":3.2,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142083014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Technical note: A software tool to extract complexity metrics from radiotherapy treatment plans","authors":"Samuele Cavinato,&nbsp;Alessandro Scaggion,&nbsp;Marta Paiusco","doi":"10.1002/mp.17365","DOIUrl":"10.1002/mp.17365","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Complexity metrics are mathematical quantities designed to quantify aspects of radiotherapy treatment plans that may affect both their deliverability and dosimetric accuracy. Despite numerous studies investigating their utility, there remains a notable absence of shared tools for their extraction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study introduces UCoMX (Universal Complexity Metrics Extractor), a software package designed for the extraction of complexity metrics from the DICOM-RT plan files of radiotherapy treatments.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>UCoMX is developed around two extraction engines: VCoMX (VMAT Complexity Metrics Extractor) for VMAT/IMRT plans, and TCoMX (Tomotherapy Complexity Metrics Extractor) tailored for Helical Tomotherapy plans. The software, built using Matlab, is freely available in both Matlab-based and stand-alone versions. More than 90 complexity metrics, drawn from relevant literature, are implemented in the package: 43 for VMAT/IMRT and 51 for Helical Tomotherapy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The package is designed to read DICOM-RT plan files generated by most commercially available Treatment Planning Systems (TPSs), across various treatment units. A reference dataset containing VMAT, IMRT, and Helical Tomotherapy plans is provided to serve as a reference for comparing UCoMX with other in-house systems available at other centers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>UCoMX offers a straightforward solution for extracting complexity metrics from radiotherapy plans. Its versatility is enhanced through different versions, including Matlab-based and stand-alone, and its compatibility with a wide range of commercially available TPSs and treatment units. UCoMX presents a free, user-friendly tool empowering researchers to compute the complexity of treatment plans efficiently.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8602-8612"},"PeriodicalIF":3.2,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17365","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142074871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}