Indian Journal of Radiology and Imaging最新文献

{"title":"Image-Guided Percutaneous Sclerotherapy for Orbital Low-Flow Malformation: Our Experience.","authors":"Gautam Lokdarshi, Shwetam Kumar, Subhash Kumar, Nitu Nitu, Nripen Gaur","doi":"10.1055/s-0044-1779689","DOIUrl":"10.1055/s-0044-1779689","url":null,"abstract":"<p><p>For a safe sclerotherapy session to be completed in the orbital low-flow malformation (namely lymphovenous malformation or venolymphatic malformation), accurate identification of the target lesion for the drug injection is crucial. Regarding the dependability and viability of the injection approach, the authors have discussed their experiences with image-guided percutaneous sclerotherapy on a few patients.</p>","PeriodicalId":51597,"journal":{"name":"Indian Journal of Radiology and Imaging","volume":"34 3","pages":"539-544"},"PeriodicalIF":0.9,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11188674/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141443740","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":"Approach to Nonmass Lesions on Breast Ultrasound.","authors":"Supraja Laguduva Mohan, Ekta Dhamija, Richa Gauba","doi":"10.1055/s-0044-1779589","DOIUrl":"https://doi.org/10.1055/s-0044-1779589","url":null,"abstract":"<p><p>Nonmass lesions in breast ultrasound (US) are areas of altered echogenicity without definite margins or mass effect. However, these lesions may show calcifications, associated architectural distortion, or shadowing just like masses. They vary in their echogenicity, distribution, ductal or nonductal appearance and the associated features that can be seen in variety of benign and malignant pathologies. With no uniform definition or classification system, there is no standardized approach in further risk categorization and management strategies of these lesions. Malignant nonmass lesions are not uncommon and few sonographic features can help in differentiating benign and malignant pathologies. US-guided tissue sampling or lesion localization can be preferred in the nonmass lesions identified on second look US after magnetic resonance imaging or mammography. This article aims to describe various imaging patterns and attempts to provide an algorithmic approach to nonmass findings on breast US.</p>","PeriodicalId":51597,"journal":{"name":"Indian Journal of Radiology and Imaging","volume":"34 4","pages":"677-687"},"PeriodicalIF":0.9,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11419763/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142332163","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":"Pretherapeutic PSMA PET-Derived Semiquantitative Parameters as Predictors of PSA Response in Patients with mCRPC Receiving [ ¹⁷⁷ Lu]Lu-PSMA-617 Radioligand Therapy.","authors":"Dheeratama Siripongsatian, Attapon Jantarato, Chetsadaporn Promteangtrong, Anchisa Kunawudhi, Peerapon Kiatkittikul, Natphimol Boonkawin, Sukanya Yaset, Sirinsuda Somboon, Chanisa Chotipanich","doi":"10.1055/s-0044-1779634","DOIUrl":"https://doi.org/10.1055/s-0044-1779634","url":null,"abstract":"<p><p><b>Objective</b>  [ ¹⁷⁷ Lu]Lu-prostate-specific membrane antigen (PSMA)-617 radioligand therapy (RLT) shows promise for metastatic castration-resistant prostate cancer (mCRPC) patients with positive PSMA positron emission tomography (PET) imaging. Identifying high-risk patients is crucial. We evaluated pretherapeutic PSMA PET-derived parameters to predict prostate-specific antigen (PSA) response in patients undergoing [ ¹⁷⁷ Lu]Lu-PSMA-617 RLT. <b>Materials and Methods</b>  We conducted a retrospective analysis among 27 patients (mean age: 71.0 ± 9.5 years; range: 52-85 years) who underwent PSMA PET/computed tomography (CT) and subsequent [ ¹⁷⁷ Lu]Lu-PSMA-617 RLT between March 2019 and January 2023. After excluding patients with liver metastases, the number of patients left for analysis was 21 (14 responders and 7 nonresponders). Tumors were semiautomatically delineated with calculation of total tumor volume (PSMA-TV), lesion uptake (PSMA-TLU = PSMA-TV * standardized uptake value [SUV]mean), and lesion quotient (PSMA-TLQ = PSMA-TV/SUVmean) for each patient. Semiquantitative parameters were analyzed only in patients with mCRPC and no liver metastasis. <b>Results</b>  In total, 17/27 patients (62.96%) had a decline in PSA levels; 15/27 patients (55.56%) experienced a decline of > 50%. Pretherapeutic PSMA PET/CT results revealed significant differences in PSMA-TV ( <i>p</i>  = 0.003), PSMA-TLU ( <i>p</i>  = 0.013), and PSMA-TLQ ( <i>p</i>  = 0.011) between responders and nonresponders. SUVmax was significantly correlated to the best percentage change in PSA response after ¹⁷⁷ Lu-PSMA-617 treatment ( <i>r</i>  = -0.79, <i>p</i>  = 0.006). No association was observed between PSMA-TV ( <i>p</i>  = 0.367), PSMA-TLU ( <i>p</i>  = 0.128), and PSMA-TLQ ( <i>p</i>  = 0.556), with the best percentage change in PSA response after ¹⁷⁷ Lu-PSMA-617 therapy. <b>Conclusion</b>  Pretherapeutic PSMA PET-derived PSMA-TV, PSMA-TLU, and PSMA-TLQ were significant negative predictors of PSA response in patients with mCRPC and no liver metastasis receiving [ ¹⁷⁷ Lu]Lu-PSMA-617 RLT.</p>","PeriodicalId":51597,"journal":{"name":"Indian Journal of Radiology and Imaging","volume":"34 4","pages":"579-587"},"PeriodicalIF":0.9,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11419753/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142332165","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":"Assessing the Capability of ChatGPT, Google Bard, and Microsoft Bing in Solving Radiology Case Vignettes","authors":"Pradosh Kumar Sarangi, Ravi Kant Narayan, S. Mohakud, Aditi Vats, Debabrata Sahani, Himel Mondal","doi":"10.1055/s-0043-1777746","DOIUrl":"https://doi.org/10.1055/s-0043-1777746","url":null,"abstract":"Abstract Background  The field of radiology relies on accurate interpretation of medical images for effective diagnosis and patient care. Recent advancements in artificial intelligence (AI) and natural language processing have sparked interest in exploring the potential of AI models in assisting radiologists. However, limited research has been conducted to assess the performance of AI models in radiology case interpretation, particularly in comparison to human experts. Objective  This study aimed to evaluate the performance of ChatGPT, Google Bard, and Bing in solving radiology case vignettes (Fellowship of the Royal College of Radiologists 2A [FRCR2A] examination style questions) by comparing their responses to those provided by two radiology residents. Methods  A total of 120 multiple-choice questions based on radiology case vignettes were formulated according to the pattern of FRCR2A examination. The questions were presented to ChatGPT, Google Bard, and Bing. Two residents wrote the examination with the same questions in 3 hours. The responses generated by the AI models were collected and compared to the answer keys and explanation of the answers was rated by the two radiologists. A cutoff of 60% was set as the passing score. Results  The two residents (63.33 and 57.5%) outperformed the three AI models: Bard (44.17%), Bing (53.33%), and ChatGPT (45%), but only one resident passed the examination. The response patterns among the five respondents were significantly different ( p  = 0.0117). In addition, the agreement among the generative AI models was significant (intraclass correlation coefficient [ICC] = 0.628), but there was no agreement between the residents (Kappa = –0.376). The explanation of generative AI models in support of answer was 44.72% accurate. Conclusion  Humans exhibited superior accuracy compared to the AI models, showcasing a stronger comprehension of the subject matter. All three AI models included in the study could not achieve the minimum percentage needed to pass an FRCR2A examination. However, generative AI models showed significant agreement in their answers where the residents exhibited low agreement, highlighting a lack of consistency in their responses.","PeriodicalId":51597,"journal":{"name":"Indian Journal of Radiology and Imaging","volume":" 33","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139143939","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":"Bedside Ultrasound-Guided Percutaneous Cholecystostomy in Critically Ill Patients—Outcomes in 51 Patients","authors":"Rozil Gandhi, K. Gala, Mohd Shariq, Aditi Gandhi, Manish Gandhi, Amit Shah","doi":"10.1055/s-0043-1777744","DOIUrl":"https://doi.org/10.1055/s-0043-1777744","url":null,"abstract":"Abstract Purpose  The aim of this study was to report technical and clinical success of bedside ultrasound-guided percutaneous cholecystostomy (PC) tube placement in intensive care unit (ICU). Materials and Methods  This is a retrospective study of 51 patients (36 males:15 females, mean age: 67 years) who underwent ultrasound-guided PC from May 2015 to January 2020. The indication for cholecystostomy tube placement, comorbidities, imaging finding, technical success, clinical success, timing of surgery post-cholecystostomy tube placement, indwelling catheter time, complications, and follow-up were recorded. Results  Indications for cholecystostomy tube placement were acute calculous cholecystitis ( n  = 43; 84.3%), perforated cholecystitis ( n  = 5; 9.8%), and emphysematous cholecystitis ( n  = 3; 5.9%). Most of the patients had multiple comorbidities; these were diabetes mellitus, hypertension, cardiovascular disease, chronic renal disease, underlying malignancy, and multisystem disease with sepsis. All patients had undergone PC through transhepatic approach under ultrasound guidance in ICU. Technical success rate of the procedure was 100%. Clinical success rate was 92.1% (47/51) and among these 44/51 (86.2%) patients underwent definitive elective cholecystectomy, 3/51 (5.9%) patients had elective tube removal. Three of fifty-one (5.9%) patients did not improve; among these two underwent emergency surgery, while there was 1/51 (1.9%) mortality due to ongoing sepsis and multiorgan dysfunction. There were no procedure-related mortalities or procedure-related major complications. One patient had bile leak due to multiple attempts for cholecystostomy placement. Mean tube indwelling time was 13 days (range: 3–45 days). Conclusion  Ultrasound-guided PC can be safely performed in ICU in critically ill patients unfit for surgery with high technical and clinical success rates. Early laparoscopic cholecystectomy should be preferred after stabilization of clinical condition following cholecystostomy.","PeriodicalId":51597,"journal":{"name":"Indian Journal of Radiology and Imaging","volume":"325 9","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139152442","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":"Macrodystrophia Lipomatosa: A Rare Case of Ulnar Nerve Territory Involvement","authors":"Sonali Ullal, Shivani Arora","doi":"10.1055/s-0043-1777745","DOIUrl":"https://doi.org/10.1055/s-0043-1777745","url":null,"abstract":"Abstract Macrodystrophia lipomatosa (MDL) is a rare congenital, nonhereditary anomaly characterized by overgrowth of all the mesenchymal elements, predominantly the fibroadipose tissue in a sclerotomal distribution commonly involving the median nerve territory in the upper extremity and plantar nerve territory in the lower extremity. It can be either static or progressive, with the former being the more common. MDL is usually present since birth and the affected digit/region increases in length and girth, and growth ceases after puberty. We discuss a rare case of ulnar nerve territory involvement that progressed to grow even after puberty.","PeriodicalId":51597,"journal":{"name":"Indian Journal of Radiology and Imaging","volume":"44 11","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139149452","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":"Radiological Differential Diagnoses Based on Cardiovascular and Thoracic Imaging Patterns: Perspectives of Four Large Language Models","authors":"Pradosh Kumar Sarangi, A. Irodi, Swaha Panda, Debasish Swapnesh Kumar Nayak, Himel Mondal","doi":"10.1055/s-0043-1777289","DOIUrl":"https://doi.org/10.1055/s-0043-1777289","url":null,"abstract":"Abstract Background  Differential diagnosis in radiology is a critical aspect of clinical decision-making. Radiologists in the early stages may find difficulties in listing the differential diagnosis from image patterns. In this context, the emergence of large language models (LLMs) has introduced new opportunities as these models have the capacity to access and contextualize extensive information from text-based input. Objective  The objective of this study was to explore the utility of four LLMs—ChatGPT3.5, Google Bard, Microsoft Bing, and Perplexity—in providing most important differential diagnoses of cardiovascular and thoracic imaging patterns. Methods  We selected 15 unique cardiovascular ( n  = 5) and thoracic ( n  = 10) imaging patterns. We asked each model to generate top 5 most important differential diagnoses for every pattern. Concurrently, a panel of two cardiothoracic radiologists independently identified top 5 differentials for each case and came to consensus when discrepancies occurred. We checked the concordance and acceptance of LLM-generated differentials with the consensus differential diagnosis. Categorical variables were compared by binomial, chi-squared, or Fisher's exact test. Results  A total of 15 cases with five differentials generated a total of 75 items to analyze. The highest level of concordance was observed for diagnoses provided by Perplexity (66.67%), followed by ChatGPT (65.33%) and Bing (62.67%). The lowest score was for Bard with 45.33% of concordance with expert consensus. The acceptance rate was highest for Perplexity (90.67%), followed by Bing (89.33%) and ChatGPT (85.33%). The lowest acceptance rate was for Bard (69.33%). Conclusion  Four LLMs—ChatGPT3.5, Google Bard, Microsoft Bing, and Perplexity—generated differential diagnoses had high level of acceptance but relatively lower concordance. There were significant differences in acceptance and concordance among the LLMs. Hence, it is important to carefully select the suitable model for usage in patient care or in medical education.","PeriodicalId":51597,"journal":{"name":"Indian Journal of Radiology and Imaging","volume":"63 3","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139149597","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":"Atypical Meningioma with Perineural Spread Along Hypoglossal Nerve","authors":"S. Rastogi, K. Bhattacharya, Aayush Mathur, Arpita A. Sahu, Amit Chaudhari, Epari Shridhar","doi":"10.1055/s-0043-1777743","DOIUrl":"https://doi.org/10.1055/s-0043-1777743","url":null,"abstract":"A 50-year-old female presented with acute onset bilateral limb weakness, episodes of severe occipital headache with multiple episodes of loss ofconsciousnesswith a background history of left side neck pain, and occipital headache in the past 4 years. There was no signi fi cant past medical/surgical, social, or familyhistory.On examination,therewasleft-sided deviation of the tongue with left-sided face weakness. Bilateral upper limb has power was 2/5 and lowerlimb power was 3/5 without any bowel and bladder incontinence. On imaging, magnetic resonance imaging (MRI) revealed a large well-de fi ned lobulated extra-axial left petroclival dura-based mass. The mass was seen extending along the prepon-tine, left cerebellopontine, and cerebellomedullary cisterns and inferiorly into the spinal canal through the foramen magnum ( ► Fig. 1A – D ). The mass was isointense on T1-weighted(T1)imagingandonT2-weighted(T2)imaging.There was no signi fi cant diffusion restriction in diffusion-weighted imaging or blooming in gradient images. The tumor displayed intense, homogeneous post-contrast enhancement. The mass showed broad base along the tentorium cerebelli and clivus. Laterally the lesion was seen widening and eroding the hypo-glossal canal and extending intotheleft parapharyngeal","PeriodicalId":51597,"journal":{"name":"Indian Journal of Radiology and Imaging","volume":"61 8","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139150419","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":"Impact of the 2023 FIGO Staging System for Endometrial Cancer on the Use of Imaging Services: An Indian Perspective","authors":"A. Chandramohan, Smitha Manchanda, Rupa Renganathan, P. Popat, Diva Shah, E. Dhamija, Anitha Sen","doi":"10.1055/s-0043-1777355","DOIUrl":"https://doi.org/10.1055/s-0043-1777355","url":null,"abstract":"Abstract The new 2023 update of the International Federation of Gynecology and Obstetrics (FIGO) staging system for endometrial cancer incorporates the advances made in the understanding of the pathology and molecular classifications into the staging system. While the new staging system aids in precision medicine and may lead to better documentation of prognostic risk categories of endometrial cancer, it is complex and calls for an integrated approach and better communication between multiple disciplines involved in the management of endometrial cancer. In this review article, we address how the referral patterns to imaging services might change considering the updated staging system for endometrial cancer. We also discuss the practical aspects and nuances involved in the radiology service delivery and reporting practices as we adopt the new FIGO staging system for managing endometrial cancer patients.","PeriodicalId":51597,"journal":{"name":"Indian Journal of Radiology and Imaging","volume":"123 3","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138999669","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":"Hand Radiographs in Skeletal Dysplasia: A Pictorial Review","authors":"Dheeksha D. S., Stuti Chandola, Aayush Jain, Neerja Gupta, M. Kabra, M. Jana","doi":"10.1055/s-0043-1777320","DOIUrl":"https://doi.org/10.1055/s-0043-1777320","url":null,"abstract":"Abstract Skeletal dysplasias or osteochondrodysplasias comprise a large heterogeneous group of genetic disorders and possess significant overlap on imaging, which adds to the dilemma of the reporting radiologist. These entities are routinely evaluated with a detailed skeletal survey and hand radiographs form a crucial part of a complete survey. Certain conditions have characteristic imaging findings that enable a diagnosis be made on hand radiograph alone. Additionally, hand radiographs may also demonstrate findings that may be suggestive of a particular diagnosis/differential diagnoses and would warrant further assessment for proving the same. We aim to demonstrate the use of hand radiographs in diagnosis of various such entities through this review. Although they cannot replace a complete skeletal survey in the diagnosis, hand radiographs performed for other indications might alert a radiologist to the diagnosis of an unsuspected skeletal dysplasia.","PeriodicalId":51597,"journal":{"name":"Indian Journal of Radiology and Imaging","volume":"80 S11","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138999603","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}