• Title/Summary/Keyword: Cancers

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Risk Factors for Renal Function Impairment Following Radiofrequency Ablation of Renal Tumors (신장 종양 고주파 절제술 이후 신장 기능 저하의 위험요소)

  • Il Cheol Park;Seong Kuk Yoon;Dong Won Kim
    • Journal of the Korean Society of Radiology
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    • v.83 no.2
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    • pp.317-330
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    • 2022
  • Purpose To evaluate the various factors that affect renal function following percutaneous radiofrequency ablation (RFA) therapy in patients with renal tumors. Materials and Methods Between 2010 and 2018, 91 patients diagnosed with renal tumors using ultrasonography and CT-guided RFA were enrolled. We retrospectively investigated the serum creatinine (SCr) level and estimated glomerular filtration rates immediately prior to RFA and during post-treatment follow-up. The patients were divided into two groups based on the degree of change in SCr level (0.3 mg/dL). Group comparisons were performed using univariable and multivariable logistic regression analyses to determine the factors impacting renal function. Results Impaired renal function was associated with solitary kidney, chronic kidney disease (CKD) over stage 3, and pyeloureteral injury. Sex, age, other cancers, tumor size, location, growth pattern, and proximity to the collecting system were not significantly associated with impaired renal function. There was a difference in the overall change over time between the association with and without solitary kidney, CKD stage 3, and pyeloureteral injury. Conclusion Among the medical conditions present prior to RFA, solitary kidney and CKD over stage 3 could be considered as risk factors for impaired renal function. Post-procedural pyeloureteral injury can also be considered a risk factor.

Correlation between MR Image-Based Radiomics Features and Risk Scores Associated with Gene Expression Profiles in Breast Cancer (유방암에서 자기공명영상 근거 영상표현형과 유전자 발현 프로파일 근거 위험도의 관계)

  • Ga Ram Kim;You Jin Ku;Jun Ho Kim;Eun-Kyung Kim
    • Journal of the Korean Society of Radiology
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    • v.81 no.3
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    • pp.632-643
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    • 2020
  • Purpose To investigate the correlation between magnetic resonance (MR) image-based radiomics features and the genomic features of breast cancer by focusing on biomolecular intrinsic subtypes and gene expression profiles based on risk scores. Materials and Methods We used the publicly available datasets from the Cancer Genome Atlas and the Cancer Imaging Archive to extract the radiomics features of 122 breast cancers on MR images. Furthermore, PAM50 intrinsic subtypes were classified and their risk scores were determined from gene expression profiles. The relationship between radiomics features and biomolecular characteristics was analyzed. A penalized generalized regression analysis was performed to build prediction models. Results The PAM50 subtype demonstrated a statistically significant association with the maximum 2D diameter (p = 0.0189), degree of correlation (p = 0.0386), and inverse difference moment normalized (p = 0.0337). Among risk score systems, GGI and GENE70 shared 8 correlated radiomic features (p = 0.0008-0.0492) that were statistically significant. Although the maximum 2D diameter was most significantly correlated to both score systems (p = 0.0139, and p = 0.0008), the overall degree of correlation of the prediction models was weak with the highest correlation coefficient of GENE70 being 0.2171. Conclusion Maximum 2D diameter, degree of correlation, and inverse difference moment normalized demonstrated significant relationships with the PAM50 intrinsic subtypes along with gene expression profile-based risk scores such as GENE70, despite weak correlations.

Automated Versus Handheld Breast Ultrasound for Evaluating Axillary Lymph Nodes in Patients With Breast Cancer

  • Sun Mi Kim;Mijung Jang;Bo La Yun;Sung Ui Shin;Jiwon Rim;Eunyoung Kang;Eun-Kyu Kim;Hee-Chul Shin;So Yeon Park;Bohyoung Kim
    • Korean Journal of Radiology
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    • v.25 no.2
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    • pp.146-156
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    • 2024
  • Objective: Automated breast ultrasound (ABUS) is a relevant imaging technique for early breast cancer diagnosis and is increasingly being used as a supplementary tool for mammography. This study compared the performance of ABUS and handheld ultrasound (HHUS) in detecting and characterizing the axillary lymph nodes (LNs) in patients with breast cancer. Materials and Methods: We retrospectively reviewed the medical records of women with recently diagnosed early breast cancer (≤ T2) who underwent both ABUS and HHUS examinations for axilla (September 2017-May 2018). ABUS and HHUS findings were compared using pathological outcomes as reference standards. Diagnostic performance in predicting any axillary LN metastasis and heavy nodal-burden metastases (i.e., ≥ 3 LNs) was evaluated. The ABUS-HHUS agreement for visibility and US findings was calculated. Results: The study included 377 women (53.1 ± 11.1 years). Among 385 breast cancers in 377 patients, 101 had axillary LN metastases and 30 had heavy nodal burden metastases. ABUS identified benign-looking or suspicious axillary LNs (average, 1.4 ± 0.8) in 246 axillae (63.9%, 246/385). According to the per-breast analysis, the sensitivity, specificity, positive and negative predictive values, and accuracy of ABUS in predicting axillary LN metastases were 43.6% (44/101), 95.1% (270/284), 75.9% (44/58), 82.6% (270/327), and 81.6% (314/385), respectively. The corresponding results for HHUS were 41.6% (42/101), 95.1% (270/284), 75.0% (42/56), 82.1% (270/329), and 81.0% (312/385), respectively, which were not significantly different from those of ABUS (P ≥ 0.53). The performance results for heavy nodal-burden metastases were 70.0% (21/30), 89.6% (318/355), 36.2% (21/58), 97.3% (318/327), and 88.1% (339/385), respectively, for ABUS and 66.7% (20/30), 89.9% (319/355), 35.7% (20/56), 97.0% (319/329), and 88.1% (339/385), respectively, for HHUS, also not showing significant difference (P ≥ 0.57). The ABUS-HHUS agreement was 95.9% (236/246; Cohen's kappa = 0.883). Conclusion: Although ABUS showed limited sensitivity in diagnosing axillary LN metastasis in early breast cancer, it was still useful as the performance was comparable to that of HHUS.

Evaluation of Malignancy Risk of Ampullary Tumors Detected by Endoscopy Using 2-[18F]FDG PET/CT

  • Pei-Ju Chuang;Hsiu-Po Wang;Yu-Wen Tien;Wei-Shan Chin;Min-Shu Hsieh;Chieh-Chang Chen;Tzu-Chan Hong;Chi-Lun Ko;Yen-Wen Wu;Mei-Fang Cheng
    • Korean Journal of Radiology
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    • v.25 no.3
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    • pp.243-256
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    • 2024
  • Objective: We aimed to investigate whether 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) can aid in evaluating the risk of malignancy in ampullary tumors detected by endoscopy. Materials and Methods: This single-center retrospective cohort study analyzed 155 patients (79 male, 76 female; mean age, 65.7 ± 12.7 years) receiving 2-[18F]FDG PET/CT for endoscopy-detected ampullary tumors 5-87 days (median, 7 days) after the diagnostic endoscopy between June 2007 and December 2020. The final diagnosis was made based on histopathological findings. The PET imaging parameters were compared with clinical data and endoscopic features. A model to predict the risk of malignancy, based on PET, endoscopy, and clinical findings, was generated and validated using multivariable logistic regression analysis and an additional bootstrapping method. The final model was compared with standard endoscopy for the diagnosis of ampullary cancer using the DeLong test. Results: The mean tumor size was 17.1 ± 7.7 mm. Sixty-four (41.3%) tumors were benign, and 91 (58.7%) were malignant. Univariable analysis found that ampullary neoplasms with a blood-pool corrected peak standardized uptake value in earlyphase scan (SUVe) ≥ 1.7 were more likely to be malignant (odds ratio [OR], 16.06; 95% confidence interval [CI], 7.13-36.18; P < 0.001). Multivariable analysis identified the presence of jaundice (adjusted OR [aOR], 4.89; 95% CI, 1.80-13.33; P = 0.002), malignant traits in endoscopy (aOR, 6.80; 95% CI, 2.41-19.20; P < 0.001), SUVe ≥ 1.7 in PET (aOR, 5.43; 95% CI, 2.00-14.72; P < 0.001), and PET-detected nodal disease (aOR, 5.03; 95% CI, 1.16-21.86; P = 0.041) as independent predictors of malignancy. The model combining these four factors predicted ampullary cancers better than endoscopic diagnosis alone (area under the curve [AUC] and 95% CI: 0.925 [0.874-0.956] vs. 0.815 [0.732-0.873], P < 0.001). The model demonstrated an AUC of 0.921 (95% CI, 0.816-0.967) in candidates for endoscopic papillectomy. Conclusion: Adding 2-[18F]FDG PET/CT to endoscopy can improve the diagnosis of ampullary cancer and may help refine therapeutic decision-making, particularly when contemplating endoscopic papillectomy.

Deep Learning in Thyroid Ultrasonography to Predict Tumor Recurrence in Thyroid Cancers (인공지능 딥러닝을 이용한 갑상선 초음파에서의 갑상선암의 재발 예측)

  • Jieun Kil;Kwang Gi Kim;Young Jae Kim;Hye Ryoung Koo;Jeong Seon Park
    • Journal of the Korean Society of Radiology
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    • v.81 no.5
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    • pp.1164-1174
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    • 2020
  • Purpose To evaluate a deep learning model to predict recurrence of thyroid tumor using preoperative ultrasonography (US). Materials and Methods We included representative images from 229 US-based patients (male:female = 42:187; mean age, 49.6 years) who had been diagnosed with thyroid cancer on preoperative US and subsequently underwent thyroid surgery. After selecting each representative transverse or longitudinal US image, we created a data set from the resulting database of 898 images after augmentation. The Python 2.7.6 and Keras 2.1.5 framework for neural networks were used for deep learning with a convolutional neural network. We compared the clinical and histological features between patients with and without recurrence. The predictive performance of the deep learning model between groups was evaluated using receiver operating characteristic (ROC) analysis, and the area under the ROC curve served as a summary of the prognostic performance of the deep learning model to predict recurrent thyroid cancer. Results Tumor recurrence was noted in 49 (21.4%) among the 229 patients. Tumor size and multifocality varied significantly between the groups with and without recurrence (p < 0.05). The overall mean area under the curve (AUC) value of the deep learning model for prediction of recurrent thyroid cancer was 0.9 ± 0.06. The mean AUC value was 0.87 ± 0.03 in macrocarcinoma and 0.79 ± 0.16 in microcarcinoma. Conclusion A deep learning model for analysis of US images of thyroid cancer showed the possibility of predicting recurrence of thyroid cancer.

Percutaneous Transgastric Stent Placement for Malignant Gastroduodenal Obstruction (악성 위십이지장 협착 환자에서의 경피적 위 경유 스텐트 설치)

  • Bumsang Cho;Gyoo-Sik Jung;Jong Hyouk Yun
    • Journal of the Korean Society of Radiology
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    • v.81 no.5
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    • pp.1175-1183
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    • 2020
  • Purpose To evaluate the technical feasibility and clinical efficacy of percutaneous transgastric stent placement after the failure of treatment attempt with the transoral approach in malignant gastroduodenal obstruction patients. Materials and Methods From October 2008 to April 2016, nine patients (M:F = 4:5; mean age = 66 years) with malignant gastroduodenal obstruction underwent stent placement via a gastrostomy tract, which was attributed to the failure of the transoral approach. The primary etiologies of the obstruction were pancreatic (n = 5), gastric (n = 2), and metastatic (n = 2) cancers. Through percutaneous gastrostomy, dual stents (inner bare metal and outer polytetrafluoroethylene-covered) were deployed at the obstruction site. The technical and clinical success rates, as well as complications were evaluated during the follow-up period. Results Stents were successfully inserted in eight patients (88%). We failed to insert stent in one patient due to the presence of a tight obstruction. After stent placement, symptoms improved in seven patients. Gastrostomy tube was removed 9 to 20 days (mean = 12 days) after the stent insertion. During the mean follow-up of 136 days (range, 3-387 days), one patient developed a recurrent symptom due to tumor overgrowth. However, there were no other major complications associated with the procedure. Conclusion Percutaneous transgastric stent placement appeared to be technically feasible and clinically effective in patients who underwent a failed transoral approach.

Digital Breast Tomosynthesis Plus Ultrasound Versus Digital Mammography Plus Ultrasound for Screening Breast Cancer in Women With Dense Breasts

  • Su Min Ha;Ann Yi;Dahae Yim;Myoung-jin Jang;Bo Ra Kwon;Sung Ui Shin;Eun Jae Lee;Soo Hyun Lee;Woo Kyung Moon;Jung Min Chang
    • Korean Journal of Radiology
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    • v.24 no.4
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    • pp.274-283
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    • 2023
  • Objective: To compare the outcomes of digital breast tomosynthesis (DBT) screening combined with ultrasound (US) with those of digital mammography (DM) combined with US in women with dense breasts. Materials and Methods: A retrospective database search identified consecutive asymptomatic women with dense breasts who underwent breast cancer screening with DBT or DM and whole-breast US simultaneously between June 2016 and July 2019. Women who underwent DBT + US (DBT cohort) and DM + US (DM cohort) were matched using 1:2 ratio according to mammographic density, age, menopausal status, hormone replacement therapy, and a family history of breast cancer. The cancer detection rate (CDR) per 1000 screening examinations, abnormal interpretation rate (AIR), sensitivity, and specificity were compared. Results: A total of 863 women in the DBT cohort were matched with 1726 women in the DM cohort (median age, 53 years; interquartile range, 40-78 years) and 26 breast cancers (9 in the DBT cohort and 17 in the DM cohort) were identified. The DBT and DM cohorts showed comparable CDR (10.4 [9 of 863; 95% confidence interval {CI}: 4.8-19.7] vs. 9.8 [17 of 1726; 95% CI: 5.7-15.7] per 1000 examinations, respectively; P = 0.889). DBT cohort showed a higher AIR than the DM cohort (31.6% [273 of 863; 95% CI: 28.5%-34.9%] vs. 22.4% [387 of 1726; 95% CI: 20.5%-24.5%]; P < 0.001). The sensitivity for both cohorts was 100%. In women with negative findings on DBT or DM, supplemental US yielded similar CDRs in both DBT and DM cohorts (4.0 vs. 3.3 per 1000 examinations, respectively; P = 0.803) and higher AIR in the DBT cohort (24.8% [188 of 758; 95% CI: 21.8%-28.0%] vs. 16.9% [257 of 1516; 95% CI: 15.1%-18.9%; P < 0.001). Conclusion: DBT screening combined with US showed comparable CDR but lower specificity than DM screening combined with US in women with dense breasts.

Mediastinal Lymph Node Metastasis from Head and Neck Cancer: Predictive Factors and Imaging Features (두경부암의 종격동 림프절 전이: 예측인자 및 영상 소견)

  • Il Kwon Ko;Dae Young Yoon;Sora Baek;Ji Hyun Hong;Eun Joo Yun;In Jae Lee
    • Journal of the Korean Society of Radiology
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    • v.82 no.5
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    • pp.1246-1257
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    • 2021
  • Purpose To assess the predictive factors and describe the imaging features of mediastinal lymph node (MLN) metastases in patients with head and neck cancer. Materials and Methods We compared the clinical features and disease characteristics (sex, age, site of primary tumor, histologic type, history of prior treatments, TNM stages, and metastasis in cervical LNs) of patients with head and neck cancers between the MLN metastasis and no MLN metastasis groups. We also evaluated the chest CT (distribution and maximum dimension of the largest LN) and PET/CT (maximum standardized uptake value) features of MLN metastases based on the MLN classification. Results Of the 470 patients with head and neck cancer, 55 (11.7%) had MLN metastasis, involving 150 mediastinal stations. Hypopharynx cancer, recurrent tumor, T4 stage, N2/N3 stages, and M1 stage were found to be significant predicting factors for MLN metastasis. The most common location of MLN metastasis was ipsilateral station 2 (upper paratracheal LNs, 36.4%), followed by ipsilateral station 11 (interlobar LNs, 27.3%) and ipsilateral station 10 (hilar LNs, 25.5%). Conclusion Metastasis to MLNs should be considered in patients with head and neck cancer, especially in cases that are associated with a hypopharyngeal cancer, recurrent tumor, and high TNM stages.

Role of Dedicated Subspecialized Radiologists in Multidisciplinary Team Discussions on Lower Gastrointestinal Tract Cancers

  • Sun Kyung Jeon;Se Hyung Kim;Cheong-il Shin;Jeongin Yoo;Kyu Joo Park;Seung-Bum Ryoo;Ji Won Park;Tae-You Kim;Sae-Won Han;Dae-Won Lee;Eui Kyu Chie;Hyun-Cheol Kang
    • Korean Journal of Radiology
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    • v.23 no.7
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    • pp.732-741
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    • 2022
  • Objective: To determine the impact of dedicated subspecialized radiologists in multidisciplinary team (MDT) discussions on the management of lower gastrointestinal (GI) tract malignancies. Materials and Methods: We retrospectively analyzed the data of 244 patients (mean age ± standard deviation, 61.7 ± 11.9 years) referred to MDT discussions 249 times (i.e., 249 cases, as five patients were discussed twice for different issues) for lower GI tract malignancy including colorectal cancer, small bowel cancer, GI stromal tumor, and GI neuroendocrine tumor between April 2018 and June 2021 in a prospective database. Before the MDT discussions, dedicated GI radiologists reviewed all imaging studies again besides routine clinical reading. The referring clinician's initial diagnosis, initial treatment plan, change in radiologic interpretation compared with the initial radiology report, and the MDT's consensus recommendations for treatment were collected and compared. Factors associated with changes in treatment plans and the implementation of MDT decisions were analyzed. Results: Of the 249 cases, radiologic interpretation was changed in 73 cases (29.3%) after a review by dedicated GI radiologists, with 78.1% (57/73) resulting in changes in the treatment plan. The treatment plan was changed in 92 cases (36.9%), and the rate of change in the treatment plan was significantly higher in cases with changes in radiologic interpretation than in those without (78.1% [57/73] vs. 19.9% [35/176], p < 0.001). Follow-up records of patients showed that 91.2% (227/249) of MDT recommendations for treatment were implemented. Multiple logistic regression analysis revealed that the nonsurgical approach (vs. surgical approach) decided through MDT discussion was a significant factor for patients being managed differently than the MDT recommendations (odds ratio, 4.48; p = 0.017). Conclusion: MDT discussion involving additional review of radiology examinations by dedicated GI radiologists resulted in a change in the treatment plan in 36.9% of cases. Changes in treatment plans were significantly associated with changes in radiologic interpretation.

Use of Artificial Intelligence for Reducing Unnecessary Recalls at Screening Mammography: A Simulation Study

  • Yeon Soo Kim;Myoung-jin Jang;Su Hyun Lee;Soo-Yeon Kim;Su Min Ha;Bo Ra Kwon;Woo Kyung Moon;Jung Min Chang
    • Korean Journal of Radiology
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    • v.23 no.12
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    • pp.1241-1250
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    • 2022
  • Objective: To conduct a simulation study to determine whether artificial intelligence (AI)-aided mammography reading can reduce unnecessary recalls while maintaining cancer detection ability in women recalled after mammography screening. Materials and Methods: A retrospective reader study was performed by screening mammographies of 793 women (mean age ± standard deviation, 50 ± 9 years) recalled to obtain supplemental mammographic views regarding screening mammography-detected abnormalities between January 2016 and December 2019 at two screening centers. Initial screening mammography examinations were interpreted by three dedicated breast radiologists sequentially, case by case, with and without AI aid, in a single session. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and recall rate for breast cancer diagnosis were obtained and compared between the two reading modes. Results: Fifty-four mammograms with cancer (35 invasive cancers and 19 ductal carcinomas in situ) and 739 mammograms with benign or negative findings were included. The reader-averaged AUC improved after AI aid, from 0.79 (95% confidence interval [CI], 0.74-0.85) to 0.89 (95% CI, 0.85-0.94) (p < 0.001). The reader-averaged specificities before and after AI aid were 41.9% (95% CI, 39.3%-44.5%) and 53.9% (95% CI, 50.9%-56.9%), respectively (p < 0.001). The reader-averaged sensitivity was not statistically different between AI-unaided and AI-aided readings: 89.5% (95% CI, 83.1%-95.9%) vs. 92.6% (95% CI, 86.2%-99.0%) (p = 0.053), although the sensitivities of the least experienced radiologists before and after AI aid were 79.6% (43 of 54 [95% CI, 66.5%-89.4%]) and 90.7% (49 of 54 [95% CI, 79.7%-96.9%]), respectively (p = 0.031). With AI aid, the reader-averaged recall rate decreased by from 60.4% (95% CI, 57.8%-62.9%) to 49.5% (95% CI, 46.5%-52.4%) (p < 0.001). Conclusion: AI-aided reading reduced the number of recalls and improved the diagnostic performance in our simulation using women initially recalled for supplemental mammographic views after mammography screening.