Deep-Learning Model Prediction of Radiation Pneumonitis Using Pretreatment Chest Computed Tomography and Clinical Factors.

Objectives: This study aimed to build a comprehensive deep-learning model for the prediction of radiation pneumonitis using chest computed tomography (CT), clinical, dosimetric, and laboratory data. Introduction: Radiation therapy is an effective tool for treating patients with lung cancer. Despite its effectiveness, the risk of radiation pneumonitis limits its application. Although several studies have demonstrated models to predict radiation pneumonitis, no reliable model has been developed yet. Herein, we developed prediction models using pretreatment chest CT and various clinical data to assess the likelihood of radiation pneumonitis in lung cancer patients. Methods: This retrospective study analyzed 3-dimensional (3D) lung volume data from chest CT scans and 27 features including dosimetric, clinical, and laboratory data from 548 patients who were treated at our institution between 2010 and 2021. We developed a neural network, named MergeNet, which processes lung 3D CT, clinical, dosimetric, and laboratory data. The MergeNet integrates a convolutional neural network with subsequent fully connected layers. A support vector machine (SVM) and light gradient boosting machine (LGBM) model were also implemented for comparison. For comparison, the convolution-only neural network was implemented as well. Three-dimensional Resnet-10 network and 4-fold cross-validation were used. Results: Classification performance was quantified by using the area under the receiver operative characteristic curve (AUC) metrics. MergeNet showed the AUC of 0.689. SVM, LGBM, and convolution-only networks showed AUCs of 0.525, 0.541, and 0.550, respectively. Application of DeLong test to pairs of receiver operating characteristic curves respectively yielded P values of .001 for the MergeNet-SVM pair and 0.001 for the MergeNet-LGBM pair. Conclusion: The MergeNet model, which incorporates chest CT, clinical, dosimetric, and laboratory data, demonstrated superior performance compared to other models. However, since its prediction performance has not yet reached an efficient level for clinical application, further research is required. Contribution: This study showed that MergeNet may be an effective means to predict radiation pneumonitis. Various predictive factors can be used together for the radiation pneumonitis prediction task via the MergeNet.

Comparing deep learning and handcrafted radiomics to predict chemoradiotherapy response for locally advanced cervical cancer using pretreatment MRI.

Concurrent chemoradiotherapy (CRT) is the standard treatment for locally advanced cervical cancer (LACC), but its responsiveness varies among patients. A reliable tool for predicting CRT responses is necessary for personalized cancer treatment. In this study, we constructed prediction models using handcrafted radiomics (HCR) and deep learning radiomics (DLR) based on pretreatment MRI data to predict CRT response in LACC. Furthermore, we investigated the potential improvement in prediction performance by incorporating clinical factors. A total of 252 LACC patients undergoing curative chemoradiotherapy are included. The patients are randomly divided into two independent groups for the training (167 patients) and test datasets (85 patients). Contrast-enhanced T1- and T2-weighted MR scans are obtained. For HCR analysis, 1890 imaging features are extracted and a support vector machine classifier with a five-fold cross-validation is trained on training dataset to predict CRT response and subsequently validated on test dataset. For DLR analysis, a 3-dimensional convolutional neural network was trained on training dataset and validated on test dataset. In conclusion, both HCR and DLR models could predict CRT responses in patients with LACC. The integration of clinical factors into radiomics prediction models tended to improve performance in HCR analysis. Our findings may contribute to the development of personalized treatment strategies for LACC patients.

Predictive factors for severe radiation-induced lung injury in patients with lung cancer and coexisting interstitial lung disease.

BACKGROUND AND PURPOSE: This study aimed to investigate the predictive factors of severe radiation-induced lung injury (RILI) in patients with lung cancer and coexisting interstitial lung disease (ILD) undergoing conventionally fractionated thoracic radiotherapy. MATERIALS AND METHODS: The study includes consecutive patients treated with thoracic radiotherapy for lung cancer at two tertiary centers between 2010 and 2021. RILI severity was graded using the National Cancer Institute Common Terminology Criteria version 5.0, with severe RILI defined as toxicity grade ≥4, and symptomatic RILI as grade ≥2. The absolute neutrophil count (ANC), absolute lymphocyte count (ALC), and C-reactive protein were collected within 4 weeks before starting radiotherapy. Neutrophil-lymphocyte ratios (NLR) were calculated as ANC/ALC. The median follow-up was 9 (range, 6-114) months. RESULTS: Among 54 patients, 22 (40.7 %) had severe RILI. On multivariate logistic regression analysis, high pretreatment ANC (p = 0.030, OR = 4.313), pretreatment NLR (p = 0.007, OR = 5.784), and ILD severity (p = 0.027, OR = 2.416) were significant predictors of severe RILI. Dosimetric factors were not associated with severe RP. Overall survival was significantly worse for patients with severe RILI than those without, with 1-year cumulative overall survival rates of 7.4 % and 62.8 %, respectively. CONCLUSION: Pretreatment blood NLR, ANC, and ILD severity were associated with severe RILI. Overall survival was dismal for patients with severe RILI.

Nanocrystalline Composite Layer Realized by Simple Sintering Without Surface Treatment, Reducing Hydrophilicity and Increasing Thermal Conductivity.

The surface treatment for a polymer-ceramic composite is additionally performed in advanced material industries. To prepare the composite without a surface treatment, the simplest way to manufacture an advanced ceramic-particle is devised. The method is the formation of a nanocrystalline composite layer through the simple liquid-phase sintering. Using magnesia (MgO) which shows hydrophilicity, a nanocrystalline surface layer is realized by liquid-phase sintering. The amorphous matrix of nanocrystalline composite layer makes MgO hydrophobic and ensures miscibility with polymers, and the nanocrystalline MgO ensures high thermal conductivity. In addition, the liquid phase removes the open pores and makes the surface morphology smooth MgO with smooth surface (MgO-SM). Thermal interface materials (TIM) prepared with MgO-SM and epoxy show a high thermal conductivity of ≈7.5 W m-1 K-1 , which is significantly higher than 4.5 W m-1 K-1 of pure MgO TIM. Consequently, the formation process of a nanocrystalline surface layer utilizing simple liquid-phase sintering is proposed as a fabrication method for a next-generation ceramic-filler. In addition, it is fundamentally identified that the thermal conductivity of MgO depends on the Mg deficiency, and therefore a poly-crystal MgO-SM (produced at a low temperature) has a higher thermal conductivity than a single-crystal MgO (produced at a high temperature).

Recent achievements toward the development of Ni-based layered oxide cathodes for fast-charging Li-ion batteries.

The driving mileage of electric vehicles (EVs) has been substantially improved in recent years with the adoption of Ni-based layered oxide materials as the battery cathode. The average charging period of EVs is still time-consuming, compared with the short refueling time of an internal combustion engine vehicle. With the guidance from the United States Department of Energy, the charging time of refilling 60% of the battery capacity should be less than 6 min for EVs, indicating that the corresponding charging rate for the cathode materials is to be greater than 6C. However, the sluggish kinetic conditions and insufficient thermal stability of the Ni-based layered oxide materials hinder further application in fast-charging operations. Most of the recent review articles regarding Ni-based layered oxide materials as cathodes for lithium-ion batteries (LIBs) only touch degradation mechanisms under slow charging conditions. Of note, the fading mechanisms of the cathode materials for fast-charging, of which the importance abruptly increases due to the development of electric vehicles, may be significantly different from those of slow charging conditions. There are a few review articles regarding fast-charging; however, their perspectives are limited mostly to battery thermal management simulations, lacking experimental validations such as microscale structure degradations of Ni-based layered oxide cathode materials. In this review, a general and fundamental definition of fast-charging is discussed at first, and then we summarize the rate capability required in EVs and the electrochemical and kinetic properties of Ni-based layered oxide cathode materials. Next, the degradation mechanisms of LIBs leveraging Ni-based cathodes under fast-charging operation are systematically discussed from the electrode scale to the particle scale and finally the atom scale (lattice oxygen-level investigation). Then, various strategies to achieve higher rate capability, such as optimizing the synthesis process of cathode particles, fabricating single-crystalline particles, employing electrolyte additives, doping foreign ions, coating protective layers, and engineering the cathode architecture, are detailed. All these strategies need to be considered to enhance the electrochemical performance of Ni-based oxide cathode materials under fast-charging conditions.

Explainable Artificial Intelligence and Wearable Sensor-Based Gait Analysis to Identify Patients with Osteopenia and Sarcopenia in Daily Life.

Osteopenia and sarcopenia can cause various senile diseases and are key factors related to the quality of life in old age. There is need for portable tools and methods that can analyze osteopenia and sarcopenia risks during daily life, rather than requiring a specialized hospital setting. Gait is a suitable indicator of musculoskeletal diseases; therefore, we analyzed the gait signal obtained from an inertial-sensor-based wearable gait device as a tool to manage bone loss and muscle loss in daily life. To analyze the inertial-sensor-based gait, the inertial signal was classified into seven gait phases, and descriptive statistical parameters were obtained for each gait phase. Subsequently, explainable artificial intelligence was utilized to analyze the contribution and importance of descriptive statistical parameters on osteopenia and sarcopenia. It was found that XGBoost yielded a high accuracy of 88.69% for osteopenia, whereas the random forest approach showed a high accuracy of 93.75% for sarcopenia. Transfer learning with a ResNet backbone exhibited appropriate performance but showed lower accuracy than the descriptive statistical parameter-based identification result. The proposed gait analysis method confirmed high classification accuracy and the statistical significance of gait factors that can be used for osteopenia and sarcopenia management.

Predicting Tumor Budding Status in Cervical Cancer Using MRI Radiomics: Linking Imaging Biomarkers to Histologic Characteristics.

BACKGROUND: Our previous study demonstrated that tumor budding (TB) status was associated with inferior overall survival in cervical cancer. The purpose of this study is to evaluate whether radiomic features can predict TB status in cervical cancer patients. METHODS: Seventy-four patients with cervical cancer who underwent preoperative MRI and radical hysterectomy from 2011 to 2015 at our institution were enrolled. The patients were randomly allocated to the training dataset (n = 48) and test dataset (n = 26). Tumors were segmented on axial gadolinium-enhanced T1- and T2-weighted images. A total of 2074 radiomic features were extracted. Four machine learning classifiers, including logistic regression (LR), random forest (RF), support vector machine (SVM), and neural network (NN), were used. The trained models were validated on the test dataset. RESULTS: Twenty radiomic features were selected; all were features from filtered-images and 85% were texture-related features. The area under the curve values and accuracy of the models by LR, RF, SVM and NN were 0.742 and 0.769, 0.782 and 0.731, 0.849 and 0.885, and 0.891 and 0.731, respectively, in the test dataset. CONCLUSION: MRI-based radiomic features could predict TB status in patients with cervical cancer.

Mapping patterns of para-aortic lymph node recurrence in cervical cancer: a retrospective cohort analysis.

BACKGROUND: To map anatomic patterns of para-aortic lymph node (PALN) recurrence in cervical cancer patients and validate currently available guidelines on PA clinical target volumes (CTV). METHODS: Cervical cancer patients who developed PALN recurrence were included. The PALNs were classified as left-lateral para-aortic (LPA), aorto-caval (AC), and right para-caval (RPC). Four PA CTVs were contoured for each patient to validate PALN coverage. CTVRTOG was contoured based on the Radiation Therapy Oncology Group guideline. CTVK was contoured as proposed by Keenan et al. CTVM was contoured by expanding symmetrical margins around the aorta and inferior vena cava of 7 mm up to the T12-L1 interspace. CTVnew was created by modifying CTVRTOG to obtain better coverage. RESULTS: We identified 92 PALNs in 35 cervical cancer patients. 46.8% of the PALNs were at LPA, 38.0% were at AC, and 15.2% were at RPC areas. CTVRTOG, CTVK, and CTVM covered 87.0%, 88.0%, and 62.0% of all PALNs, respectively. PALN recurrence above the left renal vein was associated with PALN involvement at diagnosis (p = 0.043). Extending upper border to the superior mesenteric artery allowed the CTVnew to cover 96.7% of all PALNs and all nodes in 91.4% of patients. CONCLUSION: CTVRTOG and CTVK encompassed most PALN recurrences. For high-risk patients, such as those having PALN involvement at diagnosis, extending the superior border of CTV from the left renal vein to superior mesenteric artery could be considered.

Robustness of magnetic resonance radiomic features to pixel size resampling and interpolation in patients with cervical cancer.

BACKGROUND: Radiomics is a promising field in oncology imaging. However, the implementation of radiomics clinically has been limited because its robustness remains unclear. Previous CT and PET studies suggested that radiomic features were sensitive to variations in pixel size and slice thickness of the images. The purpose of this study was to assess robustness of magnetic resonance (MR) radiomic features to pixel size resampling and interpolation in patients with cervical cancer. METHODS: This retrospective study included 254 patients with a pathological diagnosis of cervical cancer stages IB to IVA who received definitive chemoradiation at our institution between January 2006 and June 2020. Pretreatment MR scans were analyzed. Each region of cervical cancer was segmented on the axial gadolinium-enhanced T1- and T2-weighted images; 107 radiomic features were extracted. MR scans were interpolated and resampled using various slice thicknesses and pixel spaces. Intraclass correlation coefficients (ICCs) were calculated between the original images and images that underwent pixel size resampling (OP), interpolation (OI), or pixel size resampling and interpolation (OP+I) as well as among processed image sets with various pixel spaces (P), various slice thicknesses (I), and both (P + I). RESULTS: After feature standardization, ≥86.0% of features showed good robustness when compared between the original and processed images (OP, OI, and OP+I) and ≥ 88.8% of features showed good robustness when processed images were compared (P, I, and P + I). Although most first-order, shape, and texture features showed good robustness, GLSZM small-area emphasis-related features and NGTDM strength were sensitive to variations in pixel size and slice thickness. CONCLUSION: Most MR radiomic features in patients with cervical cancer were robust after pixel size resampling and interpolation following the feature standardization process. The understanding regarding the robustness of individual features after pixel size resampling and interpolation could help future radiomics research.

Initial experience of preoperative short-course radiotherapy followed by oxaliplatin-based consolidation chemotherapy for locally advanced rectal cancer.

PURPOSE: We analyzed the safety and feasibility of preoperative short-course radiotherapy (SCRT) followed by consolidation chemotherapy for patients with locally advanced rectal cancer (LARC). METHODS: From April 2018 to May 2019, 19 patients with LARC were treated with SCRT followed by three cycles of consolidation chemotherapy with leucovorin, fluorouracil, and oxaliplatin (FOLFOX6) before surgery. Adjuvant chemotherapy relied on oxaliplatin. Tumor response, patient compliance, and toxicities were analyzed. RESULTS: The median age was 60 years (range 44-71), and 16 of the patients were male. The median tumor height was 5 cm (range 0-9) from anal verge. All patients received a total dose of 25 Gy in five fractions. The number of cycles of FOLFOX6 before surgery was three in 17, four in one, five in one. Five patients required dose reductions in consolidation chemotherapy. The median interval between initiation of SCRT and surgery was 10.6 weeks (range 8.6-16.4). A pathologic complete response was seen in two patients (11%). Grade III toxicities to the preoperative treatment were seen in five patients (26%): diarrhea in two, a decreased white blood cell count in one, and anemia in two. Postoperative complications arising within 30 days developed in five patients (26%). During the median follow-up period of 20.4 months, there was no tumor recurrence. CONCLUSION: Preoperative SCRT followed by oxaliplatin-based consolidation chemotherapy showed acceptable toxicity and feasibility in patients with LARC. Prospective randomized trials are warranted to verify the efficacy and safety of this treatment strategy compared with conventional long-course concurrent chemoradiotherapy.

A solid-state route to stabilize cubic Li7La3Zr2O12 at low temperature for all-solid-state-battery applications.

The integration of a solid electrolyte with electrodes without interfacial degradation is an integral part of enabling high-performance all-solid-state batteries. Here we highlight that additive-assisted solid-state reactions using high-energy ball-milling and multistep heating can be an effective approach to lower the processing temperatures of cubic Li7La3Zr2O12 garnet. The obtained total Li conductivity is 1.4 × 10-4 S cm-1, comparable with that obtained using high-temperature processing. We found that liquid-phase sintering triggered by a lithium borate additive increases the microstrain of Li7La3Zr2O12, increasing Li conductivity. Our work demonstrates the feasibility to engineer conventional ceramics processing to sustainably produce all-solid-state batteries with a low thermal budget in practice.

Lithium and Chlorine-Rich Preparation of Mechanochemically Activated Antiperovskite Composites for Solid-State Batteries.

Assembling all-solid-state batteries presents a unique challenge due to chemical and electrochemical complexities of interfaces between a solid electrolyte and electrodes. While the interface stability is dictated by thermodynamics, making use of passivation materials often delays interfacial degradation and extends the cycle life of all-solid cells. In this work, we investigated antiperovskite lithium oxychloride, Li3OCl, as a promising passivation material that can engineer the properties of solid electrolyte-Li metal interfaces. Our experiment to obtain stoichiometric Li3OCl focuses on how the starting ratios of lithium and chlorine and mechanochemical activation affect the phase stability. For substantial LiCl excess conditions, the antiperovskite phase was found to form by simple melt-quenching and subsequent high-energy ball-milling. Li3OCl prepared with 100% excess LiCl exhibits ionic conductivity of 3.2 × 10-5 S cm-1 at room temperature, as well as cathodic stability against Li metal upon the extended number of cycling. With a conductivity comparable to other passivation layers, and stable interface properties, our Li3OCl/LiCl composite has the potential to stably passivate the solid-solid interfaces in all-solid-state batteries.

Regional nodal irradiation in pT1-2N1 breast cancer patients treated with breast-conserving surgery and whole breast irradiation.

PURPOSE: To evaluate the necessity of regional nodal irradiation (RNI) for pT1-2N1 breast cancer patients treated with breast-conserving surgery and radiotherapy, we compared clinical outcomes of patients treated with and without RNI. MATERIALS AND METHODS: We retrospectively analyzed the data of 214 pT1-2N1 breast cancer patients treated with breast-conserving surgery and whole breast irradiation from 2009-2016. There were 142 (66.4%), 51 (23.85%), and 21 (9.8%) patients with one, two, and three positive lymph nodes, respectively. Thirty-six patients (16.8%) underwent RNI. Adjuvant chemotherapy, endocrine therapy, and anti-HER2 therapy were given to 91.6%, 79.0%, and 15.0% patients, respectively. The most common chemotherapy regimen was anthracycline + cyclophosphamide, followed by taxane (76.5%). The median follow-up was 64 months (range, 6 to 147 months). Patients were propensity matched 1:2 into RNI and no-RNI groups. RESULTS: Two patients experienced locoregional recurrences simultaneously with distant metastases, ten patients developed distant metastases, and one patient died. Before matching, the 5-year actuarial locoregional control (LRC), distant metastasis-free survival (DMFS), and overall survival (OS) rates in the RNI and no-RNI groups were 100.0% and 99.4% (p = 0.629), 94.1% and 96.0% (p = 0.676), and 100.0% and 99.4% (p = 0.658), respectively. After matching, the 5-year LRC, DMFS, and OS were 98.3% and 100.0% (p = 0.455), 96.6% and 93.9% (p = 0.557), and 100.0% and 100.0% (p > 0.999) in the RNI and no-RNI groups, respectively. No clinicopathologic or treatment-related factors were significantly associated with LRC, DMFS, or OS. CONCLUSION: Adding RNI did not show superior LRC, DMFS, or OS in pT1-2N1 breast cancer patients.

Magnetic resonance imaging features of tumor and lymph node to predict clinical outcome in node-positive cervical cancer: a retrospective analysis.

BACKGROUND: Current chemoradiation regimens for locally advanced cervical cancer are fairly uniform despite a profound diversity of treatment response and recurrence patterns. The wide range of treatment responses and prognoses to standardized concurrent chemoradiation highlights the need for a reliable tool to predict treatment outcomes. We investigated pretreatment magnetic resonance (MR) imaging features of primary tumor and involved lymph node for predicting clinical outcome in cervical cancer patients. METHODS: We included 93 node-positive cervical cancer patients treated with definitive chemoradiotherapy at our institution between 2006 and 2017. The median follow-up period was 38 months (range, 5-128). Primary tumor and involved lymph node were manually segmented on axial gadolinium-enhanced T1-weighted images as well as T2-weighted images and saved as 3-dimensional regions of interest (ROI). After the segmentation, imaging features related to histogram, shape, and texture were extracted from each ROI. Using these features, random survival forest (RSF) models were built to predict local control (LC), regional control (RC), distant metastasis-free survival (DMFS), and overall survival (OS) in the training dataset (n = 62). The generated models were then tested in the validation dataset (n = 31). RESULTS: For predicting LC, models generated from primary tumor imaging features showed better predictive performance (C-index, 0.72) than those from lymph node features (C-index, 0.62). In contrast, models from lymph nodes showed superior performance for predicting RC, DMFS, and OS compared to models of the primary tumor. According to the 3-year time-dependent receiver operating characteristic analysis of LC, RC, DMFS, and OS prediction, the respective area under the curve values for the predicted risk of the models generated from the training dataset were 0.634, 0.796, 0.733, and 0.749 in the validation dataset. CONCLUSIONS: Our results suggest that tumor and lymph node imaging features may play complementary roles for predicting clinical outcomes in node-positive cervical cancer.

Hidden structural and chemical order controls lithium transport in cation-disordered oxides for rechargeable batteries.

Structure plays a vital role in determining materials properties. In lithium ion cathode materials, the crystal structure defines the dimensionality and connectivity of interstitial sites, thus determining lithium ion diffusion kinetics. In most conventional cathode materials that are well-ordered, the average structure as seen in diffraction dictates the lithium ion diffusion pathways. Here, we show that this is not the case in a class of recently discovered high-capacity lithium-excess rocksalts. An average structure picture is no longer satisfactory to understand the performance of such disordered materials. Cation short-range order, hidden in diffraction, is not only ubiquitous in these long-range disordered materials, but fully controls the local and macroscopic environments for lithium ion transport. Our discovery identifies a crucial property that has previously been overlooked and provides guidelines for designing and engineering cation-disordered cathode materials.

Evaluation of the hybrid-dynamic conformal arc therapy technique for radiotherapy of lung cancer.

PURPOSE: A hybrid-dynamic conformal arc therapy (HDCAT) technique consisting of a single half-rotated dynamic conformal arc beam and static field-in-field beams in two directions was designed and evaluated in terms of dosimetric benefits for radiotherapy of lung cancer. MATERIALS AND METHODS: This planning study was performed in 20 lung cancer cases treated with the VERO system (BrainLAB AG, Feldkirchen, Germany). Dosimetric parameters of HDCAT plans were compared with those of three-dimensional conformal radiotherapy (3D-CRT) plans in terms of target volume coverage, dose conformity, and sparing of organs at risk. RESULTS: HDCAT showed better dose conformity compared with 3D-CRT (conformity index: 0.74 ± 0.06 vs. 0.62 ± 0.06, p < 0.001). HDCAT significantly reduced the lung volume receiving more than 20 Gy (V20: 21.4% ± 8.2% vs. 24.5% ± 8.8%, p < 0.001; V30: 14.2% ± 6.1% vs. 15.1% ± 6.4%, p = 0.02; V40: 8.8% ± 3.9% vs. 10.3% ± 4.5%, p < 0.001; and V50: 5.7% ± 2.7% vs. 7.1% ± 3.2%, p < 0.001), V40 and V50 of the heart (V40: 5.2 ± 3.9 Gy vs. 7.6 ± 5.5 Gy, p < 0.001; V50: 1.8 ± 1.6 Gy vs. 3.1 ± 2.8 Gy, p = 0.001), and the maximum spinal cord dose (34.8 ± 9.4 Gy vs. 42.5 ± 7.8 Gy, p < 0.001) compared with 3D-CRT. CONCLUSION: HDCAT could achieve highly conformal target coverage and reduce the doses to critical organs such as the lung, heart, and spinal cord compared to 3D-CRT for the treatment of lung cancer patients.

Prognostic significance of residual lymph node status after definitive chemoradiotherapy in patients with node-positive cervical cancer.

OBJECTIVE: Lymph node involvement is an important prognostic factor in patients with cervical cancer. However, the prognostic significance of lymph node response to chemoradiotherapy remains unclear. We retrospectively analyzed the relationship between residual lymph node status after definitive chemoradiotherapy and survival. METHODS: We enrolled 117 patients with node-positive cervical cancer. All patients were treated with definitive chemoradiotherapy in our institution, from 2006 to 2016. The median follow-up period was 41months (range, 6-128months). The criterion for a positive lymph node was defined as a maximum short axis diameter of ≥8mm on pretreatment magnetic resonance imaging (MRI)/computed tomography (CT) scans. Posttreatment pelvic MRI was obtained 3months after the completion of chemoradiotherapy. Residual primary tumor was defined as any residual lesion identified upon clinical examination and/or MRI. Residual lymph node was defined as any lymph node with a short axis diameter of ≥8mm posttreatment, according to MRI/CT. RESULTS: At follow-up, 3months after chemoradiotherapy, we observed residual primary tumor in 30 patients (25.6%), and residual lymph node in 31 patients (26.5%). The presence of residual lymph node was associated with worse overall survival according to multivariate analysis (hazard ratio, 3.04; 95% confidence interval, 1.43-6.44; p=0.004). In the 5-year time-dependent ROC analysis of survival prediction, the presence of residual lymph node showed an AUC value of 0.72. CONCLUSIONS: The presence of residual lymph node after chemoradiotherapy was associated with worse survival in patients with node-positive cervical cancer.

Local and regional recurrence following mastectomy in breast cancer patients with 1-3 positive nodes: implications for postmastectomy radiotherapy volume.

PURPOSE: To determine the necessity of postmastectomy radiotherapy (PMRT) and which regions would be at risk for recurrence, we evaluated local and regional recurrence in breast cancer patients with 1-3 positive nodes and a tumor size of <5 cm. MATERIALS AND METHODS: We retrospectively analyzed data of 133 female breast cancer patients with 1-3 positive nodes, and a tumor size of <5 cm who were treated with mastectomy followed by adjuvant systemic therapy between 2007 and 2016. The median follow-up period was 57 months (range, 12 to 115 months). Most patients (82.7%) were treated with axillary lymph node dissection. Adjuvant chemotherapy, endocrine therapy, and trastuzumab therapy were administered to 124 patients (93.2%), 112 (84.2%), and 33 (24.8%), respectively. The most common chemotherapy regimen was anthracycline and cyclophosphamide followed by taxane (71.4%). RESULTS: Three patients (2.3%), 8 (6.0%), and 12 (9.0%) experienced local, regional, and distant failures, respectively. The 5-year cumulative risk of local recurrence, regional recurrence, distant metastasis, and disease-free survival was 3.1%, 8.0%, 11.7%, and 83.4%, respectively. There were no statistically significant clinicopathologic factors associated with local recurrence. Lymphovascular invasion (univariate p = 0.015 and multivariate p = 0.054) was associated with an increased risk of regional recurrence. CONCLUSION: Our study showed a very low local recurrence in patients with 1-3 positive nodes and tumor size of <5 cm who were treated with mastectomy and modern adjuvant systemic treatment. The PMRT volume need to be tailored for each patient's given risk for local and regional recurrence, and possible radiation-related toxicities.

Prognostic value of intratumoral metabolic heterogeneity on F-18 fluorodeoxyglucose positron emission tomography/computed tomography in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy.

OBJECTIVE: To evaluate the prognostic value for predicting tumor recurrence of intratumoral metabolic heterogeneity and traditional quantitative metabolic parameters on pre-treatment F-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy (CCRT). MATERIALS AND METHODS: Ninety-three patients with biopsy-proven cervical cancer and treated with CCRT (FIGO stage IIB-IV) were enrolled in this study. The traditional metabolic parameters of the primary tumor, regional lymph node, and whole body (maximum standardized uptake value [SUVmax], metabolic tumor volume [MTV], and total lesion glycolysis), and intratumoral heterogeneity factor (HF) were measured on pre-treatment 18F-FDG PET/CT images. Univariate and multivariate analyses for disease-free survival (DFS) were performed using clinical and metabolic parameters. The additional HF prognostic value was evaluated by means of time-dependent receiver operating characteristic curve, integrated discrimination improvement, and net reclassification improvement. RESULTS: On multivariate analysis, nodal SUVmax (hazard ratio 3.60; 95% CI, 1.66-7.85; p = 0.0012) and whole body MTV (WBMTV; hazard ratio 3.15; 95% CI, 1.17-8.53; p = 0.0236) were significant prognostic factors for DFS. When HF was combined with nodal SUVmax and WBMTV, a significant improvement in discrimination for recurrence was observed compared with nodal SUVmax alone (area under curve 0.817 vs. 0.732; p = 0.0028). CONCLUSIONS: HF did not show superiority over traditional metabolic parameters. However, when HF was combined with nodal SUVmax and WBMTV, the predictive value for tumor recurrence improved. Therefore, HF may be a useful additional prognostic biomarker to improve the prognostic value of traditional metabolic parameters on 18F-FDG PET/CT.

Simultaneous integrated boost intensity-modulated radiotherapy versus 3-dimensional conformal radiotherapy in preoperative concurrent chemoradiotherapy for locally advanced rectal cancer.

PURPOSE: To evaluate the feasibility of simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT) for preoperative concurrent chemoradiotherapy (PCRT) in locally advanced rectal cancer (LARC), by comparing with 3-dimensional conformal radiotherapy (3D-CRT). MATERIALS AND METHODS: Patients who were treated with PCRT for LARC from 2015 January to 2016 December were retrospectively enrolled. Total doses of 45 Gy to 50.4 Gy with 3D-CRT or SIB-IMRT were administered concomitantly with 5-fluorouracil plus leucovorin or capecitabine. Surgery was performed 8 weeks after PCRT. Between PCRT and surgery, one cycle of additional chemotherapy was administered. Pathologic tumor responses were compared between SIB-IMRT and 3D-CRT groups. Acute gastrointestinal, genitourinary, hematologic, and skin toxicities were compared between the two groups based on the RTOG toxicity criteria. RESULTS: SIB-IMRT was used in 53 patients, and 3D-CRT in 41 patients. After PCRT, no significant differences were noted in tumor responses, pathologic complete response (9% vs. 7%; p = 1.000), pathologic tumor regression Grade 3 or higher (85% vs. 71%; p = 0.096), and R0 resection (87% vs. 85%; p = 0.843). Grade 2 genitourinary toxicities were significantly lesser in the SIB-IMRT group (8% vs. 24%; p = 0.023), but gastrointestinal toxicities were not different across the two groups. CONCLUSION: SIB-IMRT showed lower GU toxicity and similar tumor responses when compared with 3D-CRT in PCRT for LARC.