Management of gynaecologic plasmacytoma: A review article.

In contrast to multiple myeloma (MM) which exhibits diffuse bone marrow and other organ involvement, solitary plasmacytomas carry a favourable prognosis. Extramedullary plasmacytomas (EMP) are a unique form of plasma cell neoplasms. These tumours are rare in the female reproductive tract. Only 24 cases of gynaecologic plasmacytomas were reported to date (7 cases were solitary plasmacytomas and 17 cases were either part of disseminated MM with involvement of a gynaecologic organ or were lacking complete work-up to rule out MM). The standard care of gynaecologic solitary EMP is surgical resection alone when feasible. Adjuvant radiation therapy may be considered for adverse prognostic factors such as positive resection margins. MM with gynaecologic organ involvement should be managed with systemic therapy and defer local therapies to symptomatic progression.

An Analysis of Clinical Toxic Effects and Quality of Life as a Function of Radiation Dose and Volume After Lung Stereotactic Body Radiation Therapy.

PURPOSE: To analyze clinical toxicity and quality-of-life (QOL) outcomes among patients with stage I non-small cell lung cancer (NSCLC) after stereotactic body radiation therapy (SBRT) as a function of radiation dose and volume parameters. METHODS AND MATERIALS: In this institutional review board-approved study, 55 patients with stage I NSCLC who received SBRT (12 Gy × 4) and completed QOL forms were analyzed. Clinical symptoms and QOL outcomes were measured at baseline and at 3, 6, 12, 18, 24, and 36 months after SBRT. Clinical toxicity was graded using the Common Terminology Criteria for Adverse Events, version 4.0. Quality of life was followed using the validated Functional Assessment of Cancer Therapy-Lung-Trial Outcome Index (FACT-L-TOI) instrument. Dosimetric parameters including the mean lung radiation dose and the volume of normal lung receiving greater than 5, 10, 13, or 20 Gy (V5, V10, V13, and V20) were measured from the radiation treatment plan. Student t tests and Pearson correlation analyses were used to examine the relationships between radiation lung metrics and clinically meaningful changes in QOL and/or clinical toxic effects. The Kaplan-Meier method was used to estimate rates of local control (LC), disease-free survival (DFS), and overall survival (OS). RESULTS: With a median follow-up of 24 months, the 3-year LC, DFS, and OS were 93%, 65%, and 84%, respectively, with a 5.5% rate of grade-3 toxic effects and no grade 4 or 5 toxic effects. Clinically meaningful declines in patient-reported QOL (FACT-L-TOI, lung cancer subscale, physical well-being, and/or functional well-being) posttreatment significantly correlated with increased dosimetric parameters such as V10, V13, and V20. CONCLUSION: Although lung SBRT was associated with excellent LC and minimal clinical toxic effects for early-stage NSCLC, clinically meaningful declines in QOL were significantly correlated with increasing lung dose and volume parameters.

A Grade I Intracranial Meningioma with Metastasis to Multiple Vertebral Bodies: A Case Report and Literature Review.

World Health Organization (WHO) grade I meningiomas are slow-growing and typically benign brain tumors that can often be easily removed by surgery and rarely become malignant. We report the case of a WHO grade I meningioma in a 67-year-old man with multiple extracranial metastases.

A deep dive into understanding tumor foci classification using multiparametric MRI based on convolutional neural network.

PURPOSE: Deep learning models have had a great success in disease classifications using large data pools of skin cancer images or lung X-rays. However, data scarcity has been the roadblock of applying deep learning models directly on prostate multiparametric MRI (mpMRI). Although model interpretation has been heavily studied for natural images for the past few years, there has been a lack of interpretation of deep learning models trained on medical images. In this paper, an efficient convolutional neural network (CNN) was developed and the model interpretation at various convolutional layers was systematically analyzed to improve the understanding of how CNN interprets multimodality medical images and the predictive powers of features at each layer. The problem of small sample size was addressed by feeding the intermediate features into a traditional classification algorithm known as weighted extreme learning machine (wELM), with imbalanced distribution among output categories taken into consideration. METHODS: The training data collection used a retrospective set of prostate MR studies, from SPIE-AAPM-NCI PROSTATEx Challenges held in 2017. Three hundred twenty biopsy samples of lesions from 201 prostate cancer patients were diagnosed and identified as clinically significant (malignant) or not significant (benign). All studies included T2-weighted (T2W), proton density-weighted (PD-W), dynamic contrast enhanced (DCE) and diffusion-weighted (DW) imaging. After registration and lesion-based normalization, a CNN with four convolutional layers were developed and trained on tenfold cross validation. The features from intermediate layers were then extracted as input to wELM to test the discriminative power of each individual layer. The best performing model from the tenfolds was chosen to be tested on the holdout cohort from two sources. Feature maps after each convolutional layer were then visualized to monitor the trend, as the layer propagated. Scatter plotting was used to visualize the transformation of data distribution. Finally, a class activation map was generated to highlight the region of interest based on the model perspective. RESULTS: Experimental trials indicated that the best input for CNN was a modality combination of T2W, apparent diffusion coefficient (ADC) and DWIb50 . The convolutional features from CNN paired with a weighted extreme learning classifier showed substantial performance compared to a CNN end-to-end training model. The feature map visualization reveals similar findings on natural images where lower layers tend to learn lower level features such as edges, intensity changes, etc, while higher layers learn more abstract and task-related concept such as the lesion region. The generated saliency map revealed that the model was able to focus on the region of interest where the lesion resided and filter out background information, including prostate boundary, rectum, etc. CONCLUSIONS: This work designs a customized workflow for the small and imbalanced dataset of prostate mpMRI where features were extracted from a deep learning model and then analyzed by a traditional machine learning classifier. In addition, this work contributes to revealing how deep learning models interpret mpMRI for prostate cancer patient stratification.

Real-time Magnetic Resonance-guided Liver Stereotactic Body Radiation Therapy: An Institutional Report Using a Magnetic Resonance-Linac System.

Background Stereotactic body radiation therapy (SBRT) is a proven and effective modality for treatment of hepatic primary and metastatic tumors. However, these lesions are challenging for planning and treatment execution due to natural anatomic changes associated with respiration. Magnetic resonance imaging (MRI) offers superior soft tissue contrast resolution and the ability for real-time image-guided treatment delivery and lesion tracking. Objective To evaluate the plan quality, treatment delivery, and tumor response of a set of liver SBRT cancer treatments delivered with magnetic resonance (MR)-guided radiotherapy on a MR-linear accelerator (MR-linac). Methods Treatment data from 29 consecutive patients treated with SBRT were reviewed. All treatments were performed using a step and shoot technique to one or more liver lesions on an MR-linac platform. Patients received 45 to 50 Gy prescribed to at least 95% of the planning target volume (PTV) in five fractions except for two patients who received 27-30 Gy in three fractions. Computed tomography and MRI simulation were performed in the supine position prior to treatment in the free-breathing, end exhalation, and end inhalation breath-hold positions to determine patient tolerability and potential dosimetric advantages of each technique. Immobilization consisted of using anterior and posterior torso MRI receive coils embedded in a medium-sized vacuum cushion. Gating was performed using sagittal cine images acquired at 4 frames/second. Gating boundaries were defined in the three major axes to be 0.3 to 0.5 cm. An overlapping region of interest, defined as the percentage volume allowed outside the boundary for beam-on to occur, was set between 1 and 10%. The contoured target was assigned a 5-mm PTV expansion. Organs at risk constraints adopted by the American Association of Physicists in Medicine Task Group 101 were used during optimization. Results Twenty-nine patients, with a total of 34 lesions, successfully completed the prescribed treatment with minimal treatment breaks or delays. Twenty-one patients were treated at end-exhale, and six were treated at end-inhale. Two patients were treated using a free-breathing technique due to poor compliance with breath-hold instructions. The reported mean liver dose was 5.56 Gy (1.39 - 10.43; STD 2.85) and the reported mean liver volume receiving the prescribed threshold dose was 103.1 cm3 (2.9 - 236.6; STD 75.2). Follow-up imaging at one to 12 months post treatment confirmed either stable or decreased size of treated lesions in all but one patient. Toxicities were mild and included nausea/vomiting, abdominal pain and one case of bloody diarrhea. Four patients died due to complications from liver cirrhosis unrelated to radiation effect. Conclusion SBRT treatment using a gated technique on an MR-linac has been successfully demonstrated. Potential benefits of this modality include decreased liver dose leading to decreased toxicities. Further studies to identify the benefits and risks associated with MR-guided SBRT are necessary.