The Role of Imaging and Systemic Treatments in Myeloma: A Primer for Radiologists.

OBJECTIVE. The purpose of this article is to provide an up-to-date guide for radiologists on imaging and systemic therapies in myeloma and related conditions, with a focus on radiologic findings for diagnosis and treatment response assessment. CONCLUSION. Knowledge of the unique imaging presentations of myeloma is highly useful for radiologists. An understanding of the utility of different imaging modalities and the systemic therapies used in multiple myeloma is also critical in the realm of oncologic imaging.

Moral principles in May's Regard for Reason in the Moral Mind.

Joshua May offers four principles that might serve as the rational foundations of moral judgments. I argue that these principles, if they are independent of affect, are too weak to be the basis of any substantive moral judgment and do not fit with the idea that morality is categorical.

Cellular Models of Aggregation-dependent Template-directed Proteolysis to Characterize Tau Aggregation Inhibitors for Treatment of Alzheimer Disease.

Alzheimer disease (AD) is a degenerative tauopathy characterized by aggregation of Tau protein through the repeat domain to form intraneuronal paired helical filaments (PHFs). We report two cell models in which we control the inherent toxicity of the core Tau fragment. These models demonstrate the properties of prion-like recruitment of full-length Tau into an aggregation pathway in which template-directed, endogenous truncation propagates aggregation through the core Tau binding domain. We use these in combination with dissolution of native PHFs to quantify the activity of Tau aggregation inhibitors (TAIs). We report the synthesis of novel stable crystalline leucomethylthioninium salts (LMTX®), which overcome the pharmacokinetic limitations of methylthioninium chloride. LMTX®, as either a dihydromesylate or a dihydrobromide salt, retains TAI activity in vitro and disrupts PHFs isolated from AD brain tissues at 0.16 µM. The Ki value for intracellular TAI activity, which we have been able to determine for the first time, is 0.12 µM. These values are close to the steady state trough brain concentration of methylthioninium ion (0.18 µM) that is required to arrest progression of AD on clinical and imaging end points and the minimum brain concentration (0.13 µM) required to reverse behavioral deficits and pathology in Tau transgenic mice.

Reducing Barriers and Strategies to Improve Appropriate Screening Mammogram Attendance in Women 75 Years and Older.

Although breast cancer death rates have persistently declined over the last 3 decades, older women have not experienced the same degree in mortality reduction as younger women despite having more favorable breast cancer phenotypes. This occurrence can be partially attributed to less robust mammographic screening in older women, the propensity to undertreat with advancing age, and the presence of underlying comorbidities. With recent revisions to breast cancer screening guidelines, there has been a constructive shift toward more agreement in the need for routine mammographic screening to commence at age 40. Unfortunately, this shift in agreement has not occurred for cutoff guidelines, wherein the recommendations are blurred and open to interpretation. With increasing life expectancy and an aging population who is healthier now than any other time in history, it is important to revisit mammographic screening with advanced age and understand why older women who should undergo screening are not being screened as well as offer suggestions on how to improve screening mammogram attendance in this population.

Real-World Performance of Pneumothorax-Detecting Artificial Intelligence Algorithm and its Impact on Radiologist Reporting Times.

RATIONALE AND OBJECTIVES: Artificial intelligence (AI) algorithms in radiology capable of detecting urgent findings have gained significant traction in recent years, but the impact of these algorithms on real-world clinical practice remains unclear with need for scientific investigation. Our study investigates the diagnostic accuracy and impact on radiologist report turnaround times of an FDA-approved AI tool for pneumothorax (PTx) detection on inpatient chest X-rays (CXR) in our institution's radiology practice at a large academic medical center. MATERIALS AND METHODS: This retrospective study included 27,397 frontal, single-view CXRs of adult inpatients collected consecutively between August 2020 and April 2021 following deployment of an AI-based PTx detection and picture archiving and communication system (PACS) alert system. 12,728 CXRs were acquired within the AI-integrated system while 14,669 CXRs were acquired outside of the system. Receiver operator characteristic (ROC) analysis was conducted with final radiology reports as the reference standard to evaluate diagnostic accuracy of the AI algorithm in detection of PTx. Wilcoxon rank sum tests were conducted to evaluate the effect of the AI-integrated alert system on radiologist reporting times. RESULTS: Area under ROC curve (AUC) for the AI tool was.78 with sensitivity of .60 and specificity of .97. When selecting for moderate/large PTx, AUC, sensitivity and specificity increased to .93, .89 and .96, respectively. Median reporting time in CXRs with radiologist-confirmed PTx was reduced by 46% in those with AI integration as compared to those without AI integration (100 vs. 186 min, p < .001). CONCLUSION: Real-world deployment of an AI-integrated system capable of detecting PTx and generating alerts within PACS achieved a strong AUC for clinically actionable PTx (i.e., moderate- or large-sized) while substantially reducing median radiologist reporting times, enabling swifter clinical response to a critical but treatable condition.

Discussion and Optimization of the Male Breast Cancer Patient Experience.

Breast cancer in men is rare and often overlooked as there is a misconception that it is a gendered disease that affects women only. The feminization, or "pinkification," of the disease has been socially constructed to raise awareness, improve screening, and empower women but has not addressed the occurrence of the illness in men. Men may therefore experience unique psychosocial difficulties when faced with a disease that predominantly affects women, including feelings of disbelief and embarrassment that impact their sense of self and challenge their masculinity. The lack of mammographic screening in men, lack of public awareness, and the shame that develops during the time of diagnosis can result in treatment avoidant behaviors, a delayed presentation, and worse prognosis in men. Although male breast cancer (MBC) is uncommon, the incidence is increasing; therefore, efforts should be made to enhance education for health care professionals and the general public in order to lessen the stigma, with the goal of improving outcomes. Furthermore, special attention to the unique medical needs and hurdles encountered by transgender males can break down health care barriers in this marginalized patient population. This article offers male perceptions on breast cancer, the psychosocial implications of being diagnosed with a gendered disease, and suggestions on how to improve the MBC experience.

Using an Assumed Lung Mass Inaccurately Estimates the Lung Absorbed Dose in Patients Undergoing Hepatic 90Yttrium Radioembolization Therapy.

RATIONALE: Currently, the estimated absorbed radiation dose to the lung in 90Y radioembolization therapy is calculated using an assumed 1 kg lung mass for all patients. The aim of this study was to evaluate whether using a patient-specific lung mass measurement for each patient rather than a generic, assumed 1 kg lung mass would change the estimated lung absorbed dose. METHODS: A retrospective analysis was performed on 68 patients who had undergone 90Y radioembolization therapy at our institution. Individualized lung volumes were measured manually on CT scans for each patient, and these volumes were used to calculate personalized lung masses. The personalized lung masses were used to recalculate the estimated lung absorbed dose from the 90Y therapy, and this dose was compared to the estimated lung absorbed dose calculated using an assumed 1 kg lung mass. RESULTS: Patient-specific lung masses were significantly different from the generic 1 kg when compared individually for each patient (p < 0.0001). Median individualized lung mass was 0.71 (IQR: 0.59, 1.02) kg overall and was significantly different from the generic 1 kg lung mass for female patients [0.59 (0.50, 0.68) kg, (p < 0.0001)] but not for male patients [0.99 (0.71, 1.14) kg, (p = 0.24)]. Median estimated lung absorbed dose was 4.48 (2.38, 11.71) Gy using a patient-specific lung mass and 3.45 (1.81, 6.68) Gy when assuming a 1 kg lung mass for all patients. The estimated lung absorbed dose was significantly different using a patient-specific versus generic 1 kg lung mass when comparing the doses individually for each patient (p < 0.0001). The difference in the estimated lung absorbed dose between the patient-specific and generic 1 kg lung mass method was significant for female patients as a subgroup but not for male patients. CONCLUSIONS: The current method of assuming a 1 kg lung mass for all patients inaccurately estimates the lung absorbed dose in 90Y radioembolization therapy. Using patient-specific lung masses resulted in estimated lung absorbed doses that were significantly different from those calculated using an assumed 1 kg lung mass for all patients. A personalized dosimetry method that includes individualized lung masses is necessary and can warrant a 90Y dose reduction in some patients with lung masses smaller than 1 kg. LEVEL OF EVIDENCE: Level 3, Retrospective Study.

Predicting Mechanical Ventilation and Mortality in COVID-19 Using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study.

In this study, we aimed to predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs (CXRs) for coronavirus disease 2019 (COVID-19) patients. This two-center, retrospective study analyzed 530 deidentified CXRs from 515 COVID-19 patients treated at Stony Brook University Hospital and Newark Beth Israel Medical Center between March and August 2020. Linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and random forest (RF) machine learning classifiers to predict mechanical ventilation requirement and mortality were trained and evaluated using radiomic features extracted from patients' CXRs. Deep learning (DL) approaches were also explored for the clinical outcome prediction task and a novel radiomic embedding framework was introduced. All results are compared against radiologist grading of CXRs (zone-wise expert severity scores). Radiomic classification models had mean area under the receiver operating characteristic curve (mAUCs) of 0.78 ± 0.05 (sensitivity = 0.72 ± 0.07, specificity = 0.72 ± 0.06) and 0.78 ± 0.06 (sensitivity = 0.70 ± 0.09, specificity = 0.73 ± 0.09), compared with expert scores mAUCs of 0.75 ± 0.02 (sensitivity = 0.67 ± 0.08, specificity = 0.69 ± 0.07) and 0.79 ± 0.05 (sensitivity = 0.69 ± 0.08, specificity = 0.76 ± 0.08) for mechanical ventilation requirement and mortality prediction, respectively. Classifiers using both expert severity scores and radiomic features for mechanical ventilation (mAUC = 0.79 ± 0.04, sensitivity = 0.71 ± 0.06, specificity = 0.71 ± 0.08) and mortality (mAUC = 0.83 ± 0.04, sensitivity = 0.79 ± 0.07, specificity = 0.74 ± 0.09) demonstrated improvement over either artificial intelligence or radiologist interpretation alone. Our results also suggest instances in which the inclusion of radiomic features in DL improves model predictions over DL alone. The models proposed in this study and the prognostic information they provide might aid physician decision making and efficient resource allocation during the COVID-19 pandemic.

Predicting Clinical Outcomes in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study.

We predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs (CXRs) for coronavirus disease 2019 (COVID-19) patients. This two-center, retrospective study analyzed 530 deidentified CXRs from 515 COVID-19 patients treated at Stony Brook University Hospital and Newark Beth Israel Medical Center between March and August 2020. DL and machine learning classifiers to predict mechanical ventilation requirement and mortality were trained and evaluated using patient CXRs. A novel radiomic embedding framework was also explored for outcome prediction. All results are compared against radiologist grading of CXRs (zone-wise expert severity scores). Radiomic and DL classification models had mAUCs of 0.78+/-0.02 and 0.81+/-0.04, compared with expert scores mAUCs of 0.75+/-0.02 and 0.79+/-0.05 for mechanical ventilation requirement and mortality prediction, respectively. Combined classifiers using both radiomics and expert severity scores resulted in mAUCs of 0.79+/-0.04 and 0.83+/-0.04 for each prediction task, demonstrating improvement over either artificial intelligence or radiologist interpretation alone. Our results also suggest instances where inclusion of radiomic features in DL improves model predictions, something that might be explored in other pathologies. The models proposed in this study and the prognostic information they provide might aid physician decision making and resource allocation during the COVID-19 pandemic.

The moderating role of race/ethnicity on associations between insurance status and HPV vaccination among women in the USA.

OBJECTIVE: To evaluate associations between insurance status and HPV vaccination. METHODS: The present cross-sectional study analyzed data from women aged 18-26 years who participated in the National Health and Nutritional Examination Surveys 2009-2012 in the USA. RESULTS: The study included 621 women; 424 (68.3%) had some type of insurance and 198 (30.6%) had received the HPV vaccine. In the multivariable model, we found significant interactions between race/ethnicity and insurance status on receiving HPV vaccination. Compared with individuals with no insurance, non-Hispanic black women with any type of insurance demonstrated increased likelihood of HPV vaccination (adjusted odds ratio [aOR] 3.63, 95% confidence interval [CI] 1.60-8.21; P=0.002). Among Mexican Americans, there was a negative association between having some insurance and HPV vaccination (aOR 0.35, 95% CI 0.15-0.81; P=0.007). For non-Hispanic black women, the association remained significant across all insurance types (private [aOR 4.29, 95% CI 1.67-11.00; P=0.003], Medicaid [aOR 2.86, 95% CI 1.15-7.13; P=0.025], and other [aOR 4.74, 95% CI 1.06-21.15; P=0.042]). Non-Hispanic white women with insurance other than private or Medicaid had a higher likelihood of HPV vaccination compared with uninsured individuals (aOR 8.36, 95% CI 2.79-25.05; P<0.001). CONCLUSION: The present findings help to identify at-risk populations less likely to receive the HPV vaccine.

Overview of systemic treatment in recurrent and advanced cervical cancer: a primer for radiologists.

Imaging has a central role in surveillance of cervical cancer, guiding decision on when to initiate treatment for recurrent disease and to guide management in advanced cervical cancer. Due to the increased availability of pelvic radiation therapy, the rate of atypical presentation of recurrent disease has increased. Simultaneously, the array of systemic therapies now available for advanced cervical cancer has considerably expanded in the last few years, with therapies now available in mid and low-income countries. While pelvic recurrences are amenable of loco-regional treatment, recurrent disease may present with metastases to the thoracoabdominal organs, lymph nodes, bones, skin and brain, for which systemic treatment represent the standard of care. Besides combined chemotherapy regimens, alternative chemotherapies, biosimilars and immune checkpoint inhibitors are now available, each associated with a definite pattern of response and toxicity. In this review, after describing the typical and atypical presentations of recurrent and advanced cervical carcinoma on cross-sectional imaging, we will discuss systemic treatment for recurrent or advanced disease and their associated radiographic sequelae, in light of the newly available therapies.

Serum tumor markers and testicular germ cell tumors: a primer for radiologists.

Serum tumor markers (STMs) play a critical role in the diagnosis, staging and follow-up of both seminomatous and nonseminomatous testicular germ cell neoplasms. Levels of alpha-fetoprotein (AFP), human chorionic gonadotropin (HCG), and lactate dehydrogenase (LDH), especially those measured after orchiectomy, also have implications for patient prognosis. Given that testicular germ cell tumors represent the most common solid tumor in men aged 20-34, radiologists must have familiarity with the clinical utilization and implications of these STMs. This article will review the classical patterns of STM elevation most commonly seen in pure seminomatous and nonseminomatous germ cell tumors while also providing case-based examples highlighting the importance of STM correlation with imaging. The role of STMs in clinical staging and disease surveillance will also be discussed.

(4S,5S)-2,2-Dimethyl-4,5-bis-(3-methyl-2-thioxo-2,3-dihydro-1H-imidazol-1-yl-meth-yl)-1,3-dioxolane.

In the chiral title compound, C(15)H(22)N(4)O(2)S(2), there are two mol-ecules in the asymmetric unit with distinctly different conformations, as quanti-fied by torsion angles. The dihedral angles between the thio-imidazole rings are 81.59 (5) and 67.04 (4)°. One mol-ecule exhibits local twofold rotation symmetry, while the other displays no local symmetry. Inter-molecular C-H⋯O and C-H⋯S inter-actions are observed.