A Metabolically Optimized, Noncytotoxic Low-Dose Weekly Decitabine/Venetoclax in MDS and AML.

PURPOSE: Venetoclax (VEN) added to the hypomethylating agents (HMA) decitabine or azacitidine is the new standard of care for elderly patients with acute myeloid leukemia (AML) and is being evaluated in myelodysplastic syndrome (MDS). Current dosing of HMA/VEN relies on leukemia suppression through cytotoxicity which also impacts normal hematopoiesis. A regimen using once-weekly low-dose decitabine (LDDec) has demonstrated activity in myeloid malignancies. To overcome the severe myelosuppression often seen with HMA/VEN, we evaluated a once-weekly dosing regimen of VEN and LDDec in elderly and/or frail patients who were felt less likely to tolerate severe myelosuppression. PATIENTS AND METHODS: This is a retrospective, single-center analysis of patients with AML, MDS, or chronic myelomonocytic leukemia treated with a once-weekly LDDec/VEN regimen. We also compare this regimen with a cohort treated with standard dosing HMA/VEN. RESULTS: In a retrospective cohort of 39 patients, the overall response rate for patients receiving LDDec/VEN for first-line AML and MDS was 88% and 64%, respectively. In patients with TP53 mutations, the composite complete response rate was 71% and the median overall survival was 10.7 months. When compared with 36 patients receiving standard dose HMA/VEN, the LDDec/VEN patients had a longer time on therapy (175 vs. 78 days; P = 0.014) and a trend toward a higher rate of transfusion independence (47% vs. 26%; P = 0.33). Neutropenic fever occurred in 31% of patients, with a median of one hospitalization at any point during treatment. CONCLUSIONS: This preliminary clinical experience, although retrospective, provides proof-of-activity of noncytotoxic DNA methyltransferase 1-targeting by allowing frequent, sustained drug exposure often not possible with standard HMA/VEN regimens.

A Co-Management Model for Myeloid Malignancies That Evolved during the COVID-19 Pandemic.

INTRODUCTION: Myeloid malignancies are a heterogeneous group of clonal bone marrow disorders that are complex to manage in the community and therefore often referred to subspecialists at tertiary oncology referral centers. Many patients do not live in close proximity to tertiary referral centers and are unable to commute long distances due to age, comorbidities, and frailty. Interventions that minimize the travel time burden without compromising quality of care are an area of unmet need. We describe a cancer care delivery model for patients with myeloid malignancies that is built around telehealth and enables this vulnerable population access to care at an NCI-designated cancer center while receiving majority of their care close to home. METHODS AND MATERIALS: We report on a cohort of patients with myeloid malignancies who were co-managed by a general community oncologist and an academic leukemia subspecialist at Montefiore Einstein Cancer Center in New York. Patients were initially referred to our institute for a second opinion by community practices that are in partnership with Montefiore Health System, and initial visits were in-person or via telehealth. Treatment plans were made after discussion with patient's local community oncologist. Patients then continued to receive majority of their treatment and supportive care including transfusion support with their local oncologist, and follow-up visits were mainly via telehealth with the academic leukemia subspecialist. RESULTS: Our cohort of 12 patients had a median age of 81 years (range, 59-88 years). Patients remained on active treatment for a median time of 357 days (range, 154-557 days). Most of our patients had a performance status of ECOG 2 or higher. Three patients had myelodysplastic syndromes, 7 patients had acute myeloid leukemia, and 2 patients had myelofibrosis. The median number of hospitalizations over the total treatment time period was one. CONCLUSION: We demonstrate a shared academic and community care co-management model for the treatment of myeloid malignancies in elderly, frail patients using telehealth as a backbone with a very low hospitalization rate.

Analysis of digital noise and reduction methods on classifiers used in automated visual evaluation in cervical cancer screening.

The burden of cervical cancer disproportionately falls on low- and middle-income countries (LMICs). Automated visual evaluation (AVE) is a technology being considered as an adjunct tool for the management of HPV-positive women. AVE involves analysis of a white light illuminated cervical image using machine learning classifiers. It is of importance to analyze various impacts of different kinds of image degradations on AVE. In this paper, we report our work regarding the impact of one type of image degradation, Gaussian noise, and one of its remedies we have been exploring. The images, originated from the Natural History Study (NHS) and ASCUS-LSIL Triage Study (ALTS), were modified by the addition of white Gaussian noise at different levels. The AVE pipeline used in the experiments consists of two deep learning components: a cervix locator which uses RetinaNet (an object detection network), and a binary pathology classifier that uses the ResNeSt network. Our findings indicate that Gaussian noise, which frequently appears in low light conditions, is a key factor in degrading the AVE's performance. A blind image denoising technique which uses Variational Denoising Network (VDNet) was tested on a set of 345 digitized cervigram images (115 positives) and evaluated both visually and quantitatively. AVE performances on both the synthetically generated noisy images and the corresponding denoised images were examined and compared. In addition, the denoising technique was evaluated on several real noisy cervix images captured by a camera-based imaging device used for AVE that have no histology confirmation. The comparison between the AVE performances on images with and without denoising shows that denoising can be effective at mitigating classification performance degradation.

Efficacy of booster doses in augmenting waning immune responses to COVID-19 vaccine in patients with cancer.

Anti-COVID-19 immunity dynamics were assessed in patients with cancer in a prospective clinical trial. Waning of immunity was detected 4-6 months post-vaccination with significant increases in anti-spike IgG titers after booster dosing, and 56% of seronegative patients seroconverted post-booster vaccination. Prior anti-CD20/BTK inhibitor therapy was associated with reduced vaccine efficacy.

The development of "automated visual evaluation" for cervical cancer screening: The promise and challenges in adapting deep-learning for clinical testing: Interdisciplinary principles of automated visual evaluation in cervical screening.

There is limited access to effective cervical cancer screening programs in many resource-limited settings, resulting in continued high cervical cancer burden. Human papillomavirus (HPV) testing is increasingly recognized to be the preferable primary screening approach if affordable due to superior long-term reassurance when negative and adaptability to self-sampling. Visual inspection with acetic acid (VIA) is an inexpensive but subjective and inaccurate method widely used in resource-limited settings, either for primary screening or for triage of HPV-positive individuals. A deep learning (DL)-based automated visual evaluation (AVE) of cervical images has been developed to help improve the accuracy and reproducibility of VIA as assistive technology. However, like any new clinical technology, rigorous evaluation and proof of clinical effectiveness are required before AVE is implemented widely. In the current article, we outline essential clinical and technical considerations involved in building a validated DL-based AVE tool for broad use as a clinical test.

Portable, low-cost multispectral imaging system: design, development, validation, and utilization.

Optical spectral images can be used to estimate the amount of bulk absorbers in tissues, specifically oxy- and deoxyhemoglobin, as well as scattering parameters. Most systems that capture spectral image data are large, heavy, and expensive. This paper presents a full end-to-end analysis of a low-cost reflectance-mode multispectral imaging system operating in the visible and near-infrared spectra. The system consists of 13 LEDs mounted on a printed circuit board, a monochrome machine vision camera, and a tablet computer to control the hardware. The bill of materials for the system is less than $1000. Hardware design and implementation are detailed. Calibration, image capture, and preprocessing are also discussed. In validation experiments, excellent agreement is observed in diffuse reflectance measurements between the spectral camera setup and a spectrometer. To demonstrate that such spectral image data can yield meaningful optical measurements in vivo, the forearms of eight volunteers are imaged in the system. Their data are then analyzed to estimate the tissue optical properties of different skin layers using a Monte Carlo lookup table. In three volunteers, spectral images are captured before and after inducing erythema using a warm wet towel. Across the three subjects, a clear increase in the blood content of the superficial plexus layer was observed as a result of the erythema. Collectively, these findings suggest that a low-cost system can capture accurate spectral data and that clinically meaningful information can be derived from it.

Real-Time Monitoring and Evaluation of a Visual-Based Cervical Cancer Screening Program Using a Decision Support Job Aid.

In many developing nations, cervical cancer screening is done by visual inspection with acetic acid (VIA). Monitoring and evaluation (M&E) of such screening programs is challenging. An enhanced visual assessment (EVA) system was developed to augment VIA procedures in low-resource settings. The EVA System consists of a mobile colposcope built around a smartphone, and an online image portal for storing and annotating images. A smartphone app is used to control the mobile colposcope, and upload pictures to the image portal. In this paper, a new app feature that documents clinical decisions using an integrated job aid was deployed in a cervical cancer screening camp in Kenya. Six organizations conducting VIA used the EVA System to screen 824 patients over the course of a week, and providers recorded their diagnoses and treatments in the application. Real-time aggregated statistics were broadcast on a public website. Screening organizations were able to assess the number of patients screened, alongside treatment rates, and the patients who tested positive and required treatment in real time, which allowed them to make adjustments as needed. The real-time M&E enabled by "smart" diagnostic medical devices holds promise for broader use in screening programs in low-resource settings.

Dermal reflectivity determined by optical coherence tomography is an indicator of epidermal hyperplasia and dermal edema within inflamed skin.

Psoriasis is a common inflammatory skin disease resulting from genetic and environmental alterations of cutaneous immune responses. While numerous therapeutic targets involved in the immunopathogenesis of psoriasis have been identified, the in vivo dynamics of inflammation in psoriasis remain unclear. We undertook in vivo time course focus-tracked optical coherence tomography (OCT) imaging to noninvasively document cutaneous alterations in mouse skin treated topically with Imiquimod (IMQ), an established model of a psoriasis-like disease. Quantitative appraisal of dermal architectural changes was achieved through a two parameter fit of OCT axial scans in the dermis of the form A(x, y, z) = ρ(x, y)exp [-µ(x, y)z]. Ensemble averaging over 2000 axial scans per mouse in each treatment arm revealed no significant changes in the average dermal attenuation rate, <µ>, however the average local dermal reflectivity <ρ>, decreased significantly following 1, 3, and 6 days of IMQ treatment (p < 0.001) in comparison to vehicle-treated control mice. In contrast, epidermal and dermal thickness changes were only significant when comparing controls and 6-day IMQ treated mice. This suggests that dermal alterations, attributed to collagen fiber bundle enlargement, occur prior to epidermal thickness changes due to hyperplasia and dermal thickness changes due to edema. Dermal reflectivity positively correlated with epidermal hyperplasia (r(epi)(2) = 0.78) and dermal edema (r(derm)(2) = 0.86). Our results suggest that dermal reflectivity as measured by OCT can be utilized to quantify a psoriasis-like disease in mice, and thus has the potential to aid in the quantitative assessment of psoriasis in humans.

Non-destructive label-free monitoring of collagen gel remodeling using optical coherence tomography.

Matrix remodeling plays a fundamental role in physiological and pathological processes, as well as in tissue engineering applications. In this paper, optical coherence tomography (OCT), a non-destructive optical imaging technology, was used to image collagen gel remodeling by smooth muscle cells (SMCs). The optical scattering properties of collagen-SMC gels were characterized quantitatively by fitting OCT data to a theoretical model. Matrix remodeling over 5 days produced a 10-fold increase in the reflectivity of the collagen gels, corresponding to a decrease in scattering anisotropy from 0.91 to 0.46. The increase in reflectivity was corroborated in confocal mosaic images. Blocking matrix degradation in collagen-SMC gels with doxycycline, a non-specific matrix metalloproteinases (MMPs) inhibitor, impeded the decrease in scattering anisotropy and resulted in few macroscopic signs of remodeling. Causing matrix degradation in acellular gels with a 3 h treatment of MMP-8 (collagenase 2) partially mimicked the decrease in anisotropy measured in collagen-SMC gels after 5 days. These results suggest that the decrease in scattering anisotropy in the collagen-SMC gels was due to MMP activity that degrades collagen fibrils into smaller fragments.

Quantitative characterization of developing collagen gels using optical coherence tomography.

Nondestructive optical imaging methods such as optical coherence tomography (OCT) have been proposed for characterizing engineered tissues such as collagen gels. In our study, OCT was used to image collagen gels with different seeding densities of smooth muscle cells (SMCs), including acellular gels, over a five-day period during which the gels contracted and became turbid with increased optical scattering. The gels were characterized quantitatively by their optical properties, specified by analysis of OCT data using a theoretical model. At 6 h, seeded cell density and scattering coefficient (mu(s)) were correlated, with mu(s) equal to 10.8 cm(-1)(10(6) cells mL). Seeded cell density and the scattering anisotropy (g) were uncorrelated. Over five days, the reflectivity in SMC gels gradually doubled with little change in optical attenuation, which indicated a decrease in g that increased backscatter, but only a small drop in mu(s). At five days, a subpopulation of sites on the gel showed substantially higher reflectivity (approximately a tenfold increase from the first 24 h). In summary, the increased turbidity of SMC gels that develops over time is due to a change in the structure of collagen, which affects g, and not simply due to a change in number density of collagen fibers due to contraction.

Determination of optical scattering properties of highly-scattering media in optical coherence tomography images.

We developed a new algorithm that fits optical coherence tomography (OCT) signals as a function of depth to a general theoretical OCT model which takes into account multiple scattering effects. With use of this algorithm, it was possible to extract both the scattering coefficient and anisotropy factor from a particular region of interest in an OCT image. The extraction algorithm was evaluated against measurements from an integrating sphere on a set of tissue phantoms and yielded valid results. Finally, a preliminary ex vivo OCT investigation on human aortic specimen indicated that the algorithm may contribute importantly to differentiation between normal and atherosclerotic arteries. We conclude that this algorithm may facilitate tissue characterization by OCT.