Long-term clinical outcomes of combined modality therapy for advanced-stage Hodgkin lymphoma in the PET era: A retrospective study.

BACKGROUND OBJECTIVES: The role of consolidation radiation therapy (CRT) after complete metabolic response to chemotherapy in advanced-stage (stage III and IV) Hodgkin lymphoma (HL) is controversial. This study was undertaken to assess the clinical outcomes in terms of event free survival, local failure free survival and overall survival in individuals with advanced HL treated with chemotherapy and CRT. METHODS: A retrospective review was conducted to study the long-term clinical outcomes in individuals diagnosed with HL and treated with chemotherapy and CRT from 2012 to 2016 at a tertiary cancer care hospital in India. RESULTS: Data from 203 study participants with advanced-stage HL were analyzed. Positron emission tomography-computed tomography (PET-CT) was done at baseline and after 2 cycles for response assessment. The median age at presentation was 32 yr [interquartile range (IQR): 26-46]. Early metabolic response (after 2 cycles) and delayed metabolic response (after 4 or 6 cycles) were observed in 74.4 and 25.6 per cent of individuals, respectively. With a median follow up of 52 months (IQR: 40-67), the five-year event-free survival (EFS), local failure-free survival (LFFS) and overall survival (OS) were 83.2, 95.1 and 94.6 per cent, respectively. On univariate analysis, extranodal disease was associated with inferior EFS (P=0.043). Haemoglobin <10.5 g/dl (P=0.002) and Hasenclever index >3 (P=0.00047) were associated with poorer OS. Relapses were observed in 28/203 (13.8%) study participants with predominance at central nodal stations. The median time to relapse was 19.4 months (IQR: 13-33). Local relapse alone (at the irradiated site) was observed in 5/28 study participants, systemic (distant) relapse in 14/28 individuals, while both systemic and local relapse was observed in 9/28 participants. Extranodal disease (P=0.05), bulky disease (P=0.005) and haemoglobin concentration ≤10.5 g/dl (P=0.036) were significant predictors for disease relapse. INTERPRETATION CONCLUSIONS: Individuals with advanced-stage HL treated with anthracycline-based chemotherapy (anthracycline-based chemotherapy with doxorubicin, bleomycin, vinblastine and dacarbazine regimen) and CRT had excellent long-term outcomes. As isolated infield failures are uncommon, selective consolidation with conformal RT to high-risk sites improves final disease outcomes.

Nanomedicine as a multimodal therapeutic paradigm against cancer: on the way forward in advancing precision therapy.

Recent years have witnessed dramatic improvements in nanotechnology-based cancer therapeutics, and it continues to evolve from the use of conventional therapies (chemotherapy, surgery, and radiotherapy) to increasingly multi-complex approaches incorporating thermal energy-based tumor ablation (e.g. magnetic hyperthermia and photothermal therapy), dynamic therapy (e.g. photodynamic therapy), gene therapy, sonodynamic therapy (e.g. ultrasound), immunotherapy, and more recently real-time treatment efficacy monitoring (e.g. theranostic MRI-sensitive nanoparticles). Unlike monotherapy, these multimodal therapies (bimodal, i.e., a combination of two therapies, and trimodal, i.e., a combination of more than two therapies) incorporating nanoplatforms have tremendous potential to improve the tumor tissue penetration and retention of therapeutic agents through selective active/passive targeting effects. These combinatorial therapies can correspondingly alleviate drug response against hypoxic/acidic and immunosuppressive tumor microenvironments and promote/induce tumor cell death through various multi-mechanisms such as apoptosis, autophagy, and reactive oxygen-based cytotoxicity, e.g., ferroptosis, etc. These multi-faced approaches such as targeting the tumor vasculature, neoangiogenic vessels, drug-resistant cancer stem cells (CSCs), preventing intra/extravasation to reduce metastatic growth, and modulation of antitumor immune responses work complementary to each other, enhancing treatment efficacy. In this review, we discuss recent advances in different nanotechnology-mediated synergistic/additive combination therapies, emphasizing their underlying mechanisms for improving cancer prognosis and survival outcomes. Additionally, significant challenges such as CSCs, hypoxia, immunosuppression, and distant/local metastasis associated with therapy resistance and tumor recurrences are reviewed. Furthermore, to improve the clinical precision of these multimodal nanoplatforms in cancer treatment, their successful bench-to-clinic translation with controlled and localized drug-release kinetics, maximizing the therapeutic window while addressing safety and regulatory concerns are discussed. As we advance further, exploiting these strategies in clinically more relevant models such as patient-derived xenografts and 3D organoids will pave the way for the application of precision therapy.

A Retrospective Cohort Study to Evaluate the Outcomes of HIV-Associated High-Grade B-Cell Non-Hodgkin Lymphoma (NHL) Treated with Dose Adjusted EPOCH (+/-R) Regimen.

High-grade B-cell NHL's are more common in seropositive patients. They are biologically different from their seronegative counterparts. We report our analysis on our cohort of patients who were treated with DA-EPOCH(+/-R). We retrospectively analyzed treatment-naïve HIV-associated High-grade B-cell NHL patients (aged ≥ 18) treated with DA-EPOCH(+/-R) regimen from 2011 to 2015. Descriptive statistics were summarized with median and range; survival outcomes were analyzed with Kaplan-Meier method. The cohort comprised of 40 patients [DLBCL(19), Burkitt's Lymphoma(16), High-grade B-Cell Lymphoma-Unclassifiable(09), and Plasmablastic Lymphoma(01)] and the median CD4 + T cell count was 202/mm3. CNS prophylaxis was administered with intrathecal methotrexate to 90% of patients. With a median follow-up of 72 months, an estimated 5-year OS was 82.5%, and 5-PFS was 77.5%. There were 9 deaths, and 9 patients had progression. At least 4 cycles of chemotherapy were administered to 35 (93%) patients, with 28 (70%) receiving 6 cycles. Grade 3-4 toxicities were seen in 33 (83%) patients- febrile neutropenia (65%) being the most common followed by mucositis (25%) and peripheral neuropathy (13%). There was no difference in survival based on IPI, CD 4 + T cell count, CDI, or duration of HIV. DA-EPOCH(+/-R) is a highly effective regimen in seropositive high-grade B-cell lymphoma, even in the presence of adverse features. Supplementary Information: The online version contains supplementary material available at 10.1007/s12288-023-01652-3.

Dosimetric Impact of Voluntary Deep Inspiration Breath Hold (DIBH) in Mediastinal Hodgkin Lymphomas: A Comparative Evaluation of Three Different Intensity Modulated Radiation Therapy (IMRT) Delivery Methods Using Voluntary DIBH and Free Breathing Techniques.

Hodgkin lymphomas are radiosensitive and curable tumors that often involve the mediastinum. However, the application of radiation therapy to the mediastinum is associated with late effects including cardiac and pulmonary toxicities and secondary cancers. The adoption of conformal IMRT and deep inspiration breath- hold (DIBH) can reduce the dose to healthy normal tissues (lungs, heart and breast). We compared the dosimetry of organs at risk (OARs) using different IMRT techniques for two breathing conditions, i.e., deep inspiration breath hold (DIBH) and free breathing. Twenty-three patients with early-stage mediastinal Hodgkin lymphomas were accrued in the prospective study. The patients were given treatment plans which utilized full arc volumetric modulated arc therapy (F-VMAT), Butterfly VMAT (B-VMAT), and fixed field IMRT (FF-IMRT) techniques for both DIBH and free breathing methods, respectively. All the plans were optimized to deliver 95% of the prescription dose which was 25.2 Gy to 95% of the PTV volume. The mean dose and standard error of the mean for each OAR, conformity index (CI), and homogeneity index (HI) for the target using the three planning techniques were calculated and compared using Student's t-test for parametric data and Wilcoxon signed-rank test for non-parametric data. The HI and CI of the target was not compromised using the DIBH technique for mediastinal lymphomas. The mean values of CI and HI for both DIBH and FB were comparable. The mean heart doses were reduced by 2.1 Gy, 2.54 Gy, and 2.38 Gy in DIBH compared to FB for the F-VMAT, B-VMAT, and IMRT techniques, respectively. There was a significant reduction in V5Gy, V10Gy, and V15Gy to the heart (p < 0.005) with DIBH. DIBH reduced the mean dose to the total lung by 1.19 Gy, 1.47 Gy, and 1.3 Gy, respectively. Among the 14 female patients, there was a reduction in the mean right breast dose with DIBH compared to FB (4.47 Gy vs. 3.63 Gy, p = 0.004). DIBH results in lower heart, lung, and breast doses than free breathing in mediastinal Hodgkin Lymphoma. Among the different IMRT techniques, FF-IMRT, B-VMAT, and F-VMAT showed similar PTV coverage, with similar conformity and homogeneity indices. However, the time taken for FF-IMRT was much longer than for the F-VMAT and B-VMAT techniques for both breathing methods. B-VMAT and F-VMAT emerged as the optimal planning techniques able to achieve the best target coverage and lower doses to the OARs, with less time required to deliver the prescribed dose.

Patterns of Care in Craniopharyngioma: Clinical Outcomes After Surgery and Radiation Therapy in a Real-World Setting.

OBJECTIVE: Craniopharyngioma (CP) is a benign neuroepithelial tumor generally treated with maximal safe resection and radiation therapy (RT) in incompletely resected CP or in recurrent tumors to achieve long-term control. We analyzed the clinical outcomes of patients with CPs treated with a multimodality approach. PATIENTS AND METHODS: A retrospective clinical audit of histologically proven CPs registered between 2008 and 2019 at a specialized neuro-oncology center in India was performed. Time-to-event outcomes (overall survival [OS] and progression-free survival [PFS]) were analyzed. RESULTS: One hundred and twenty-two patients with CP were analyzed. The median age of the population was 14 years (interquartile range [IQR], 8-26) with a significant male preponderance. Gross total resection was achieved in only 25% of patients. At a median follow-up of 57.1 months (IQR, 27.8-87.8), 5-year estimates of PFS and OS were 52% (95% confidence interval, 46%-63.4%) and 85.8% (95% confidence interval, 78.6%-93%), respectively. Recurrence or progression was observed in 48 of 122 patients (39.3%) at a median time of 84.4 months (IQR, 24.7-174.8). On multivariate analysis, the absence of residual disease (P = 0.004), near-total resection (P = 0.035), and use of up-front adjuvant RT (P < 0.001) significantly improved the 5-year PFS, whereas the absence of extracavernous extension (P = 0.058) and any use of postoperative RT (P = 0.026) significantly improved the 5-year OS. CONCLUSIONS: This study represents one of the largest single-institutional series of CPs, showing improved PFS with up-front adjuvant RT in most cases of CP. Deferring adjuvant RT should be considered only in patients with no evidence of residual disease (as shown on dedicated sellar imaging) after primary surgery.

Primary central nervous system lymphoma: Comprehension of cell-of-origin subtypes.

Primary central nervous system diffuse large B-cell lymphoma (PCNS-DLBCL) is an uncommon extranodal lymphoma that accounts for more than 95% of all the CNS lymphomas. Unlike its systemic/nodal counterpart, which is currently subtyped into cell-of origin (COO) subtypes, its feasibility and utility are largely debatable in PCNS-DLBCL. Objectives: To classify PCNS-DLBCL into COO-subtypes based on immunohistochemical algorithms by Hans and Choi and evaluate concordance between the two. A further aim is to investigate the clinicoradiological and histomorphological parameters of the subtypes thus obtained. Materials and Methods: As many as 143 cases of primary CNS lymphoma were evaluated by immunohistochemistry for CD10, BCL6, MUM1, GCET, and FOXP1 and based on which the said 143 cases were further classified into COO subtypes using Hans and Choi algorithms. Results: Mean age was 53.8 years with marginal male preponderance and predominantly centroblastic morphology (75.5%). CD 10 was positive in 8.9% of the cases, BCL6 in 58.6%, MUM1 in 89.9%, GCET in 32.9%, and FOXP1 in 79.5%. As much as 84.9% cases were of non-germinal center B-cell (GCB) subtype and 15.1% cases were of GCB subtype as determined based on Hans algorithm. Furthermore, 90.7% cases were of activated B-cell (ABC) subtype and 9.3% cases were of GCB subtype according to Choi algorithm. A 91.8% concordance was observed between Hans and Choi algorithms. Among the 6 discordant cases, 5 cases were subtyped as GCB by Hans and ABC by Choi and 1 case as ABC by Hans and GCB by Choi. Conclusion: Most of PCNS-DLBCLs are of non-GCB/ABC COO subtype, but inconsistences abound in the utility of IHC algorithms in PCNS-DLBCL COO subtypes.

Insight into lipid-based nanoplatform-mediated drug and gene delivery in neuro-oncology and their clinical prospects.

Tumors of the Central nervous System (CNS) are a spectrum of neoplasms that range from benign lesions to highly malignant and aggressive lesions. Despite aggressive multimodal treatment approaches, the morbidity and mortality are high with dismal survival outcomes in these malignant tumors. Moreover, the non-specificity of conventional treatments substantiates the rationale for precise therapeutic strategies that selectively target infiltrating tumor cells within the brain, and minimize systemic and collateral damage. With the recent advancement of nanoplatforms for biomaterials applications, lipid-based nanoparticulate systems present an attractive and breakthrough impact on CNS tumor management. Lipid nanoparticles centered immunotherapeutic agents treating malignant CNS tumors could convene the clear need for precise treatment strategies. Immunotherapeutic agents can selectively induce specific immune responses by active or innate immune responses at the local site within the brain. In this review, we discuss the therapeutic applications of lipid-based nanoplatforms for CNS tumors with an emphasis on revolutionary approaches in brain targeting, imaging, and drug and gene delivery with immunotherapy. Lipid-based nanoparticle platforms represent one of the most promising colloidal carriers for chemotherapeutic, and immunotherapeutic drugs. Their current application in oncology especially in brain tumors has brought about a paradigm shift in cancer treatment by improving the antitumor activity of several agents that could be used to selectively target brain tumors. Subsequently, the lab-to-clinic transformation and challenges towards translational feasibility of lipid-based nanoplatforms for drug and gene/immunotherapy delivery in the context of CNS tumor management is addressed.

Primary Intracranial Germ Cell Tumors: A Study with an Integrated Clinicopathological Approach.

Background and Objective: Primary intracranial germ cell tumors (ICGCTs) are rare and are histologically classified as germinomas and non-germinomatous with distinctive prognostic and therapeutic implications. ICGCTs, essentially due to the inherent difficulty of surgical access, pose different challenges and management connotations than their extracranial counterparts. This is a retrospective analysis of histologically verified ICGCTs, which was undertaken to evaluate various clinicopathological features and their implications on patient management. Materials and Methods: Eighty-eight histologically diagnosed cases (over 14 years) of ICGCT at our institute formed the study cohort and were classified into germinoma and non-germinomatous germ cell tumors (NGGCTs). Additionally, germinomas were further subdivided on the basis of 1) tumor marker (TM) levels, as germinoma with normal TM, mildly elevated TM, and markedly elevated TM and 2) radiology features, as germinomas with typical radiology and atypical radiological features. Results: ICGCT with age ≤6 years (P = 0.049), elevated TM (P = 0.047), and NGGCT histology (P < 0.001) showed significantly worse outcomes. Furthermore, germinomas with markedly elevated TM and certain atypical radiological features showed prognosis akin to NGGCT. Conclusions: Analysis of our largest single cancer center Indian patient cohort of ICGCT shows that inclusion of age ≤6 years, raised TM, and certain radiological features may assist clinicians in overcoming the limitations of surgical sampling, with better prognostication of histologically diagnosed germinomas.

Metabolic tumor parameters complement clinicopathological factors in prognosticating advanced stage Hodgkin Lymphoma.

Objectives: Advanced Hodgkin Lymphoma has a higher probability of relapse and recurrence. Classical clinicopathological parameters including the International Prognostic Score (IPS) have not been reliable in predicting prognosis or tailoring treatment. Since FDG PET/CT is the standard of care in staging Hodgkin Lymphoma, this study attempted to evaluate the clinical utility of baseline metabolic tumor parameters in a cohort of advanced Hodgkin lymphoma (stage III and IV). Methods: Histology-proven advanced Hodgkin Patients presenting to our institute between 2012-2016 and treated with chemo-radiotherapy (ABVD / AEVD) were followed up till 2019. Quantitative PET/CT and clinicopathological parameters were used to estimate the Event Free Survival (EFS) in 100 patients. Kaplan-Meier method with log-rank test was used to compare the survival times of prognostic factors. Results: At a median follow-up of 48.83 months (IQR:33.31-63.05 months), the five-year-EFS was 81%. Of the 100 patients, 16 had relapsed (16%) and none died at the last follow-up. On Univariate analysis, among non-PET parameters bulky disease (P=0.03) and B-symptoms (P=0.04) were significant while among PET/CT parameters SUVmax (p=0.001), SUVmean (P=0.002), WBMTV2.5 (P<0.001), WBMTV41% (P<0.001), WBTLG2.5 (P<0.001) and WBTLG41% (P <0.001) predicted poorer EFS. 5-year EFS for patients with low WBMTV2.5 [<1038.3 cm3] was 89% and 35% for patients with high WBMTV2.5 [≥1038.3 cm3] (p <0.001). In a multivariate model, only WBMTV2.5 (P=0.03) independently predicted poorer EFS. Conclusion: PET-based metabolic parameter (WBMTV2.5) was able to prognosticate and complement the classical clinical prognostic factors in advanced Hodgkin Lymphoma. This parameter could have a surrogate value for prognosticating advanced Hodgkin lymphoma. Better prognostication at baseline translates to tailored or risk-modified treatment and hence higher survival.

Computerized tomography-based first order tumor texture features in non-small cell lung carcinoma treated with concurrent chemoradiation: A simplistic and potential surrogate imaging marker for survival.

Objectives: This study examines the role of tumor texture on computed tomography (CT) images as a complement to clinical prognostic factors in predicting survival in patients of non-small cell lung carcinoma (NSCLC) treated with radical chemo-radiation (CRT). Methods: A total of 93 patients with confirmed NSCLC treated with CRT accrued in a study approved by the institutional ethics committee were analyzed for CT-based radiomic features. Pretreatment CT images were used to contour the primary tumor and texture features were computed by the image filtration method to differentially highlight fine to coarse textures. Texture parameters included mean intensity, entropy, kurtosis, standard deviation, and mean positive pixel and skewness. Optimal threshold cut-off values of the above tumor texture features were analyzed. These features were explored as imaging biomarkers to predict survival using Kaplan-Meier and Cox proportional hazard model. Results: Median follow-up of the entire cohort was 23.5 months [Interquartile range, IQR: 14-37] while for alive patients, median follow-up was 31 months (IQR: 23-49), 47 (50.6%) patients had died at the last follow-up. Univariate analysis revealed certain features like age, gender, response to therapy, and texture features like mean and kurtosis in CT images to be significant predictors of survival. In multivariate analysis, age (P = 0.006), gender (P = 0.004), treatment response (P< 0.0001), and two CT texture parameters: mean (P = 0.027) and kurtosis (P= 0.002) were independent prognostic factors of survival. Interpretation and Conclusion: CT-derived tumor heterogeneity (mean and kurtosis) complements clinical factors for predicting survival in NSCLC patients treated with CRT. Tumor radiomics warrants further validation as potential prognostic biomarkers for these patients.

Machine-Learning-Based Radiomics for Classifying Glioma Grade from Magnetic Resonance Images of the Brain.

Grading of gliomas is a piece of critical information related to prognosis and survival. Classifying glioma grade by semantic radiological features is subjective, requires multiple MRI sequences, is quite complex and clinically demanding, and can very often result in erroneous radiological diagnosis. We used a radiomics approach with machine learning classifiers to determine the grade of gliomas. Eighty-three patients with histopathologically proven gliomas underwent MRI of the brain. Whenever available, immunohistochemistry was additionally used to augment the histopathological diagnosis. Segmentation was performed manually on the T2W MR sequence using the TexRad texture analysis softwareTM, Version 3.10. Forty-two radiomics features, which included first-order features and shape features, were derived and compared between high-grade and low-grade gliomas. Features were selected by recursive feature elimination using a random forest algorithm method. The classification performance of the models was measured using accuracy, precision, recall, f1 score, and area under the curve (AUC) of the receiver operating characteristic curve. A 10-fold cross-validation was adopted to separate the training and the test data. The selected features were used to build five classifier models: support vector machine, random forest, gradient boost, naive Bayes, and AdaBoost classifiers. The random forest model performed the best, achieving an AUC of 0.81, an accuracy of 0.83, f1 score of 0.88, a recall of 0.93, and a precision of 0.85 for the test cohort. The results suggest that machine-learning-based radiomics features extracted from multiparametric MRI images can provide a non-invasive method for predicting glioma grades preoperatively. In the present study, we extracted the radiomics features from a single cross-sectional image of the T2W MRI sequence and utilized these features to build a fairly robust model to classify low-grade gliomas from high-grade gliomas (grade 4 gliomas).

Oncolytic immunovirotherapy for high-grade gliomas: A novel and an evolving therapeutic option.

Glioblastoma is one of the most difficult tumor types to manage, having high morbidity and mortality with available therapies (surgery, radiotherapy and chemotherapy). Immunotherapeutic agents like Oncolytic Viruses (OVs), Immune Checkpoint Inhibitors (ICIs), Chimeric Antigen Receptor (CAR) T cells and Natural Killer (NK) cell therapies are now being extensively used as experimental therapies in the management of glioblastoma. Oncolytic virotherapy is an emerging form of anti-cancer therapy, employing nature's own agents to target and destroy glioma cells. Several oncolytic viruses have demonstrated the ability to infect and lyse glioma cells by inducing apoptosis or triggering an anti-tumor immune response. In this mini-review, we discuss the role of OV therapy (OVT) in malignant gliomas with a special focus on ongoing and completed clinical trials and the ensuing challenges and perspectives thereof in subsequent sections.

Post-radiation treatment of 3,3'-diselenodipropionic acid augments cell kill by modulating DNA repair and cell migration pathways in A549 cells.

Aim of the present study was to test whether ionizing radiation (IR) treatment along with 3,3'-diselenodipropionic acid (DSePA), a redox active organodiselenide achieved better tumor control by suppressing the growth and migration of lung cancer cells. The results indicated that post-IR (2 Gy) treatment of DSePA (5 µM) led to a significantly higher cell death as compared to that of DSePA and IR treatments separately. Importantly, combinatorial treatment also showed reduction in the proportion of cancer stem cells and the clonogenic survival of A549 cells. The mechanistic studies indicated that combinatorial treatment although exhibited reductive environment (marked by decrease in ROS and increase of GSH/GSSG) at early time points (2-6 h postradiation), slowed DNA repair, inhibited epithelial-mesenchymal transition (EMT)/cell migration and induced significant level of apoptosis. DSePA mediated suppression of ATM/DNAPKs/p53 (DNA damage response signaling) and Akt/G-CSF (EMT) pathways appeared to be the major mechanism responsible for its radio-modulating activity. Finally, the combined treatment of IR (2 Gy × 4) and DSePA (0.1-0.25 mg/kg body weight daily through oral gavage) showed a significantly higher tumor suppression of the A549 xenograft as compared to that of DSePA and IR treatments separately in the mouse model. In conclusion, post-IR treatment of DSePA augmented cell kill by inhibiting DNA repair and cell migration in A549 cells.

Institutional Patterns of Care of Diffuse Intrinsic Pontine Glioma.

Background and Aim: Despite recent advances, the outcomes of diffuse intrinsic pontine glioma (DIPG) remain dismal. This is a retrospective study to understand the pattern of care and its impact on DIPG patients diagnosed over 5 years in a single institute. Subjects and Methods: DIPGs diagnosed between 2015 and 2019 were retrospectively reviewed to understand the demographics, clinical features, patterns of care, and outcomes. The usage of steroids and response to treatment were analyzed as per the available records and criteria. The re-irradiation cohort was propensity matched with patients with a progression-free survival (PFS) >6 months treated with supportive care alone based on PFS and age as a continuous variable. Survival analysis was performed using the Kaplan-Meier method, and Cox regression model was used to identify any potential prognostic factors. Results: One hundred and eighty-four patients were identified with demographic profiles similar to western population-based data in the literature. Of them, 42.4% were residents from outside the state of the institution. About 75.2% of patients completed their first radiotherapy treatment, of which only 5% and 6% had worsening clinical symptoms and persistent need for steroids 1 month posttreatment. On multivariate analysis, Lansky performance status <60 (P = 0.028) and cranial nerve IX and X (P = 0.026) involvement were associated with poor survival outcomes while receiving radiotherapy with better survival (P < 0.001). In the cohort of patients receiving radiotherapy, only re-irradiation (reRT) was associated with improved survival (P = 0.002). Conclusion: Many patient families still do not choose radiotherapy treatment, although it has a consistent and significant positive association with survival and steroid usage. reRT further improves outcomes in the selective cohorts. Involvement of cranial nerves IX and X needs improved care.

Demographics, Pattern of Care & Outcomes of Primary CNS Lymphoma- Experience from a Tertiary Care Cancer Center in India.

Primary CNS lymphoma (PCNSL) is a rare subtype of non-Hodgkin lymphoma with the worst outcomes amongst all extranodal lymphomas. There is a scarcity of data on real-world outcomes of primary CNS lymphoma (PCNSL) owing to the rarity of the disease. This study analyzed the demographic patterns, risk stratification, treatment regimens used, & outcomes of patients treated at Tata Memorial Center Mumbai, India. This is a retrospective analysis of newly diagnosed primary CNS lymphoma patients treated at our centre over seven years from January 2013 to December 2019. A total of 142 patients with PCNSL were diagnosed during this period. Thirty (21.1%) patients were deemed ineligible for any systemic or local therapies,ten patients were referred to other hospitals, two patients had relapsed disease, and one was excluded because age less than 18 years. Finally 99 patients were included in the final analysis. Among these 99 patients,72 patients (72.7%) were < 60 years,70 (70.7%) patients had Eastern cooperative oncology group (ECOG) performance status (PS) less than equal to 2. DLBCL was the most common histology (86.4%) while rests were high grade B cell NHL NOS (11.4%),Burkitt's Lymphoma(1%),Peripheral T-cell Lymphoma NOS (1.2%). Only one of 99 patients was positive for HIV serology. Multiple intracranial lesions were found in 59.5%. Surgical resection was performed in 28.4% of patients. Out of 63 patients in whom the International extranodal lymphoma study group (IELSG) score is available, 34(54%) were IELSG high-risk groups. As per Memorial Sloan Kettering Cancer Center (MSKCC) risk grouping, patients were almost equally distributed in all the risk groups, with 32(32.3%) patients in risk group 1 (age < 50 years), 36(36.4%) patients in risk group 2 (age > 50 years, KPS > = 70), and 31(31.3%) patients in risk group 3 age > 50 years, KPS < 70). First-line treatment with high dose methotrexate (HD-MTX) based regimens was administered to 92 (92.9%) patients, and 72.8% of these patients received rituximab. Of these 92 patients, 59 (64.1%) patients could complete induction, and 52 patients received consolidation. Thirty-one patients received high dose cytarabine based chemo consolidation, one patient underwent high dose chemotherapy followed by autologous stem cell transplantation (ACST), and 19 patients received whole-brain radiotherapy (WBRT) and 1 patient received temozolomide as consolidation regimen. Thus only 52 patients completed the entire course of induction with consolidation therapy. The response to treatment was assessed using International PCNSL Collaborative Group Criteria. Post completion of consolidation, 49(94.2%) patients had a complete response. With a median follow-up duration of 39.2 months, the median progression-free survival (PFS) and the median overall survival (OS) of the patients taken into the analysis (N = 99) were 21 and 37 months respectively. On multivariate analysis, age < 60 yrs, > = 5 HD-MTX cycles received & the use of rituximab predicted better OS.Outcomes of patients with PCNSL treated with HD-MTX based therapy are comparable to reported literature however a large proportion of patients do not undergo required treatment despite the curable nature of disease. Supplementary Information: The online version supplementary material available at 10.1007/s12288-022-01557-7.

Targeted nano-delivery of chemotherapy via intranasal route suppresses in vivo glioblastoma growth and prolongs survival in the intracranial mouse model.

Nanotechnology-based drug delivery platforms have shown great potential in overcoming the limitations of conventional therapy for glioblastoma (GBM). However, permeation across the blood-brain barrier (BBB), physiological complexity of the brain, and glioma targeting strategies cannot entirely meet the challenging requirements of distinctive therapeutic delivery stages. The objective of this research is to fabricate lipid nanoparticles (LNPs) for the co-delivery of paclitaxel (PTX) and miltefosine (HePc) a proapoptotic agent decorated with transferrin (Tf-PTX-LNPs) and investigate its anti-glioma activity both in vitro and in vivo orthotopic NOD/SCID GBM mouse model. The present study demonstrates the anti-glioma effect of the dual drug combination of PTX and proapoptotic HePc lipid-based transferrin receptor (TfR) targeted alternative delivery (direct nose to brain transportation) of the nanoparticulate system (Tf-PTX-LNPs, 364 ± 5 nm, -43 ± 9 mV) to overcome the O6-methylguanine-DNA methyltransferase induce drug-resistant for improving the effectiveness of GBM therapy. The resulting nasally targeted LNPs present good biocompatibility, stability, high BBB transcytosis through selective TfR-mediated uptake by tumor cells, and effective tumor penetration in the brain of GBM induced mice. We observed markedly enhanced anti-proliferative efficacy of the targeted LNPs in U87MG cells compared to free drug. Nasal targeted LNPs had shown significantly improved brain concentration (Cmax fivefold and AUC0-24 4.9 fold) with early tmax (0.5 h) than the free drug. In vivo intracranial GBM-bearing targeted LNPs treated mice exhibited significantly prolonged survival with improved anti-tumor efficacy accompanied by reduced toxicity compared to systemic Taxol® and nasal free drug. These findings indicate that the nasal delivery of targeted synergistic nanocarrier holds great promise as a non-invasive adjuvant chemotherapy therapy of GBM.

Using Artificial Intelligence for Optimization of the Processes and Resource Utilization in Radiotherapy.

The radiotherapy (RT) process from planning to treatment delivery is a multistep, complex operation involving numerous levels of human-machine interaction and requiring high precision. These steps are labor-intensive and time-consuming and require meticulous coordination between professionals with diverse expertise. We reviewed and summarized the current status and prospects of artificial intelligence and machine learning relevant to the various steps in RT treatment planning and delivery workflow specifically in low- and middle-income countries (LMICs). We also searched the PubMed database using the search terms (Artificial Intelligence OR Machine Learning OR Deep Learning OR Automation OR knowledge-based planning AND Radiotherapy) AND (list of Low- and Middle-Income Countries as defined by the World Bank at the time of writing this review). The search yielded a total of 90 results, of which results with first authors from the LMICs were chosen. The reference lists of retrieved articles were also reviewed to search for more studies. No language restrictions were imposed. A total of 20 research items with unique study objectives conducted with the aim of enhancing RT processes were examined in detail. Artificial intelligence and machine learning can improve the overall efficiency of RT processes by reducing human intervention, aiding decision making, and efficiently executing lengthy, repetitive tasks. This improvement could permit the radiation oncologist to redistribute resources and focus on responsibilities such as patient counseling, education, and research, especially in resource-constrained LMICs.

Predicting IDH subtype of grade 4 astrocytoma and glioblastoma from tumor radiomic patterns extracted from multiparametric magnetic resonance images using a machine learning approach.

Background and purpose: Semantic imaging features have been used for molecular subclassification of high-grade gliomas. Radiomics-based prediction of molecular subgroups has the potential to strategize and individualize therapy. Using MRI texture features, we propose to distinguish between IDH wild type and IDH mutant type high grade gliomas. Methods: Between 2013 and 2020, 100 patients were retrospectively analyzed for the radiomics study. Immunohistochemistry of the pathological specimen was used to initially identify patients for the IDH mutant/wild phenotype and was then confirmed by Sanger's sequencing. Image texture analysis was performed on contrast-enhanced T1 (T1C) and T2 weighted (T2W) MR images. Manual segmentation was performed on MR image slices followed by single-slice multiple sampling image augmentation. Both whole tumor multislice segmentation and single-slice multiple sampling approaches were used to arrive at the best model. Radiomic features were extracted, which included first-order features, second-order (GLCM-Grey level co-occurrence matrix), and shape features. Feature enrichment was done using LASSO (Least Absolute Shrinkage and Selection Operator) regression, followed by radiomic classification using Support Vector Machine (SVM) and a 10-fold cross-validation strategy for model development. The area under the Receiver Operator Characteristic (ROC) curve and predictive accuracy were used as diagnostic metrics to evaluate the model to classify IDH mutant and wild-type subgroups. Results: Multislice analysis resulted in a better model compared to the single-slice multiple-sampling approach. A total of 164 MR-based texture features were extracted, out of which LASSO regression identified 14 distinctive GLCM features for the endpoint, which were used for further model development. The best model was achieved by using combined T1C and T2W MR images using a Quadratic Support Vector Machine Classifier and a 10-fold internal cross-validation approach, which demonstrated a predictive accuracy of 89% with an AUC of 0.89 for each IDH mutant and IDH wild subgroup. Conclusion: A machine learning classifier of radiomic features extracted from multiparametric MRI images (T1C and T2w) provides important diagnostic information for the non-invasive prediction of the IDH mutant or wild-type phenotype of high-grade gliomas and may have potential use in either escalating or de-escalating adjuvant therapy for gliomas or for using targeted agents in the future.

Classifying primary central nervous system lymphoma from glioblastoma using deep learning and radiomics based machine learning approach - a systematic review and meta-analysis.

Background: Glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) are common in elderly yet difficult to differentiate on MRI. Their management and prognosis are quite different. Recent surge of interest in predictive analytics, using machine learning (ML) from radiomic features and deep learning (DL) for diagnosing, predicting response and prognosticating disease has evinced interest among radiologists and clinicians. The objective of this systematic review and meta-analysis was to evaluate the deep learning & ML algorithms in classifying PCNSL from GBM. Methods: The authors performed a systematic review of the literature from MEDLINE, EMBASE and the Cochrane central trials register for the search strategy in accordance with PRISMA guidelines to select and evaluate studies that included themes of ML, DL, AI, GBM, PCNSL. All studies reporting on ML algorithms or DL that for differentiating PCNSL from GBM on MR imaging were included. These studies were further narrowed down to focus on works published between 2018 and 2021. Two researchers independently conducted the literature screening, database extraction and risk bias assessment. The extracted data was synthesised and analysed by forest plots. Outcomes assessed were test characteristics such as accuracy, sensitivity, specificity and balanced accuracy. Results: Ten articles meeting the eligibility criteria were identified addressing use of ML and DL in training and validation classifiers to distinguish PCNSL from GBM on MR imaging. The total sample size was 1311 in the included studies. ML approach was used in 6 studies while DL in 4 studies. The lowest reported sensitivity was 80%, while the highest reported sensitivity was 99% in studies in which ML and DL was directly compared with the gold standard histopathology. The lowest reported specificity was 87% while the highest reported specificity was 100%. The highest reported balanced accuracy was 100% and the lowest was 84%. Conclusions: Extensive search of the database revealed a limited number of studies that have applied ML or DL to differentiate PCNSL from GBM. Of the currently published studies, Both DL & ML algorithms have demonstrated encouraging results and certainly have the potential to aid neurooncologists in taking preoperative decisions in the future leading to not only reduction in morbidities but also be cost effective.