Identifying patients suitable for targeted adjuvant therapy: advances in the field of developing biomarkers for tumor recurrence following irradiation.

Introduction: Radiation therapy (RT) is commonly used to treat cancer in conjunction with chemotherapy, immunotherapy, and targeted therapies. Despite the effectiveness of RT, tumor recurrence due to treatment resistance still lead to treatment failure. RT-specific biomarkers are currently lacking and remain challenging to investigate with existing data since, for many common malignancies, standard of care (SOC) paradigms involve the administration of RT in conjunction with other agents. Areas Covered: Established clinically relevant biomarkers are used in surveillance, as prognostic indicators, and sometimes for treatment planning; however, the inability to intercept early recurrence or predict upfront resistance to treatment remains a significant challenge that limits the selection of patients for adjuvant therapy. We discuss attempts at intercepting early failure. We examine biomarkers that have made it into the clinic where they are used for treatment monitoring and management alteration, and novel biomarkers that lead the field with targeted adjuvant therapy seeking to harness these. Expert Opinion: Given the growth of data correlating interventions with omic analysis toward identifying biomarkers of radiation resistance, more robust markers of recurrence that link to biology will increasingly be leveraged toward targeted adjuvant therapy to make a successful transition to the clinic in the coming years.

AI-Driven Image Analysis in Central Nervous System Tumors-Traditional Machine Learning, Deep Learning and Hybrid Models.

The interpretation of imaging in medicine in general and in oncology specifically remains problematic due to several limitations which include the need to incorporate detailed clinical history, patient and disease-specific history, clinical exam features, previous and ongoing treatment, and account for the dependency on reproducible human interpretation of multiple factors with incomplete data linkage. To standardize reporting, minimize bias, expedite management, and improve outcomes, the use of Artificial Intelligence (AI) has gained significant prominence in imaging analysis. In oncology, AI methods have as a result been explored in most cancer types with ongoing progress in employing AI towards imaging for oncology treatment, assessing treatment response, and understanding and communicating prognosis. Challenges remain with limited available data sets, variability in imaging changes over time augmented by a growing heterogeneity in analysis approaches. We review the imaging analysis workflow and examine how hand-crafted features also referred to as traditional Machine Learning (ML), Deep Learning (DL) approaches, and hybrid analyses, are being employed in AI-driven imaging analysis in central nervous system tumors. ML, DL, and hybrid approaches coexist, and their combination may produce superior results although data in this space is as yet novel, and conclusions and pitfalls have yet to be fully explored. We note the growing technical complexities that may become increasingly separated from the clinic and enforce the acute need for clinician engagement to guide progress and ensure that conclusions derived from AI-driven imaging analysis reflect that same level of scrutiny lent to other avenues of clinical research.

LITHIUM-INDUCED NEPHROGENIC DIABETES INSIPIDUS RESPONSIVE TO DESMOPRESSIN.

Nephrogenic diabetes insipidus (NDI) is the most common renal side effect seen with lithium therapy. Persisting cases after the cessation of the therapy may be seen when lithium therapy is continued for too long. Although desmopressin treatment is not one of the accepted treatment modalities for NDI, there are few reports using desmopressin treatment in unresponsive cases. Herein, we reported the fourth lithium-induced NDI case in the literature responsive to desmopressin therapy.

Symmetry conditions for type II multiferroicity in commensurate magnetic structures.

Type II multiferroics are magnetically ordered phases that exhibit ferroelectricity as a magnetic induced effect. We show that in single-k magnetic phases the presence in the paramagnetic phase of non-symmorphic symmetry combined with some specific type of magnetic propagation vector can be sufficient for the occurrence of this type of multiferroic behaviour. Other symmetry scenarios especially favourable for spin driven multiferroicity are also presented. We review and classify known type II multiferroics under this viewpoint. In addition, some other magnetic phases which due to their symmetry properties can exhibit type II multiferroicity are pointed out.

"Stripping" to prevent prolonged air leak; is there a future in the past?

BACKGROUND: A number of technical precautions and many synthetic or biological materials have been suggested to reduce the frequency of prolonged air leak (PAL) following lung resection. Preserving the three-dimensional properties of the remaining lung parenchyma may prevent this complication to some extent. This study presents our experience with an old technique called "stripping" for the division of incomplete fissures to preserve the original shape of the remaining lung with the hope that this will minimize PAL-related problems. METHODS: 262 consecutive patients with incomplete fissures underwent lobectomy or bilobectomy. Stripping was employed for the division of incomplete fissures in Group S (Study arm; n = 148) and a cut-and-sew technique or staplers were used in Group C (Control arm; n = 114). To evaluate a possible learning curve effect with this technique, Group S was further divided into two subgroups, designated the initial experience (Group S (IE)) and the late experience group (Group S (LE)) and consisting of the first 1/3 (n = 50) and remaining 2/3 (n = 98) of patients, respectively. The frequency of PAL and other related morbidities were investigated. RESULTS: Morbidity and mortality rates were comparable between Group S and C (10 % vs. 8.7 % and 2 % vs. 2.6 %; P = 0.83 and P = 0.96), as was the frequency of PAL, which occurred in 12 (8.1 %) and 13 (11.4 %) patients ( P = 0.40), respectively. When each of the subgroups was compared with Group C, PAL occurred in 9 (18 %) patients in Group S(IE) ( P = n. s.) but only in 3 (3 %) patients in Group S(LE) ( P = 0.03). There was also more postoperative persistent air space in Group C, without this difference reaching statistical significance. CONCLUSION: This study suggests that preservation of the original shape of the remaining lung might decrease the incidence of PAL in patients with relatively healthy lung tissue. An actual favorable effect of stripping over other techniques emerges only when the technique is precisely applied, which is only possible with experience.

Pulmonary echinococcosis (hydatidosis) in children: results of surgical treatment.

From 1986-1996, 33 children with 49 pulmonary hydatid cysts underwent surgical treatment in Vienna and Istanbul. Cysts were unilateral in 28 and bilateral in 5 cases; unruptured cysts (URC) were diagnosed in 19 patients, and 14 children presented with ruptured cysts (RC). Ten patients had cysts in other organs (liver, spleen, central nervous system) in addition to pulmonary cysts. Diagnosis was primarily based on chest X-ray and computed tomography scan. In Austrian children, a new combination of serological tests was used successfully (71% positive). The standard surgical procedure was cystotomy followed by capitonnage. The main postoperative complications were fever and wound infection. There were two recurrences after a mean follow-up of 4.8 years, and one patient died because of multiple organ involvement. We conclude that the therapy of choice in pediatric pulmonary hydatidosis is complete surgical elimination of the cyst by cystotomy and capitonnage, whereas more extended resections should be avoided. Ideally, benzimidazole treatment should be combined with surgery. New serological tests can improve diagnostic accuracy.